gsc_extractor_v8.6.ipynb

{
  "cells": [
    {
      "cell_type": "code",
      "execution_count": 1,
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "nYD-rya2B9sP",
        "outputId": "826d8d73-ff41-42f1-8eaa-3a32ce3b2b83",
        "tags": [
          "def"
        ]
      },
      "outputs": [
        {
          "name": "stderr",
          "output_type": "stream",
          "text": [
            "[nltk_data] Downloading package averaged_perceptron_tagger to\n",
            "[nltk_data]     C:\\Users\\Giovanni Sacheli\\AppData\\Roaming\\nltk_data...\n",
            "[nltk_data]   Package averaged_perceptron_tagger is already up-to-\n",
            "[nltk_data]       date!\n",
            "[nltk_data] Downloading package omw to C:\\Users\\Giovanni\n",
            "[nltk_data]     Sacheli\\AppData\\Roaming\\nltk_data...\n",
            "[nltk_data]   Package omw is already up-to-date!\n",
            "[nltk_data] Downloading package punkt to C:\\Users\\Giovanni\n",
            "[nltk_data]     Sacheli\\AppData\\Roaming\\nltk_data...\n",
            "[nltk_data]   Package punkt is already up-to-date!\n",
            "[nltk_data] Downloading package stopwords to C:\\Users\\Giovanni\n",
            "[nltk_data]     Sacheli\\AppData\\Roaming\\nltk_data...\n",
            "[nltk_data]   Package stopwords is already up-to-date!\n",
            "[nltk_data] Downloading package wordnet to C:\\Users\\Giovanni\n",
            "[nltk_data]     Sacheli\\AppData\\Roaming\\nltk_data...\n",
            "[nltk_data]   Package wordnet is already up-to-date!\n"
          ]
        }
      ],
      "source": [
        "# ----------- Importazione delle librerie standard e di terze parti -----------\n",
        "# Moduli per la manipolazione dei dati e per operazioni matematiche\n",
        "import pandas as pd\n",
        "import numpy as np\n",
        "import math\n",
        "import re\n",
        "import json\n",
        "from collections import Counter\n",
        "from operator import itemgetter\n",
        "import string\n",
        "# Moduli per le operazioni con le date\n",
        "import datetime\n",
        "from datetime import datetime, timedelta\n",
        "import time\n",
        "# Moduli per la gestione dei file e delle directory\n",
        "import os\n",
        "# Moduli per la visualizzazione dei dati\n",
        "import matplotlib.pyplot as plt\n",
        "import seaborn as sns\n",
        "# Moduli per la gestione delle richieste HTTP e per la manipolazione del HTML\n",
        "import requests\n",
        "from fake_useragent import UserAgent\n",
        "from bs4 import BeautifulSoup\n",
        "from lxml import html\n",
        "# Moduli per la gestione delle interfacce utente\n",
        "import tkinter as tk\n",
        "from tkinter import messagebox\n",
        "# Moduli per l'apprendimento automatico e l'analisi del testo\n",
        "import nltk\n",
        "#from nltk.corpus import stopwords\n",
        "from nltk.corpus import stopwords as nltk_stopwords\n",
        "\n",
        "\n",
        "from nltk.stem import WordNetLemmatizer\n",
        "\n",
        "from nltk.tokenize import word_tokenize\n",
        "# Scarica i pacchetti necessari di nltk se non sono già presenti\n",
        "nltk.download('averaged_perceptron_tagger')\n",
        "nltk.download('omw')\n",
        "nltk.download('punkt')\n",
        "nltk.download('stopwords')\n",
        "nltk.download('wordnet')\n",
        "# Moduli specifici per l'analisi e la manipolazione del testo in italiano\n",
        "import spacy\n",
        "\n",
        "# Modulo per l'interazione con Google Search Console\n",
        "# pip install git+https://github.com/joshcarty/google-searchconsole\n",
        "import searchconsole\n",
        "# Modulo per la visualizzazione della barra di avanzamento\n",
        "from tqdm import tqdm"
      ]
    },
    {
      "cell_type": "code",
      "execution_count": 292,
      "metadata": {},
      "outputs": [],
      "source": [
        "## OPZIONI ########################################################\n",
        "## LINGUA #########################################################\n",
        "language = 'it' # it/en\n",
        "\n",
        "## DATI GSC #######################################################\n",
        "## number of days to split into segments min 3 max 365\n",
        "giorni = 31 # valore da 1 a 480\n",
        "# filtri URL per chiamate GSC\n",
        "contains_gsc = \"\"\n",
        "# filtro COUNTRY, un solo valore - sigle country https://en.wikipedia.org/wiki/ISO_3166-1_alpha-3\n",
        "countryCall=\"\" # ITA, USA, GBR, DEU, FRA, ...\n",
        "\n",
        "## BRAND ###############################################################\n",
        "query_brand = \"evemilano|eve milano|sacheli\"\n",
        "\n",
        "## HTTP CRAWLER ##########################################################\n",
        "## massime richieste crawler, min 1\n",
        "counter_max = 1\n",
        "# pausa tra una chiamata http e l'altra del title crawler\n",
        "attesa=0\n",
        "# Opzioni per la scelta dell'User-Agent per la scansione\n",
        "user_agent_option = 'fixed'  # Opzioni: 'random', 'chrome', 'fixed'\n",
        "# filtri URL da scansionare | separatore\n",
        "include=\"\"\n",
        "exclude=\"\"\n",
        "\n",
        "## PREVISIONI ################################################\n",
        "previsioni = 'n' # y/n\n",
        "## FORMATTAZIONE ########################################################\n",
        "formattazione = 'n' # y/n\n",
        "## FILTRI ###############################################################\n",
        "min_imp = 100 # valore libero da 1 a infinito\n",
        "max_pos = 100 # 1-100"
      ]
    },
    {
      "cell_type": "code",
      "execution_count": 168,
      "metadata": {},
      "outputs": [
        {
          "name": "stdout",
          "output_type": "stream",
          "text": [
            "it loaded\n"
          ]
        }
      ],
      "source": [
        "## LOADING NLP ################################################################\n",
        "if language == 'it':\n",
        "    # ITALIANO\n",
        "    # update\n",
        "    # python -m spacy download it_core_news_lg\n",
        "    #nlp = spacy.load(\"it_core_news_lg\", disable=[\"tagger\", \"parser\", \"entityrecognizer\"])\n",
        "    from nltk.stem.snowball import SnowballStemmer\n",
        "    nlp = spacy.load(\"it_core_news_lg\", disable=[\"parser\", \"ner\"])\n",
        "    stemmer = SnowballStemmer(\"italian\")\n",
        "    stopwords = nltk_stopwords.words('italian')\n",
        "    gpt_language = 'italiano'\n",
        "elif language == 'en':\n",
        "    # INGLESE\n",
        "    # Download the English model\n",
        "    # python -m spacy download en_core_web_lg\n",
        "    #nlp = spacy.load(\"en_core_web_lg\", disable=[\"tagger\", \"parser\", \"entity_recognizer\"])\n",
        "    from nltk.stem import PorterStemmer\n",
        "    nlp = spacy.load(\"en_core_web_lg\", disable=[\"parser\", \"ner\"])\n",
        "    stemmer = PorterStemmer()\n",
        "    stopwords = nltk_stopwords.words('english')\n",
        "    gpt_language = 'inglese'\n",
        "print(f'{language} loaded')"
      ]
    },
    {
      "cell_type": "code",
      "execution_count": 169,
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "_cKyxRbmFGuj",
        "outputId": "48aa1d73-0d47-45f7-bf4d-80bd97851383"
      },
      "outputs": [
        {
          "name": "stdout",
          "output_type": "stream",
          "text": [
            "Please visit this URL to authorize this application: https://accounts.google.com/o/oauth2/auth?response_type=code&client_id=615773305903-ieefueojceq5624v7e9otk5clcneulpm.apps.googleusercontent.com&redirect_uri=http%3A%2F%2Flocalhost%3A8080%2F&scope=https%3A%2F%2Fwww.googleapis.com%2Fauth%2Fwebmasters.readonly&state=xB8g64nxWhUviMMMKVRC2KRZcfl1oh&access_type=offline\n"
          ]
        }
      ],
      "source": [
        "# Get the absolute path of the credentials file\n",
        "creds_path = os.path.abspath(\"client_secret_.json\")\n",
        "# Load the client configuration from the file\n",
        "with open(creds_path, 'r') as f:\n",
        "    client_config = json.load(f)\n",
        "# Authenticate with the Search Console API\n",
        "#account = searchconsole.authenticate(client_config=client_config, serialize='credentials.json', flow='console')\n",
        "account = searchconsole.authenticate(client_config=client_config, serialize='credentials.json', flow='web')"
      ]
    },
    {
      "cell_type": "code",
      "execution_count": 170,
      "metadata": {},
      "outputs": [
        {
          "name": "stdout",
          "output_type": "stream",
          "text": [
            "Hai selezionato la proprietà https://www.evemilano.com/\n"
          ]
        }
      ],
      "source": [
        "# Crea una finestra di dialogo per mostrare le proprietà filtrate\n",
        "\n",
        "import tkinter as tk\n",
        "from tkinter import messagebox\n",
        "\n",
        "# Funzione per mostrare le proprietà filtrate\n",
        "def show_properties(properties):\n",
        "    def select_property():\n",
        "        nonlocal selected\n",
        "        try:\n",
        "            selected = int(lb.curselection()[0])\n",
        "            root.destroy()\n",
        "        except:\n",
        "            messagebox.showerror(\"Errore\", \"Devi selezionare una proprietà.\")\n",
        "\n",
        "    root = tk.Tk()\n",
        "    root.title(\"Proprietà filtrate\")\n",
        "    root.geometry(\"640x480\")\n",
        "    lb = tk.Listbox(root)\n",
        "    for prop in properties:\n",
        "        lb.insert(tk.END, prop.url)\n",
        "    lb.pack(fill=tk.BOTH, expand=True)\n",
        "    select_button = tk.Button(root, text=\"Seleziona\", command=select_property)\n",
        "    select_button.pack(side=tk.BOTTOM, pady=10)\n",
        "    selected = None\n",
        "    root.mainloop()\n",
        "    return selected\n",
        "\n",
        "while True:\n",
        "    # Chiede all'utente di inserire una parola chiave\n",
        "    keyword = input(\"Inserisci la parola chiave per il filtro (oppure digita 'exit' per uscire): \")\n",
        "    if keyword.lower() == 'exit':\n",
        "        print(\"Script interrotto dall'utente.\")\n",
        "        break\n",
        "\n",
        "    # Filtra le proprietà in base alla parola chiave\n",
        "    filtered_properties = [prop for prop in account.webproperties if keyword in prop.url]\n",
        "    \n",
        "    # Gestisce i casi di nessuna proprietà trovata\n",
        "    if len(filtered_properties) == 0:\n",
        "        print(\"Nessuna proprietà trovata. Riprova.\")\n",
        "        continue\n",
        "\n",
        "    # Mostra la finestra con le proprietà filtrate\n",
        "    selected_index = show_properties(filtered_properties)\n",
        "    if selected_index is None:\n",
        "        print(\"Nessuna proprietà selezionata.\")\n",
        "    else:\n",
        "        webproperty = filtered_properties[selected_index]\n",
        "        print(f\"Hai selezionato la proprietà {webproperty.url}\")\n",
        "        break\n"
      ]
    },
    {
      "cell_type": "code",
      "execution_count": 171,
      "metadata": {},
      "outputs": [
        {
          "name": "stdout",
          "output_type": "stream",
          "text": [
            "Esiste. L'URL https://www.evemilano.com/ ha restituito uno status code 200\n"
          ]
        }
      ],
      "source": [
        "# se profilo GSC dominio, trasforma in URL\n",
        "if webproperty.url.startswith(\"sc-domain:\"):\n",
        "    url = \"https://\" + webproperty.url[len(\"sc-domain:\"):]\n",
        "    # prova a connetterti al sito\n",
        "    try:\n",
        "        response = requests.get(url)\n",
        "        if response.status_code == 200:\n",
        "            print(f\"Esiste. L'URL {url} ha restituito uno status code {response.status_code}\")\n",
        "        else:\n",
        "            print(f\"Non raggiungibile. L'URL {url} ha restituito uno status code {response.status_code}\")\n",
        "    except requests.exceptions.ConnectionError as e:\n",
        "        print(f\"Errore di connessione: {e}\")\n",
        "else:\n",
        "    url = webproperty.url\n",
        "    # prova a connetterti al sito\n",
        "    try:\n",
        "        response = requests.get(webproperty.url)\n",
        "        if response.status_code == 200:\n",
        "            print(f\"Esiste. L'URL {webproperty.url} ha restituito uno status code {response.status_code}\")\n",
        "        else:\n",
        "            print(f\"Non raggiungibile. L'URL {webproperty.url} ha restituito uno status code {response.status_code}\")\n",
        "    except requests.exceptions.ConnectionError as e:\n",
        "        print(f\"Errore di connessione: {e}\")"
      ]
    },
    {
      "cell_type": "code",
      "execution_count": 320,
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "KeGcx62OTrBe",
        "outputId": "66df7916-a8f5-42c3-b4ae-cb951f927eb7"
      },
      "outputs": [
        {
          "data": {
            "text/plain": [
              "<searchconsole.account.WebProperty(url='https://www.evemilano.com/')>"
            ]
          },
          "execution_count": 320,
          "metadata": {},
          "output_type": "execute_result"
        }
      ],
      "source": [
        "##########################################\n",
        "# opzione UX selezione sito web da lista #\n",
        "##########################################\n",
        "# usare pagina di selezione sito web già presente in altri tool sul server\n",
        "\n",
        "# webproperty=account[str(property_name)]\n",
        "# https://github.com/joshcarty/google-searchconsole\n",
        "\n",
        "def extract_gsc_data(webproperty, start, stop, countryCall, contains_gsc, *args):\n",
        " if webproperty is not None:\n",
        "   print(f'Extracting data for {webproperty}')\n",
        "   gsc_data = webproperty.query.range(start, stop).dimension(*args).filter('country',countryCall,'contains').filter('page',contains_gsc,'contains').get()\n",
        "   return gsc_data\n",
        " else:\n",
        "   print('Webproperty not found, please select the correct one')\n",
        "   return None\n",
        "\n",
        "webproperty"
      ]
    },
    {
      "cell_type": "code",
      "execution_count": 173,
      "metadata": {},
      "outputs": [
        {
          "name": "stdout",
          "output_type": "stream",
          "text": [
            "GSC_EXT_evemilano.com_365days_1crawls_20231205_2121\n",
            "output/evemilano.com\n",
            "GSC_EXT_evemilano.com_365days_1crawls_20231205_2121.xlsx\n"
          ]
        }
      ],
      "source": [
        "# crea pattern filename\n",
        "# Ripulisci il nome della proprietà\n",
        "property_name = webproperty.url.replace('https://', '').replace('http://', '').replace('www.', '').replace('/', '')\n",
        "# Ottieni la data e l'ora corrente\n",
        "now = datetime.now()\n",
        "# Formatta la data e l'ora in una stringa\n",
        "now_str = now.strftime(\"%Y%m%d_%H%M\")\n",
        "# crea filename pattern\n",
        "file_name= f\"GSC_EXT_{property_name}_{giorni}days_{counter_max}crawls_{now_str}\"\n",
        "file_name = file_name.replace(\":\", \"-\")\n",
        "\n",
        "print(file_name)\n",
        "\n",
        "# Specifica la cartella di output\n",
        "output_dir = \"output\"\n",
        "if not os.path.exists(output_dir):\n",
        "    os.makedirs(output_dir)\n",
        "# Crea il nome del file\n",
        "filename = f\"{file_name}.xlsx\"\n",
        "# crea cartella della property\n",
        "new_output_dir = f\"{output_dir}/{property_name}\"\n",
        "# Replace \":\" with \"-\" in filename\n",
        "new_output_dir=new_output_dir.replace(\":\", \"-\")\n",
        "filename=filename.replace(\":\", \"-\")\n",
        "# Crea la cartella se non esiste\n",
        "os.makedirs(new_output_dir, exist_ok=True)\n",
        "print(new_output_dir)\n",
        "print(filename)"
      ]
    },
    {
      "cell_type": "code",
      "execution_count": 330,
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 1633
        },
        "id": "Rem1-UiSKOYL",
        "outputId": "e5d59b01-2786-4228-c24d-5695c0cafe71"
      },
      "outputs": [
        {
          "name": "stdout",
          "output_type": "stream",
          "text": [
            "(1/31) - Requests from 2023-11-03 00:00:00 to 2023-11-03 23:59:59\n",
            "Extracting query data for <searchconsole.account.WebProperty(url='https://www.evemilano.com/')>\n",
            "(2/31) - Requests from 2023-11-04 00:00:00 to 2023-11-04 23:59:59\n",
            "Extracting query data for <searchconsole.account.WebProperty(url='https://www.evemilano.com/')>\n",
            "(3/31) - Requests from 2023-11-05 00:00:00 to 2023-11-05 23:59:59\n",
            "Extracting query data for <searchconsole.account.WebProperty(url='https://www.evemilano.com/')>\n",
            "(4/31) - Requests from 2023-11-06 00:00:00 to 2023-11-06 23:59:59\n",
            "Extracting query data for <searchconsole.account.WebProperty(url='https://www.evemilano.com/')>\n",
            "(5/31) - Requests from 2023-11-07 00:00:00 to 2023-11-07 23:59:59\n",
            "Extracting query data for <searchconsole.account.WebProperty(url='https://www.evemilano.com/')>\n",
            "(6/31) - Requests from 2023-11-08 00:00:00 to 2023-11-08 23:59:59\n",
            "Extracting query data for <searchconsole.account.WebProperty(url='https://www.evemilano.com/')>\n",
            "(7/31) - Requests from 2023-11-09 00:00:00 to 2023-11-09 23:59:59\n",
            "Extracting query data for <searchconsole.account.WebProperty(url='https://www.evemilano.com/')>\n",
            "(8/31) - Requests from 2023-11-10 00:00:00 to 2023-11-10 23:59:59\n",
            "Extracting query data for <searchconsole.account.WebProperty(url='https://www.evemilano.com/')>\n",
            "(9/31) - Requests from 2023-11-11 00:00:00 to 2023-11-11 23:59:59\n",
            "Extracting query data for <searchconsole.account.WebProperty(url='https://www.evemilano.com/')>\n",
            "(10/31) - Requests from 2023-11-12 00:00:00 to 2023-11-12 23:59:59\n",
            "Extracting query data for <searchconsole.account.WebProperty(url='https://www.evemilano.com/')>\n",
            "(11/31) - Requests from 2023-11-13 00:00:00 to 2023-11-13 23:59:59\n",
            "Extracting query data for <searchconsole.account.WebProperty(url='https://www.evemilano.com/')>\n",
            "(12/31) - Requests from 2023-11-14 00:00:00 to 2023-11-14 23:59:59\n",
            "Extracting query data for <searchconsole.account.WebProperty(url='https://www.evemilano.com/')>\n",
            "(13/31) - Requests from 2023-11-15 00:00:00 to 2023-11-15 23:59:59\n",
            "Extracting query data for <searchconsole.account.WebProperty(url='https://www.evemilano.com/')>\n",
            "(14/31) - Requests from 2023-11-16 00:00:00 to 2023-11-16 23:59:59\n",
            "Extracting query data for <searchconsole.account.WebProperty(url='https://www.evemilano.com/')>\n",
            "(15/31) - Requests from 2023-11-17 00:00:00 to 2023-11-17 23:59:59\n",
            "Extracting query data for <searchconsole.account.WebProperty(url='https://www.evemilano.com/')>\n",
            "(16/31) - Requests from 2023-11-18 00:00:00 to 2023-11-18 23:59:59\n",
            "Extracting query data for <searchconsole.account.WebProperty(url='https://www.evemilano.com/')>\n",
            "(17/31) - Requests from 2023-11-19 00:00:00 to 2023-11-19 23:59:59\n",
            "Extracting query data for <searchconsole.account.WebProperty(url='https://www.evemilano.com/')>\n",
            "(18/31) - Requests from 2023-11-20 00:00:00 to 2023-11-20 23:59:59\n",
            "Extracting query data for <searchconsole.account.WebProperty(url='https://www.evemilano.com/')>\n",
            "(19/31) - Requests from 2023-11-21 00:00:00 to 2023-11-21 23:59:59\n",
            "Extracting query data for <searchconsole.account.WebProperty(url='https://www.evemilano.com/')>\n",
            "(20/31) - Requests from 2023-11-22 00:00:00 to 2023-11-22 23:59:59\n",
            "Extracting query data for <searchconsole.account.WebProperty(url='https://www.evemilano.com/')>\n",
            "(21/31) - Requests from 2023-11-23 00:00:00 to 2023-11-23 23:59:59\n",
            "Extracting query data for <searchconsole.account.WebProperty(url='https://www.evemilano.com/')>\n",
            "(22/31) - Requests from 2023-11-24 00:00:00 to 2023-11-24 23:59:59\n",
            "Extracting query data for <searchconsole.account.WebProperty(url='https://www.evemilano.com/')>\n",
            "(23/31) - Requests from 2023-11-25 00:00:00 to 2023-11-25 23:59:59\n",
            "Extracting query data for <searchconsole.account.WebProperty(url='https://www.evemilano.com/')>\n",
            "(24/31) - Requests from 2023-11-26 00:00:00 to 2023-11-26 23:59:59\n",
            "Extracting query data for <searchconsole.account.WebProperty(url='https://www.evemilano.com/')>\n",
            "(25/31) - Requests from 2023-11-27 00:00:00 to 2023-11-27 23:59:59\n",
            "Extracting query data for <searchconsole.account.WebProperty(url='https://www.evemilano.com/')>\n",
            "(26/31) - Requests from 2023-11-28 00:00:00 to 2023-11-28 23:59:59\n",
            "Extracting query data for <searchconsole.account.WebProperty(url='https://www.evemilano.com/')>\n",
            "(27/31) - Requests from 2023-11-29 00:00:00 to 2023-11-29 23:59:59\n",
            "Extracting query data for <searchconsole.account.WebProperty(url='https://www.evemilano.com/')>\n",
            "(28/31) - Requests from 2023-11-30 00:00:00 to 2023-11-30 23:59:59\n",
            "Extracting query data for <searchconsole.account.WebProperty(url='https://www.evemilano.com/')>\n",
            "(29/31) - Requests from 2023-12-01 00:00:00 to 2023-12-01 23:59:59\n",
            "Extracting query data for <searchconsole.account.WebProperty(url='https://www.evemilano.com/')>\n",
            "(30/31) - Requests from 2023-12-02 00:00:00 to 2023-12-02 23:59:59\n",
            "Extracting query data for <searchconsole.account.WebProperty(url='https://www.evemilano.com/')>\n",
            "(31/31) - Requests from 2023-12-03 00:00:00 to 2023-12-03 23:59:59\n",
            "Extracting query data for <searchconsole.account.WebProperty(url='https://www.evemilano.com/')>\n",
            "Creazione df query e URL\n",
            "Rows df query: 241526\n"
          ]
        },
        {
          "data": {
            "text/html": [
              "<div>\n",
              "<style scoped>\n",
              "    .dataframe tbody tr th:only-of-type {\n",
              "        vertical-align: middle;\n",
              "    }\n",
              "\n",
              "    .dataframe tbody tr th {\n",
              "        vertical-align: top;\n",
              "    }\n",
              "\n",
              "    .dataframe thead th {\n",
              "        text-align: right;\n",
              "    }\n",
              "</style>\n",
              "<table border=\"1\" class=\"dataframe\">\n",
              "  <thead>\n",
              "    <tr style=\"text-align: right;\">\n",
              "      <th></th>\n",
              "      <th>country</th>\n",
              "      <th>device</th>\n",
              "      <th>query</th>\n",
              "      <th>page</th>\n",
              "      <th>clicks</th>\n",
              "      <th>impressions</th>\n",
              "      <th>ctr</th>\n",
              "      <th>position</th>\n",
              "    </tr>\n",
              "  </thead>\n",
              "  <tbody>\n",
              "    <tr>\n",
              "      <th>0</th>\n",
              "      <td>ita</td>\n",
              "      <td>DESKTOP</td>\n",
              "      <td>cdata xml</td>\n",
              "      <td>https://www.evemilano.com/cdata-xml/</td>\n",
              "      <td>3</td>\n",
              "      <td>3</td>\n",
              "      <td>100.00%</td>\n",
              "      <td>100.00%</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>1</th>\n",
              "      <td>ita</td>\n",
              "      <td>DESKTOP</td>\n",
              "      <td>python venv</td>\n",
              "      <td>https://www.evemilano.com/python-venv/</td>\n",
              "      <td>3</td>\n",
              "      <td>19</td>\n",
              "      <td>15.79%</td>\n",
              "      <td>300.00%</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>2</th>\n",
              "      <td>ita</td>\n",
              "      <td>DESKTOP</td>\n",
              "      <td>ambiente virtuale python</td>\n",
              "      <td>https://www.evemilano.com/python-venv/</td>\n",
              "      <td>2</td>\n",
              "      <td>2</td>\n",
              "      <td>100.00%</td>\n",
              "      <td>100.00%</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>3</th>\n",
              "      <td>ita</td>\n",
              "      <td>DESKTOP</td>\n",
              "      <td>async defer</td>\n",
              "      <td>https://www.evemilano.com/async-defer/</td>\n",
              "      <td>2</td>\n",
              "      <td>2</td>\n",
              "      <td>100.00%</td>\n",
              "      <td>100.00%</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>4</th>\n",
              "      <td>ita</td>\n",
              "      <td>DESKTOP</td>\n",
              "      <td>venv python</td>\n",
              "      <td>https://www.evemilano.com/python-venv/</td>\n",
              "      <td>2</td>\n",
              "      <td>8</td>\n",
              "      <td>25.00%</td>\n",
              "      <td>262.50%</td>\n",
              "    </tr>\n",
              "  </tbody>\n",
              "</table>\n",
              "</div>"
            ],
            "text/plain": [
              "  country   device                     query  \\\n",
              "0     ita  DESKTOP                 cdata xml   \n",
              "1     ita  DESKTOP               python venv   \n",
              "2     ita  DESKTOP  ambiente virtuale python   \n",
              "3     ita  DESKTOP               async defer   \n",
              "4     ita  DESKTOP               venv python   \n",
              "\n",
              "                                     page  clicks  impressions     ctr  \\\n",
              "0    https://www.evemilano.com/cdata-xml/       3            3 100.00%   \n",
              "1  https://www.evemilano.com/python-venv/       3           19  15.79%   \n",
              "2  https://www.evemilano.com/python-venv/       2            2 100.00%   \n",
              "3  https://www.evemilano.com/async-defer/       2            2 100.00%   \n",
              "4  https://www.evemilano.com/python-venv/       2            8  25.00%   \n",
              "\n",
              "   position  \n",
              "0   100.00%  \n",
              "1   300.00%  \n",
              "2   100.00%  \n",
              "3   100.00%  \n",
              "4   262.50%  "
            ]
          },
          "execution_count": 330,
          "metadata": {},
          "output_type": "execute_result"
        }
      ],
      "source": [
        "# Funzione per generare l'intervallo di date\n",
        "def get_date_range(num_days_back):\n",
        "    today = datetime.now()\n",
        "    start_date = today - timedelta(days=num_days_back+1)\n",
        "    end_date = today - timedelta(days=1)  # la data finale è ieri\n",
        "    return start_date.strftime('%Y-%m-%d'), end_date.strftime('%Y-%m-%d')\n",
        "\n",
        "# Imposta il periodo di tempo\n",
        "start_date, end_date = get_date_range(giorni)\n",
        "\n",
        "# Converti le date in formato datetime se sono stringhe\n",
        "if type(start_date) == str:\n",
        "    start_date = datetime.strptime(start_date, '%Y-%m-%d')\n",
        "if type(end_date) == str:\n",
        "    end_date = datetime.strptime(end_date, '%Y-%m-%d')\n",
        "\n",
        "# Crea segmenti di un giorno\n",
        "date_segments = [(start_date + timedelta(days=i), start_date + timedelta(days=i + 1) - timedelta(seconds=1))\n",
        "                 for i in range((end_date - start_date).days)]\n",
        "\n",
        "total_segments = len(date_segments)  # Calcola il numero totale di segmenti\n",
        "\n",
        "# Lista per memorizzare i dati di ogni segmento\n",
        "segment_dataQ = []\n",
        "\n",
        "max_attempts = 3  # Numero massimo di tentativi per chiamata\n",
        "\n",
        "# Ciclo su ogni segmento di date\n",
        "for index, (start, end) in enumerate(date_segments):\n",
        "#for start, end in date_segments:\n",
        "    completed = False\n",
        "    attempts = 0\n",
        "    no_data_found = False\n",
        "\n",
        "    while not completed and attempts < max_attempts:\n",
        "        try:\n",
        "            #print(f'Requests from {start} to {end}')\n",
        "            print(f'({index + 1}/{total_segments}) - Requests from {start} to {end}')\n",
        "            exQ = extract_gsc_data(webproperty, start, end, countryCall, contains_gsc,'country','device','query', 'page')\n",
        "\n",
        "        except Exception as e:\n",
        "            print(f\"Error: {e}\")\n",
        "            attempts += 1\n",
        "            print(f\"Retrying, attempt {attempts}/{max_attempts}...\")\n",
        "        else:\n",
        "            if exQ:\n",
        "                segment_dataQ.append(exQ.to_dataframe())\n",
        "                completed = True\n",
        "            else:\n",
        "                no_data_found = True\n",
        "                break  # Interrompi il ciclo while se non vengono trovati dati\n",
        "    if no_data_found:\n",
        "        print(f\"No data found for period {start} to {end}.\")\n",
        "\n",
        "# Concatenazione dei dati\n",
        "print('Creazione df query e URL')\n",
        "final_data = pd.concat(segment_dataQ, ignore_index=True)\n",
        "print(f'Rows df query: {final_data.shape[0]}')\n",
        "final_data.head(5)"
      ]
    },
    {
      "cell_type": "code",
      "execution_count": 322,
      "metadata": {},
      "outputs": [
        {
          "name": "stdout",
          "output_type": "stream",
          "text": [
            "Somma totale dei clicks: 2163\n",
            "Somma totale delle impressions: 345742\n"
          ]
        }
      ],
      "source": [
        "# Stampa la somma totale dei clicks e delle impressions\n",
        "total_clicks = final_data['clicks'].sum()\n",
        "total_impressions = final_data['impressions'].sum()\n",
        "print(\"Somma totale dei clicks:\", total_clicks)\n",
        "print(\"Somma totale delle impressions:\", total_impressions)"
      ]
    },
    {
      "cell_type": "code",
      "execution_count": 176,
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "_hKfTPD6mBkw",
        "outputId": "fdb92a71-71dc-41d5-d37e-4ada736be255"
      },
      "outputs": [
        {
          "name": "stdout",
          "output_type": "stream",
          "text": [
            "3301058 righe\n",
            "Somma totale dei clicks: 32311\n",
            "Somma totale delle impressions: 4545130\n"
          ]
        },
        {
          "data": {
            "text/html": [
              "<div>\n",
              "<style scoped>\n",
              "    .dataframe tbody tr th:only-of-type {\n",
              "        vertical-align: middle;\n",
              "    }\n",
              "\n",
              "    .dataframe tbody tr th {\n",
              "        vertical-align: top;\n",
              "    }\n",
              "\n",
              "    .dataframe thead th {\n",
              "        text-align: right;\n",
              "    }\n",
              "</style>\n",
              "<table border=\"1\" class=\"dataframe\">\n",
              "  <thead>\n",
              "    <tr style=\"text-align: right;\">\n",
              "      <th></th>\n",
              "      <th>country</th>\n",
              "      <th>device</th>\n",
              "      <th>query</th>\n",
              "      <th>page</th>\n",
              "      <th>clicks</th>\n",
              "      <th>impressions</th>\n",
              "      <th>ctr</th>\n",
              "      <th>position</th>\n",
              "    </tr>\n",
              "  </thead>\n",
              "  <tbody>\n",
              "    <tr>\n",
              "      <th>0</th>\n",
              "      <td>ita</td>\n",
              "      <td>DESKTOP</td>\n",
              "      <td>python virtual environment</td>\n",
              "      <td>https://www.evemilano.com/python-venv/</td>\n",
              "      <td>4</td>\n",
              "      <td>13</td>\n",
              "      <td>30.77%</td>\n",
              "      <td>2</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>1</th>\n",
              "      <td>che</td>\n",
              "      <td>DESKTOP</td>\n",
              "      <td>meglio ipv4 o ipv6</td>\n",
              "      <td>https://www.evemilano.com/ipv4-vs-ipv6/</td>\n",
              "      <td>1</td>\n",
              "      <td>1</td>\n",
              "      <td>100.00%</td>\n",
              "      <td>5</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>2</th>\n",
              "      <td>ita</td>\n",
              "      <td>DESKTOP</td>\n",
              "      <td>apache vs nginx</td>\n",
              "      <td>https://www.evemilano.com/apache-vs-nginx/</td>\n",
              "      <td>1</td>\n",
              "      <td>1</td>\n",
              "      <td>100.00%</td>\n",
              "      <td>1</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>3</th>\n",
              "      <td>ita</td>\n",
              "      <td>DESKTOP</td>\n",
              "      <td>cdata</td>\n",
              "      <td>https://www.evemilano.com/cdata-xml/</td>\n",
              "      <td>1</td>\n",
              "      <td>2</td>\n",
              "      <td>50.00%</td>\n",
              "      <td>2</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>4</th>\n",
              "      <td>ita</td>\n",
              "      <td>DESKTOP</td>\n",
              "      <td>come migrare un sito wordpress</td>\n",
              "      <td>https://www.evemilano.com/come-migrare-wordpre...</td>\n",
              "      <td>1</td>\n",
              "      <td>1</td>\n",
              "      <td>100.00%</td>\n",
              "      <td>1</td>\n",
              "    </tr>\n",
              "  </tbody>\n",
              "</table>\n",
              "</div>"
            ],
            "text/plain": [
              "  country   device                           query  \\\n",
              "0     ita  DESKTOP      python virtual environment   \n",
              "1     che  DESKTOP              meglio ipv4 o ipv6   \n",
              "2     ita  DESKTOP                 apache vs nginx   \n",
              "3     ita  DESKTOP                           cdata   \n",
              "4     ita  DESKTOP  come migrare un sito wordpress   \n",
              "\n",
              "                                                page  clicks  impressions  \\\n",
              "0             https://www.evemilano.com/python-venv/       4           13   \n",
              "1            https://www.evemilano.com/ipv4-vs-ipv6/       1            1   \n",
              "2         https://www.evemilano.com/apache-vs-nginx/       1            1   \n",
              "3               https://www.evemilano.com/cdata-xml/       1            2   \n",
              "4  https://www.evemilano.com/come-migrare-wordpre...       1            1   \n",
              "\n",
              "      ctr  position  \n",
              "0  30.77%         2  \n",
              "1 100.00%         5  \n",
              "2 100.00%         1  \n",
              "3  50.00%         2  \n",
              "4 100.00%         1  "
            ]
          },
          "execution_count": 176,
          "metadata": {},
          "output_type": "execute_result"
        }
      ],
      "source": [
        "# pulizia db raw \n",
        "# final_data contiene tutte le chiamate alle API\n",
        "final_data1=final_data.copy()\n",
        "######################################\n",
        "\n",
        "# funzione di verifica idoneità del df e pulizia righe\n",
        "def drop_rows_with_hash_and_empty_query(df):\n",
        "    # Controlla se le COLONNE necessarie sono presenti nel DataFrame\n",
        "    if 'page' not in df.columns or 'query' not in df.columns:\n",
        "        print(\"Il DataFrame non ha le colonne necessarie ('page' o 'query'). Operazione interrotta.\")\n",
        "        return df\n",
        "    \n",
        "    # aggregare url con # invece di rimuoverli\n",
        "    # Rimuovi righe con '#' nel campo 'page'\n",
        "    df = df[~df['page'].str.contains(\"#\")]\n",
        "    \n",
        "    # Rimuovi righe con valori NaN, Null o vuoti nel campo 'query'\n",
        "    df = df[df['query'].notnull() & (df['query'].str.strip() != '')]\n",
        "    return df\n",
        "\n",
        "# Controlla se il DataFrame esiste e ha almeno una riga\n",
        "if 'final_data1' in locals() and not final_data1.empty:\n",
        "    final_data1 = drop_rows_with_hash_and_empty_query(final_data1) # pulisci il dataframe\n",
        "    # print e show\n",
        "    print(f'{final_data1.shape[0]} righe')\n",
        "    final_data1.head(1)\n",
        "else:\n",
        "    print(\"Il DataFrame non esiste o è vuoto. Operazione interrotta.\")\n",
        "    raise SystemExit\n",
        "\n",
        "\n",
        "# Stampa la somma totale dei clicks e delle impressions\n",
        "total_clicks = final_data1['clicks'].sum()\n",
        "total_impressions = final_data1['impressions'].sum()\n",
        "\n",
        "print(\"Somma totale dei clicks:\", total_clicks)\n",
        "print(\"Somma totale delle impressions:\", total_impressions)\n",
        "# formatta position in numero intero\n",
        "final_data1['position'] = final_data1['position'].astype(int)\n",
        "final_data1.head(5)"
      ]
    },
    {
      "cell_type": "code",
      "execution_count": 177,
      "metadata": {},
      "outputs": [
        {
          "data": {
            "image/png": 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",
            "text/plain": [
              "<Figure size 1000x600 with 1 Axes>"
            ]
          },
          "metadata": {},
          "output_type": "display_data"
        }
      ],
      "source": [
        "# GFX\n",
        "# Raggruppare i dati per paese e calcolare la somma dei clicks\n",
        "grouped_data = final_data1.groupby('country').agg({\n",
        "    'clicks': 'sum',\n",
        "}).reset_index()\n",
        "\n",
        "# Selezionare i top 10 paesi in base ai clicks\n",
        "top_countries = grouped_data.sort_values(by='clicks', ascending=False).head(10)\n",
        "\n",
        "# Creare il grafico a barre multiple utilizzando i valori reali di clicks\n",
        "ax = top_countries.plot(kind='bar', x='country', y='clicks', figsize=(10, 6), legend=False)\n",
        "\n",
        "# Aggiungere i valori sopra le barre\n",
        "for i in ax.patches:\n",
        "    ax.text(i.get_x() + i.get_width()/2, i.get_height(), \n",
        "            str(round((i.get_height()), 2)), \n",
        "            fontsize=11, color='black', ha='center', va='bottom')\n",
        "\n",
        "plt.title('Top 10 Countries by Clicks')\n",
        "plt.ylabel('Clicks')\n",
        "plt.xlabel('Country')\n",
        "plt.savefig(f'{new_output_dir}/{file_name}_clicks_by_country.png', bbox_inches='tight', dpi=300)\n",
        "plt.show()\n",
        "plt.close()"
      ]
    },
    {
      "cell_type": "code",
      "execution_count": 178,
      "metadata": {},
      "outputs": [
        {
          "data": {
            "image/png": 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",
            "text/plain": [
              "<Figure size 1000x600 with 1 Axes>"
            ]
          },
          "metadata": {},
          "output_type": "display_data"
        }
      ],
      "source": [
        "# Raggruppare i dati per paese e calcolare la somma dei clicks\n",
        "grouped_data = final_data1.groupby('device').agg({\n",
        "    'clicks': 'sum',\n",
        "}).reset_index()\n",
        "\n",
        "# Selezionare i top 10 paesi in base ai clicks\n",
        "top_countries = grouped_data.sort_values(by='clicks', ascending=False).head(10)\n",
        "\n",
        "# Creare il grafico a barre multiple utilizzando i valori reali di clicks\n",
        "ax = top_countries.plot(kind='bar', x='device', y='clicks', figsize=(10, 6), legend=False)\n",
        "\n",
        "# Aggiungere i valori sopra le barre\n",
        "for i in ax.patches:\n",
        "    ax.text(i.get_x() + i.get_width()/2, i.get_height(), \n",
        "            str(round((i.get_height()), 2)), \n",
        "            fontsize=11, color='black', ha='center', va='bottom')\n",
        "\n",
        "plt.title('Top Devides by Clicks')\n",
        "plt.ylabel('Clicks')\n",
        "plt.xlabel('Device')\n",
        "plt.savefig(f'{new_output_dir}/{file_name}_clicks_by_device.png', bbox_inches='tight', dpi=300)\n",
        "plt.show()\n",
        "plt.close()"
      ]
    },
    {
      "cell_type": "code",
      "execution_count": 179,
      "metadata": {},
      "outputs": [],
      "source": [
        "# Funzione per calcolare la media ponderata\n",
        "def weighted_mean(values, weights):\n",
        "    return np.sum(values * weights) / np.sum(weights)"
      ]
    },
    {
      "cell_type": "code",
      "execution_count": 180,
      "metadata": {},
      "outputs": [],
      "source": [
        "# funzione formatta ctr\n",
        "def format_ctr(value):\n",
        "    if isinstance(value, float):\n",
        "        return value / 100  # Converti il valore percentuale in float\n",
        "    return value"
      ]
    },
    {
      "cell_type": "code",
      "execution_count": 181,
      "metadata": {},
      "outputs": [
        {
          "name": "stdout",
          "output_type": "stream",
          "text": [
            "Copiando i dati per la lavorazione...\n",
            "Creando la tabella pivot...\n",
            "Calcolando il CTR...\n",
            "Ordinando la tabella pivot per impressions...\n",
            "Formattando e rinominando la colonna 'position'...\n",
            "Applicando la formattazione al CTR...\n",
            "Ordinando le colonne...\n",
            "Calcolando la somma totale di clicks e impressions...\n",
            "Somma totale dei clicks: 32311\n",
            "Somma totale delle impressions: 4545130\n",
            "Rows: 94498\n"
          ]
        }
      ],
      "source": [
        "# tabella pivot query uniche da API\n",
        "print(\"Copiando i dati per la lavorazione...\")\n",
        "final_data2=final_data1.copy()\n",
        "\n",
        "# Crea una tabella pivot con multi-livello di indici\n",
        "print(\"Creando la tabella pivot...\")\n",
        "# Creazione della tabella pivot\n",
        "export_api_pvt = final_data2.pivot_table(\n",
        "    index=['query', 'page'], \n",
        "    values=['clicks', 'impressions', 'position'], \n",
        "    aggfunc={\n",
        "        'clicks': 'sum', \n",
        "        'impressions': 'sum',\n",
        "        'position': lambda x: weighted_mean(x, final_data2.loc[x.index, 'impressions'])\n",
        "    }\n",
        ")\n",
        "\n",
        "# Calcolo del CTR direttamente sul pivot table\n",
        "print(\"Calcolando il CTR...\")\n",
        "export_api_pvt['ctr'] = (export_api_pvt['clicks'] / export_api_pvt['impressions']) * 100\n",
        "\n",
        "# Ordina la tabella pivot in base alle impressions\n",
        "print(\"Ordinando la tabella pivot per impressions...\")\n",
        "export_api_pvt.sort_values(by='impressions', axis=0, ascending=False, inplace=True)\n",
        "\n",
        "# rinomina e formatta position\n",
        "print(\"Formattando e rinominando la colonna 'position'...\")\n",
        "export_api_pvt['position'] = export_api_pvt['position'].astype(int)\n",
        "export_api_pvt = export_api_pvt.rename(columns={'position': 'weighted avg position'})\n",
        "\n",
        "\n",
        "# Apply the formatting to the CTR column\n",
        "print(\"Applicando la formattazione al CTR...\")\n",
        "export_api_pvt['ctr'] = export_api_pvt['ctr'].apply(format_ctr)\n",
        "\n",
        "# ordina le colonne\n",
        "print(\"Ordinando le colonne...\")\n",
        "export_api_pvt = export_api_pvt.reindex(columns=['clicks', 'impressions', 'ctr', 'weighted avg position'])\n",
        "\n",
        "# Stampa la somma totale dei clicks e delle impressions\n",
        "print(\"Calcolando la somma totale di clicks e impressions...\")\n",
        "total_clicks = export_api_pvt['clicks'].sum()\n",
        "total_impressions = export_api_pvt['impressions'].sum()\n",
        "\n",
        "print(\"Somma totale dei clicks:\", total_clicks)\n",
        "print(\"Somma totale delle impressions:\", total_impressions)\n",
        "\n",
        "# Mostra la tabella pivot ordinata\n",
        "print(\"Rows: \" + str(export_api_pvt.shape[0]))\n",
        "export_api_pvt.head(10)\n",
        "\n",
        "\n",
        "# test con media calcolata fuori dalla pivot\n",
        "# da testare su larghi dataset\n",
        "if False:\n",
        "\n",
        "    # tabella pivot query uniche da API\n",
        "    # test speed senza vecchia funzione LAMBDA\n",
        "\n",
        "    print(\"Copiando i dati per la lavorazione...\")\n",
        "    final_data2=final_data1.copy()\n",
        "\n",
        "    # Calcola la posizione ponderata (weighted position) per ogni riga in final_data2\n",
        "    final_data2['weighted_position'] = final_data2['position'] * final_data2['impressions']\n",
        "\n",
        "    # Modifica la tabella pivot per usare il nuovo calcolo\n",
        "    export_api_pvt = final_data2.pivot_table(\n",
        "        index=['query', 'page'], \n",
        "        values=['clicks', 'impressions', 'weighted_position'], \n",
        "        aggfunc={\n",
        "            'clicks': 'sum', \n",
        "            'impressions': 'sum',\n",
        "            'weighted_position': 'sum'\n",
        "        }\n",
        "    )\n",
        "\n",
        "    # Calcola la posizione finale ponderata\n",
        "    export_api_pvt['position'] = export_api_pvt['weighted_position'] / export_api_pvt['impressions']\n",
        "    export_api_pvt.drop(columns=['weighted_position'], inplace=True)\n",
        "\n",
        "    # Calcolo del CTR direttamente sul pivot table\n",
        "    print(\"Calcolando il CTR...\")\n",
        "    export_api_pvt['ctr'] = (export_api_pvt['clicks'] / export_api_pvt['impressions']) * 100\n",
        "\n",
        "    # Ordina la tabella pivot in base alle impressions\n",
        "    print(\"Ordinando la tabella pivot per impressions...\")\n",
        "    export_api_pvt.sort_values(by='impressions', axis=0, ascending=False, inplace=True)\n",
        "\n",
        "    # rinomina e formatta position\n",
        "    print(\"Formattando e rinominando la colonna 'position'...\")\n",
        "    export_api_pvt = export_api_pvt.rename(columns={'position': 'weighted avg position'})\n",
        "    export_api_pvt['weighted avg position'] = export_api_pvt['weighted avg position'].astype(int)\n",
        "\n",
        "    # Apply the formatting to the CTR column \n",
        "    print(\"Applicando la formattazione al CTR...\")\n",
        "    export_api_pvt['ctr'] = export_api_pvt['ctr'].apply(format_ctr)\n",
        "\n",
        "    # ordina le colonne\n",
        "    print(\"Ordinando le colonne...\")\n",
        "    export_api_pvt = export_api_pvt.reindex(columns=['clicks', 'impressions', 'ctr', 'weighted avg position'])\n",
        "\n",
        "    # Stampa la somma totale dei clicks e delle impressions\n",
        "    print(\"Calcolando la somma totale di clicks e impressions...\")\n",
        "    total_clicks = export_api_pvt['clicks'].sum()\n",
        "    total_impressions = export_api_pvt['impressions'].sum()\n",
        "\n",
        "    print(\"Somma totale dei clicks:\", total_clicks)\n",
        "    print(\"Somma totale delle impressions:\", total_impressions)\n",
        "\n",
        "    # Mostra la tabella pivot ordinata\n",
        "    print(\"Rows: \" + str(export_api_pvt.shape[0]))\n",
        "    export_api_pvt.head(5)"
      ]
    },
    {
      "cell_type": "code",
      "execution_count": 188,
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 170
        },
        "id": "qJIsogadT_oc",
        "outputId": "1af54fb2-b7fc-4ab5-a923-4982fcaefb6d"
      },
      "outputs": [
        {
          "name": "stdout",
          "output_type": "stream",
          "text": [
            "Rows: 94498\n"
          ]
        },
        {
          "data": {
            "text/html": [
              "<div>\n",
              "<style scoped>\n",
              "    .dataframe tbody tr th:only-of-type {\n",
              "        vertical-align: middle;\n",
              "    }\n",
              "\n",
              "    .dataframe tbody tr th {\n",
              "        vertical-align: top;\n",
              "    }\n",
              "\n",
              "    .dataframe thead th {\n",
              "        text-align: right;\n",
              "    }\n",
              "</style>\n",
              "<table border=\"1\" class=\"dataframe\">\n",
              "  <thead>\n",
              "    <tr style=\"text-align: right;\">\n",
              "      <th></th>\n",
              "      <th>query</th>\n",
              "      <th>page</th>\n",
              "      <th>clicks</th>\n",
              "      <th>impressions</th>\n",
              "      <th>ctr</th>\n",
              "      <th>weighted avg position</th>\n",
              "    </tr>\n",
              "  </thead>\n",
              "  <tbody>\n",
              "    <tr>\n",
              "      <th>0</th>\n",
              "      <td>web archive</td>\n",
              "      <td>https://www.evemilano.com/web-archive/</td>\n",
              "      <td>200</td>\n",
              "      <td>62371</td>\n",
              "      <td>0.32%</td>\n",
              "      <td>5</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>1</th>\n",
              "      <td>proxy</td>\n",
              "      <td>https://www.evemilano.com/proxy-server/</td>\n",
              "      <td>5</td>\n",
              "      <td>51043</td>\n",
              "      <td>0.01%</td>\n",
              "      <td>10</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>2</th>\n",
              "      <td>webarchive</td>\n",
              "      <td>https://www.evemilano.com/web-archive/</td>\n",
              "      <td>88</td>\n",
              "      <td>43088</td>\n",
              "      <td>0.20%</td>\n",
              "      <td>5</td>\n",
              "    </tr>\n",
              "  </tbody>\n",
              "</table>\n",
              "</div>"
            ],
            "text/plain": [
              "         query                                     page  clicks  impressions  \\\n",
              "0  web archive   https://www.evemilano.com/web-archive/     200        62371   \n",
              "1        proxy  https://www.evemilano.com/proxy-server/       5        51043   \n",
              "2   webarchive   https://www.evemilano.com/web-archive/      88        43088   \n",
              "\n",
              "    ctr  weighted avg position  \n",
              "0 0.32%                      5  \n",
              "1 0.01%                     10  \n",
              "2 0.20%                      5  "
            ]
          },
          "execution_count": 188,
          "metadata": {},
          "output_type": "execute_result"
        }
      ],
      "source": [
        "# crea foglio raw\n",
        "raw_df = export_api_pvt.copy()\n",
        "raw_df = raw_df.reset_index()\n",
        "print(\"Rows: \" + str(raw_df.shape[0]))\n",
        "raw_df.head(3)"
      ]
    },
    {
      "cell_type": "code",
      "execution_count": 189,
      "metadata": {},
      "outputs": [
        {
          "name": "stdout",
          "output_type": "stream",
          "text": [
            "Preparazione dei dati\n",
            "Conversione colonna query in stringa\n",
            "Creazione colonna conta caratteri\n",
            "Rimozione stopword e applica stemming in un unico passaggio\n",
            "Conteggio stemmi e ordinamento per frequenza\n",
            "Mappatura degli stemmi alle loro posizioni nella lista ordinata\n",
            "Creazione della nuova colonna ordinando gli stemmi per frequenza\n",
            "Creazione della nuova colonna Stemma più frequente\n",
            "Eliminazione colonna Stemming\n",
            "Somma totale dei clicks: 32311\n",
            "Somma totale delle impressions: 4545130\n"
          ]
        },
        {
          "data": {
            "text/html": [
              "<div>\n",
              "<style scoped>\n",
              "    .dataframe tbody tr th:only-of-type {\n",
              "        vertical-align: middle;\n",
              "    }\n",
              "\n",
              "    .dataframe tbody tr th {\n",
              "        vertical-align: top;\n",
              "    }\n",
              "\n",
              "    .dataframe thead th {\n",
              "        text-align: right;\n",
              "    }\n",
              "</style>\n",
              "<table border=\"1\" class=\"dataframe\">\n",
              "  <thead>\n",
              "    <tr style=\"text-align: right;\">\n",
              "      <th></th>\n",
              "      <th>query</th>\n",
              "      <th>page</th>\n",
              "      <th>clicks</th>\n",
              "      <th>impressions</th>\n",
              "      <th>ctr</th>\n",
              "      <th>weighted avg position</th>\n",
              "      <th>Char</th>\n",
              "      <th>Stemming</th>\n",
              "      <th>Stems Ordered by frequency</th>\n",
              "      <th>Strongest word stem</th>\n",
              "    </tr>\n",
              "  </thead>\n",
              "  <tbody>\n",
              "    <tr>\n",
              "      <th>0</th>\n",
              "      <td>web archive</td>\n",
              "      <td>https://www.evemilano.com/web-archive/</td>\n",
              "      <td>200</td>\n",
              "      <td>62371</td>\n",
              "      <td>0.32%</td>\n",
              "      <td>5</td>\n",
              "      <td>11</td>\n",
              "      <td>web archiv</td>\n",
              "      <td>web archiv</td>\n",
              "      <td>web</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>1</th>\n",
              "      <td>proxy</td>\n",
              "      <td>https://www.evemilano.com/proxy-server/</td>\n",
              "      <td>5</td>\n",
              "      <td>51043</td>\n",
              "      <td>0.01%</td>\n",
              "      <td>10</td>\n",
              "      <td>5</td>\n",
              "      <td>proxy</td>\n",
              "      <td>proxy</td>\n",
              "      <td>proxy</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>2</th>\n",
              "      <td>webarchive</td>\n",
              "      <td>https://www.evemilano.com/web-archive/</td>\n",
              "      <td>88</td>\n",
              "      <td>43088</td>\n",
              "      <td>0.20%</td>\n",
              "      <td>5</td>\n",
              "      <td>10</td>\n",
              "      <td>webarc</td>\n",
              "      <td>webarc</td>\n",
              "      <td>webarc</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>3</th>\n",
              "      <td>indirizzo ip</td>\n",
              "      <td>https://www.evemilano.com/come-trovare-indiriz...</td>\n",
              "      <td>28</td>\n",
              "      <td>41172</td>\n",
              "      <td>0.07%</td>\n",
              "      <td>3</td>\n",
              "      <td>12</td>\n",
              "      <td>indirizz ip</td>\n",
              "      <td>ip indirizz</td>\n",
              "      <td>ip</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>4</th>\n",
              "      <td>gdpr acronimo</td>\n",
              "      <td>https://www.evemilano.com/gdpr/</td>\n",
              "      <td>26</td>\n",
              "      <td>32356</td>\n",
              "      <td>0.08%</td>\n",
              "      <td>8</td>\n",
              "      <td>13</td>\n",
              "      <td>gdpr acronim</td>\n",
              "      <td>gdpr acronim</td>\n",
              "      <td>gdpr</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>5</th>\n",
              "      <td>consulenza seo</td>\n",
              "      <td>https://www.evemilano.com/</td>\n",
              "      <td>0</td>\n",
              "      <td>27454</td>\n",
              "      <td>0.00%</td>\n",
              "      <td>30</td>\n",
              "      <td>14</td>\n",
              "      <td>consult seo</td>\n",
              "      <td>seo consult</td>\n",
              "      <td>seo</td>\n",
              "    </tr>\n",
              "  </tbody>\n",
              "</table>\n",
              "</div>"
            ],
            "text/plain": [
              "            query                                               page  clicks  \\\n",
              "0     web archive             https://www.evemilano.com/web-archive/     200   \n",
              "1           proxy            https://www.evemilano.com/proxy-server/       5   \n",
              "2      webarchive             https://www.evemilano.com/web-archive/      88   \n",
              "3    indirizzo ip  https://www.evemilano.com/come-trovare-indiriz...      28   \n",
              "4   gdpr acronimo                    https://www.evemilano.com/gdpr/      26   \n",
              "5  consulenza seo                         https://www.evemilano.com/       0   \n",
              "\n",
              "   impressions   ctr  weighted avg position  Char      Stemming  \\\n",
              "0        62371 0.32%                      5    11    web archiv   \n",
              "1        51043 0.01%                     10     5         proxy   \n",
              "2        43088 0.20%                      5    10        webarc   \n",
              "3        41172 0.07%                      3    12   indirizz ip   \n",
              "4        32356 0.08%                      8    13  gdpr acronim   \n",
              "5        27454 0.00%                     30    14   consult seo   \n",
              "\n",
              "  Stems Ordered by frequency Strongest word stem  \n",
              "0                 web archiv                 web  \n",
              "1                      proxy               proxy  \n",
              "2                     webarc              webarc  \n",
              "3                ip indirizz                  ip  \n",
              "4               gdpr acronim                gdpr  \n",
              "5                seo consult                 seo  "
            ]
          },
          "execution_count": 189,
          "metadata": {},
          "output_type": "execute_result"
        }
      ],
      "source": [
        "# PULIZIA E embedding delle query\n",
        "###################################################################################\n",
        "print(\"Preparazione dei dati\")\n",
        "print(\"Conversione colonna query in stringa\")\n",
        "raw_df['query'] = raw_df['query'].fillna('').apply(str)\n",
        "print(\"Creazione colonna conta caratteri\")\n",
        "raw_df['Char'] = raw_df['query'].apply(len)  \n",
        "\n",
        "print(\"Rimozione stopword e applica stemming in un unico passaggio\")\n",
        "raw_df['Stemming'] = raw_df['query'].apply(\n",
        "    lambda x: ' '.join([stemmer.stem(word) for word in x.split() if word.lower() not in stopwords]))\n",
        "\n",
        "print(\"Conteggio stemmi e ordinamento per frequenza\")\n",
        "stem_counts = Counter(' '.join(raw_df['Stemming']).split())\n",
        "sorted_stems = sorted(stem_counts.items(), key=itemgetter(1), reverse=True)\n",
        "\n",
        "print(\"Mappatura degli stemmi alle loro posizioni nella lista ordinata\")\n",
        "stem_position_dict = {stem: i for i, (stem, _) in enumerate(sorted_stems)}\n",
        "\n",
        "print(\"Creazione della nuova colonna ordinando gli stemmi per frequenza\")\n",
        "raw_df['Stems Ordered by frequency'] = raw_df['Stemming'].apply(\n",
        "    lambda x: ' '.join(sorted(x.split(), key=stem_position_dict.get)))\n",
        "\n",
        "print(\"Creazione della nuova colonna Stemma più frequente\")\n",
        "raw_df['Strongest word stem'] = raw_df['Stems Ordered by frequency'].str.split().str[0]\n",
        "\n",
        "print(\"Eliminazione colonna Stemming\")\n",
        "#raw_df = raw_df.drop([ 'Stemming'], axis=1)\n",
        "\n",
        "# Stampa la somma totale dei clicks e delle impressions\n",
        "total_clicks = raw_df['clicks'].sum()\n",
        "total_impressions = raw_df['impressions'].sum()\n",
        "\n",
        "print(\"Somma totale dei clicks:\", total_clicks)\n",
        "print(\"Somma totale delle impressions:\", total_impressions)\n",
        "\n",
        "raw_df.head(6)"
      ]
    },
    {
      "cell_type": "code",
      "execution_count": 190,
      "metadata": {},
      "outputs": [],
      "source": [
        "if False:\n",
        "\n",
        "    # PULIZIA E embedding delle query con spaCy \n",
        "    from collections import Counter\n",
        "    from operator import itemgetter\n",
        "\n",
        "    # Caricare il modello italiano di spaCy\n",
        "\n",
        "    print(\"Preparazione dei dati\")\n",
        "    print(\"Conversione colonna query in stringa\")\n",
        "    raw_df['query'] = raw_df['query'].fillna('').apply(str)\n",
        "    print(\"Creazione colonna conta caratteri\")\n",
        "    raw_df['Char'] = raw_df['query'].apply(len)  \n",
        "\n",
        "    print(\"Rimozione stopword e applicazione della lemmatizzazione in un unico passaggio\")\n",
        "    def process_text(text):\n",
        "        doc = nlp(text)\n",
        "        return ' '.join([token.lemma_ for token in doc if not token.is_stop and not token.is_punct])\n",
        "\n",
        "    raw_df['Lemmatized'] = raw_df['query'].apply(process_text)\n",
        "\n",
        "\n",
        "    print(\"Conteggio lemmi e ordinamento per frequenza\")\n",
        "    lemma_counts = Counter(' '.join(raw_df['Lemmatized']).split())\n",
        "    sorted_lemmas = sorted(lemma_counts.items(), key=itemgetter(1), reverse=True)\n",
        "\n",
        "    print(\"Mappatura dei lemmi alle loro posizioni nella lista ordinata\")\n",
        "    lemma_position_dict = {lemma: i for i, (lemma, _) in enumerate(sorted_lemmas)}\n",
        "\n",
        "    print(\"Creazione della nuova colonna ordinando i lemmi per frequenza\")\n",
        "    raw_df['Lemmas Ordered by frequency'] = raw_df['Lemmatized'].apply(\n",
        "        lambda x: ' '.join(sorted(x.split(), key=lemma_position_dict.get)))\n",
        "\n",
        "    print(\"Creazione della nuova colonna Lemma più frequente\")\n",
        "    raw_df['Strongest lemma'] = raw_df['Lemmas Ordered by frequency'].str.split().str[0]\n",
        "\n",
        "    print(\"Eliminazione colonna Lemmatized\")\n",
        "    #raw_df = raw_df.drop(['Lemmatized'], axis=1)\n",
        "\n",
        "    # Stampa la somma totale dei clicks e delle impressions\n",
        "    total_clicks = raw_df['clicks'].sum()\n",
        "    total_impressions = raw_df['impressions'].sum()\n",
        "\n",
        "    print(\"Somma totale dei clicks:\", total_clicks)\n",
        "    print(\"Somma totale delle impressions:\", total_impressions)\n",
        "\n",
        "    raw_df.head(6)\n"
      ]
    },
    {
      "cell_type": "code",
      "execution_count": 191,
      "metadata": {},
      "outputs": [
        {
          "name": "stdout",
          "output_type": "stream",
          "text": [
            "Conversione colonna query in stringa\n",
            "Creazione colonna conta caratteri\n",
            "Rimozione stopword e applicazione della lemmatizzazione in un unico passaggio\n",
            "Conteggio lemmi e ordinamento per frequenza\n",
            "Mappatura dei lemmi alle loro posizioni nella lista ordinata\n",
            "Creazione della nuova colonna ordinando i lemmi per frequenza\n",
            "Creazione della nuova colonna Lemma più frequente\n",
            "Eliminazione colonna Lemmatized\n",
            "Somma totale dei clicks: 32311\n",
            "Somma totale delle impressions: 4545130\n"
          ]
        },
        {
          "data": {
            "text/html": [
              "<div>\n",
              "<style scoped>\n",
              "    .dataframe tbody tr th:only-of-type {\n",
              "        vertical-align: middle;\n",
              "    }\n",
              "\n",
              "    .dataframe tbody tr th {\n",
              "        vertical-align: top;\n",
              "    }\n",
              "\n",
              "    .dataframe thead th {\n",
              "        text-align: right;\n",
              "    }\n",
              "</style>\n",
              "<table border=\"1\" class=\"dataframe\">\n",
              "  <thead>\n",
              "    <tr style=\"text-align: right;\">\n",
              "      <th></th>\n",
              "      <th>query</th>\n",
              "      <th>page</th>\n",
              "      <th>clicks</th>\n",
              "      <th>impressions</th>\n",
              "      <th>ctr</th>\n",
              "      <th>weighted avg position</th>\n",
              "      <th>Char</th>\n",
              "      <th>Stemming</th>\n",
              "      <th>Stems Ordered by frequency</th>\n",
              "      <th>Strongest word stem</th>\n",
              "      <th>Lemmatized</th>\n",
              "      <th>Lemmas Ordered by frequency</th>\n",
              "      <th>Strongest lemma</th>\n",
              "    </tr>\n",
              "  </thead>\n",
              "  <tbody>\n",
              "    <tr>\n",
              "      <th>0</th>\n",
              "      <td>web archive</td>\n",
              "      <td>https://www.evemilano.com/web-archive/</td>\n",
              "      <td>200</td>\n",
              "      <td>62371</td>\n",
              "      <td>0.32%</td>\n",
              "      <td>5</td>\n",
              "      <td>11</td>\n",
              "      <td>web archiv</td>\n",
              "      <td>web archiv</td>\n",
              "      <td>web</td>\n",
              "      <td>web archive</td>\n",
              "      <td>web archive</td>\n",
              "      <td>web</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>1</th>\n",
              "      <td>proxy</td>\n",
              "      <td>https://www.evemilano.com/proxy-server/</td>\n",
              "      <td>5</td>\n",
              "      <td>51043</td>\n",
              "      <td>0.01%</td>\n",
              "      <td>10</td>\n",
              "      <td>5</td>\n",
              "      <td>proxy</td>\n",
              "      <td>proxy</td>\n",
              "      <td>proxy</td>\n",
              "      <td>proxy</td>\n",
              "      <td>proxy</td>\n",
              "      <td>proxy</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>2</th>\n",
              "      <td>webarchive</td>\n",
              "      <td>https://www.evemilano.com/web-archive/</td>\n",
              "      <td>88</td>\n",
              "      <td>43088</td>\n",
              "      <td>0.20%</td>\n",
              "      <td>5</td>\n",
              "      <td>10</td>\n",
              "      <td>webarc</td>\n",
              "      <td>webarc</td>\n",
              "      <td>webarc</td>\n",
              "      <td>Webarchive</td>\n",
              "      <td>Webarchive</td>\n",
              "      <td>Webarchive</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>3</th>\n",
              "      <td>indirizzo ip</td>\n",
              "      <td>https://www.evemilano.com/come-trovare-indiriz...</td>\n",
              "      <td>28</td>\n",
              "      <td>41172</td>\n",
              "      <td>0.07%</td>\n",
              "      <td>3</td>\n",
              "      <td>12</td>\n",
              "      <td>indirizz ip</td>\n",
              "      <td>ip indirizz</td>\n",
              "      <td>ip</td>\n",
              "      <td>indirizzo ip</td>\n",
              "      <td>ip indirizzo</td>\n",
              "      <td>ip</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>4</th>\n",
              "      <td>gdpr acronimo</td>\n",
              "      <td>https://www.evemilano.com/gdpr/</td>\n",
              "      <td>26</td>\n",
              "      <td>32356</td>\n",
              "      <td>0.08%</td>\n",
              "      <td>8</td>\n",
              "      <td>13</td>\n",
              "      <td>gdpr acronim</td>\n",
              "      <td>gdpr acronim</td>\n",
              "      <td>gdpr</td>\n",
              "      <td>gdpr acronimo</td>\n",
              "      <td>gdpr acronimo</td>\n",
              "      <td>gdpr</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>5</th>\n",
              "      <td>consulenza seo</td>\n",
              "      <td>https://www.evemilano.com/</td>\n",
              "      <td>0</td>\n",
              "      <td>27454</td>\n",
              "      <td>0.00%</td>\n",
              "      <td>30</td>\n",
              "      <td>14</td>\n",
              "      <td>consult seo</td>\n",
              "      <td>seo consult</td>\n",
              "      <td>seo</td>\n",
              "      <td>consulenza seo</td>\n",
              "      <td>seo consulenza</td>\n",
              "      <td>seo</td>\n",
              "    </tr>\n",
              "  </tbody>\n",
              "</table>\n",
              "</div>"
            ],
            "text/plain": [
              "            query                                               page  clicks  \\\n",
              "0     web archive             https://www.evemilano.com/web-archive/     200   \n",
              "1           proxy            https://www.evemilano.com/proxy-server/       5   \n",
              "2      webarchive             https://www.evemilano.com/web-archive/      88   \n",
              "3    indirizzo ip  https://www.evemilano.com/come-trovare-indiriz...      28   \n",
              "4   gdpr acronimo                    https://www.evemilano.com/gdpr/      26   \n",
              "5  consulenza seo                         https://www.evemilano.com/       0   \n",
              "\n",
              "   impressions   ctr  weighted avg position  Char      Stemming  \\\n",
              "0        62371 0.32%                      5    11    web archiv   \n",
              "1        51043 0.01%                     10     5         proxy   \n",
              "2        43088 0.20%                      5    10        webarc   \n",
              "3        41172 0.07%                      3    12   indirizz ip   \n",
              "4        32356 0.08%                      8    13  gdpr acronim   \n",
              "5        27454 0.00%                     30    14   consult seo   \n",
              "\n",
              "  Stems Ordered by frequency Strongest word stem      Lemmatized  \\\n",
              "0                 web archiv                 web     web archive   \n",
              "1                      proxy               proxy           proxy   \n",
              "2                     webarc              webarc      Webarchive   \n",
              "3                ip indirizz                  ip    indirizzo ip   \n",
              "4               gdpr acronim                gdpr   gdpr acronimo   \n",
              "5                seo consult                 seo  consulenza seo   \n",
              "\n",
              "  Lemmas Ordered by frequency Strongest lemma  \n",
              "0                 web archive             web  \n",
              "1                       proxy           proxy  \n",
              "2                  Webarchive      Webarchive  \n",
              "3                ip indirizzo              ip  \n",
              "4               gdpr acronimo            gdpr  \n",
              "5              seo consulenza             seo  "
            ]
          },
          "execution_count": 191,
          "metadata": {},
          "output_type": "execute_result"
        }
      ],
      "source": [
        "# test 2\n",
        "# PULIZIA E embedding delle query con spaCy \n",
        "from collections import Counter\n",
        "from operator import itemgetter\n",
        "\n",
        "print(\"Conversione colonna query in stringa\")\n",
        "raw_df['query'] = raw_df['query'].fillna('').apply(str)\n",
        "print(\"Creazione colonna conta caratteri\")\n",
        "raw_df['Char'] = raw_df['query'].apply(len)  \n",
        "\n",
        "print(\"Rimozione stopword e applicazione della lemmatizzazione in un unico passaggio\")\n",
        "def process_texts(texts):\n",
        "    # Elabora i testi in batch e applica lemmatizzazione e rimozione delle stopwords\n",
        "    processed_texts = []\n",
        "    for doc in nlp.pipe(texts):\n",
        "        processed_texts.append(' '.join([token.lemma_ for token in doc if not token.is_stop and not token.is_punct]))\n",
        "    return processed_texts\n",
        "\n",
        "# Applica l'elaborazione in batch all'intera colonna 'query'\n",
        "raw_df['Lemmatized'] = process_texts(raw_df['query'])\n",
        "\n",
        "print(\"Conteggio lemmi e ordinamento per frequenza\")\n",
        "lemma_counts = Counter(' '.join(raw_df['Lemmatized']).split())\n",
        "sorted_lemmas = sorted(lemma_counts.items(), key=itemgetter(1), reverse=True)\n",
        "\n",
        "print(\"Mappatura dei lemmi alle loro posizioni nella lista ordinata\")\n",
        "lemma_position_dict = {lemma: i for i, (lemma, _) in enumerate(sorted_lemmas)}\n",
        "\n",
        "print(\"Creazione della nuova colonna ordinando i lemmi per frequenza\")\n",
        "raw_df['Lemmas Ordered by frequency'] = raw_df['Lemmatized'].apply(\n",
        "    lambda x: ' '.join(sorted(x.split(), key=lemma_position_dict.get)))\n",
        "\n",
        "print(\"Creazione della nuova colonna Lemma più frequente\")\n",
        "raw_df['Strongest lemma'] = raw_df['Lemmas Ordered by frequency'].str.split().str[0]\n",
        "\n",
        "print(\"Eliminazione colonna Lemmatized\")\n",
        "#raw_df = raw_df.drop(['Lemmatized'], axis=1)\n",
        "\n",
        "# Stampa la somma totale dei clicks e delle impressions\n",
        "total_clicks = raw_df['clicks'].sum()\n",
        "total_impressions = raw_df['impressions'].sum()\n",
        "\n",
        "print(\"Somma totale dei clicks:\", total_clicks)\n",
        "print(\"Somma totale delle impressions:\", total_impressions)\n",
        "\n",
        "raw_df.head(6)\n"
      ]
    },
    {
      "cell_type": "code",
      "execution_count": 192,
      "metadata": {},
      "outputs": [
        {
          "name": "stdout",
          "output_type": "stream",
          "text": [
            "Elaborazione dei testi con SpaCy avviata\n",
            "Estrazione sostantivi\n",
            "Somma totale dei clicks: 32311\n",
            "Somma totale delle impressions: 4545130\n",
            "classificazione Spacy terminata\n"
          ]
        },
        {
          "data": {
            "text/html": [
              "<div>\n",
              "<style scoped>\n",
              "    .dataframe tbody tr th:only-of-type {\n",
              "        vertical-align: middle;\n",
              "    }\n",
              "\n",
              "    .dataframe tbody tr th {\n",
              "        vertical-align: top;\n",
              "    }\n",
              "\n",
              "    .dataframe thead th {\n",
              "        text-align: right;\n",
              "    }\n",
              "</style>\n",
              "<table border=\"1\" class=\"dataframe\">\n",
              "  <thead>\n",
              "    <tr style=\"text-align: right;\">\n",
              "      <th></th>\n",
              "      <th>query</th>\n",
              "      <th>page</th>\n",
              "      <th>clicks</th>\n",
              "      <th>impressions</th>\n",
              "      <th>ctr</th>\n",
              "      <th>weighted avg position</th>\n",
              "      <th>Char</th>\n",
              "      <th>Stemming</th>\n",
              "      <th>Stems Ordered by frequency</th>\n",
              "      <th>Strongest word stem</th>\n",
              "      <th>Lemmatized</th>\n",
              "      <th>Lemmas Ordered by frequency</th>\n",
              "      <th>Strongest lemma</th>\n",
              "      <th>spacy_nouns</th>\n",
              "    </tr>\n",
              "  </thead>\n",
              "  <tbody>\n",
              "    <tr>\n",
              "      <th>0</th>\n",
              "      <td>web archive</td>\n",
              "      <td>https://www.evemilano.com/web-archive/</td>\n",
              "      <td>200</td>\n",
              "      <td>62371</td>\n",
              "      <td>0.32%</td>\n",
              "      <td>5</td>\n",
              "      <td>11</td>\n",
              "      <td>web archiv</td>\n",
              "      <td>web archiv</td>\n",
              "      <td>web</td>\n",
              "      <td>web archive</td>\n",
              "      <td>web archive</td>\n",
              "      <td>web</td>\n",
              "      <td>web</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>1</th>\n",
              "      <td>proxy</td>\n",
              "      <td>https://www.evemilano.com/proxy-server/</td>\n",
              "      <td>5</td>\n",
              "      <td>51043</td>\n",
              "      <td>0.01%</td>\n",
              "      <td>10</td>\n",
              "      <td>5</td>\n",
              "      <td>proxy</td>\n",
              "      <td>proxy</td>\n",
              "      <td>proxy</td>\n",
              "      <td>proxy</td>\n",
              "      <td>proxy</td>\n",
              "      <td>proxy</td>\n",
              "      <td>proxy</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>2</th>\n",
              "      <td>webarchive</td>\n",
              "      <td>https://www.evemilano.com/web-archive/</td>\n",
              "      <td>88</td>\n",
              "      <td>43088</td>\n",
              "      <td>0.20%</td>\n",
              "      <td>5</td>\n",
              "      <td>10</td>\n",
              "      <td>webarc</td>\n",
              "      <td>webarc</td>\n",
              "      <td>webarc</td>\n",
              "      <td>Webarchive</td>\n",
              "      <td>Webarchive</td>\n",
              "      <td>Webarchive</td>\n",
              "      <td>webarchive</td>\n",
              "    </tr>\n",
              "  </tbody>\n",
              "</table>\n",
              "</div>"
            ],
            "text/plain": [
              "         query                                     page  clicks  impressions  \\\n",
              "0  web archive   https://www.evemilano.com/web-archive/     200        62371   \n",
              "1        proxy  https://www.evemilano.com/proxy-server/       5        51043   \n",
              "2   webarchive   https://www.evemilano.com/web-archive/      88        43088   \n",
              "\n",
              "    ctr  weighted avg position  Char    Stemming Stems Ordered by frequency  \\\n",
              "0 0.32%                      5    11  web archiv                 web archiv   \n",
              "1 0.01%                     10     5       proxy                      proxy   \n",
              "2 0.20%                      5    10      webarc                     webarc   \n",
              "\n",
              "  Strongest word stem   Lemmatized Lemmas Ordered by frequency  \\\n",
              "0                 web  web archive                 web archive   \n",
              "1               proxy        proxy                       proxy   \n",
              "2              webarc   Webarchive                  Webarchive   \n",
              "\n",
              "  Strongest lemma spacy_nouns  \n",
              "0             web         web  \n",
              "1           proxy       proxy  \n",
              "2      Webarchive  webarchive  "
            ]
          },
          "execution_count": 192,
          "metadata": {},
          "output_type": "execute_result"
        }
      ],
      "source": [
        "# classificazione spacy versione ottimizzata con pipe\n",
        "print('Elaborazione dei testi con SpaCy avviata')\n",
        "# Elaborazione dei testi in batch utilizzando il metodo pipe di Spacy, che è più efficiente rispetto all'elaborazione dei testi uno alla volta\n",
        "# batch_size può essere regolato in base alla quantità di memoria disponibile\n",
        "spacy_analysis = list(nlp.pipe(raw_df['query'], batch_size=1000))\n",
        "\n",
        "# Con questa modifica, la colonna spacy_nouns conterrà tutti i sostantivi presenti nella query, separati da uno spazio. \n",
        "# Se non ci sono sostantivi in una particolare query, il valore sarà 'other'.\n",
        "# Estrai tutti i sostantivi\n",
        "def extract_nouns(doc):\n",
        "    return ' '.join([token.text for token in doc if token.pos_ == 'NOUN'])\n",
        "# Applica la funzione per estrarre sostantivi a ogni documento\n",
        "print('Estrazione sostantivi')\n",
        "raw_df['spacy_nouns'] = [extract_nouns(doc) if any(token.pos_ == 'NOUN' for token in doc) else 'other' for doc in spacy_analysis]\n",
        "\n",
        "# Stampa la somma totale dei clicks e delle impressions\n",
        "total_clicks = raw_df['clicks'].sum()\n",
        "total_impressions = raw_df['impressions'].sum()\n",
        "print(\"Somma totale dei clicks:\", total_clicks)\n",
        "print(\"Somma totale delle impressions:\", total_impressions)\n",
        "print('classificazione Spacy terminata')\n",
        "raw_df.head(3)"
      ]
    },
    {
      "cell_type": "code",
      "execution_count": 193,
      "metadata": {},
      "outputs": [
        {
          "name": "stdout",
          "output_type": "stream",
          "text": [
            "Creazione tabella pivot con trending topic\n",
            "Calcolo del CTR direttamente sul pivot table\n",
            "Somma totale dei clicks: 29585\n",
            "Somma totale delle impressions: 4207515\n",
            "Rows: 2039\n"
          ]
        },
        {
          "data": {
            "text/html": [
              "<div>\n",
              "<style scoped>\n",
              "    .dataframe tbody tr th:only-of-type {\n",
              "        vertical-align: middle;\n",
              "    }\n",
              "\n",
              "    .dataframe tbody tr th {\n",
              "        vertical-align: top;\n",
              "    }\n",
              "\n",
              "    .dataframe thead th {\n",
              "        text-align: right;\n",
              "    }\n",
              "</style>\n",
              "<table border=\"1\" class=\"dataframe\">\n",
              "  <thead>\n",
              "    <tr style=\"text-align: right;\">\n",
              "      <th></th>\n",
              "      <th>clicks</th>\n",
              "      <th>impressions</th>\n",
              "      <th>ctr</th>\n",
              "      <th>weighted avg position</th>\n",
              "      <th>query</th>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>Trending Topics</th>\n",
              "      <th></th>\n",
              "      <th></th>\n",
              "      <th></th>\n",
              "      <th></th>\n",
              "      <th></th>\n",
              "    </tr>\n",
              "  </thead>\n",
              "  <tbody>\n",
              "    <tr>\n",
              "      <th>other</th>\n",
              "      <td>8121</td>\n",
              "      <td>712794</td>\n",
              "      <td>1.14%</td>\n",
              "      <td>30</td>\n",
              "      <td>20207</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>agenzia</th>\n",
              "      <td>19</td>\n",
              "      <td>121319</td>\n",
              "      <td>0.02%</td>\n",
              "      <td>54</td>\n",
              "      <td>542</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>consulente</th>\n",
              "      <td>14</td>\n",
              "      <td>91610</td>\n",
              "      <td>0.02%</td>\n",
              "      <td>46</td>\n",
              "      <td>343</td>\n",
              "    </tr>\n",
              "  </tbody>\n",
              "</table>\n",
              "</div>"
            ],
            "text/plain": [
              "                 clicks  impressions   ctr  weighted avg position  query\n",
              "Trending Topics                                                         \n",
              "other              8121       712794 1.14%                     30  20207\n",
              "agenzia              19       121319 0.02%                     54    542\n",
              "consulente           14        91610 0.02%                     46    343"
            ]
          },
          "execution_count": 193,
          "metadata": {},
          "output_type": "execute_result"
        }
      ],
      "source": [
        "#pvt spacy - trending topic table\n",
        "print('Creazione tabella pivot con trending topic')\n",
        "\n",
        "# Crea una tabella pivot con multi-livello di indici\n",
        "pvt_spacy = raw_df.pivot_table(\n",
        "    index='spacy_nouns', \n",
        "    values=['clicks', 'impressions', 'weighted avg position', 'query'], \n",
        "    aggfunc={\n",
        "        'clicks': 'sum',\n",
        "        'impressions': 'sum',\n",
        "        'weighted avg position': lambda x: weighted_mean(x, raw_df.loc[x.index, 'impressions']),\n",
        "        'query': 'count'  # Conteggio delle query\n",
        "    }\n",
        ")\n",
        "print('Calcolo del CTR direttamente sul pivot table')\n",
        "# Calcolo del CTR direttamente sul pivot table\n",
        "pvt_spacy['ctr'] = (pvt_spacy['clicks'] / pvt_spacy['impressions']) * 100\n",
        "\n",
        "\n",
        "# Ordina la tabella pivot in base alla somma di impressions\n",
        "pvt_spacy.sort_values(by='impressions', axis=0, ascending=False, inplace=True)\n",
        "pvt_spacy = pvt_spacy.reindex(columns=['clicks', 'impressions', 'ctr', 'weighted avg position','query'])\n",
        "\n",
        "# Applica la formattazione alla colonna CTR\n",
        "pvt_spacy['ctr'] = pvt_spacy['ctr'].apply(format_ctr)\n",
        "# Converte i valori di 'weighted avg position' da decimali a interi\n",
        "pvt_spacy['weighted avg position'] = pvt_spacy['weighted avg position'].astype(int)\n",
        "\n",
        "# Rinomina la colonna 'spacy_noun' in 'Trending Topics'\n",
        "pvt_spacy.index = pvt_spacy.index.rename(\"Trending Topics\")\n",
        "\n",
        "# cancella i topic con meno di 2 query\n",
        "pvt_spacy = pvt_spacy[pvt_spacy['query'] >= 2]\n",
        "# cancella i topic con meno di 100 impressions\n",
        "pvt_spacy = pvt_spacy[pvt_spacy['impressions'] >= 100]\n",
        "\n",
        "# Stampa la somma totale dei clicks e delle impressions\n",
        "total_clicks = pvt_spacy['clicks'].sum()\n",
        "total_impressions = pvt_spacy['impressions'].sum()\n",
        "\n",
        "print(\"Somma totale dei clicks:\", total_clicks)\n",
        "print(\"Somma totale delle impressions:\", total_impressions)\n",
        "\n",
        "\n",
        "# Mostra la tabella pivot ordinata\n",
        "print(\"Rows: \" + str(pvt_spacy.shape[0]))\n",
        "pvt_spacy.head(3)"
      ]
    },
    {
      "cell_type": "code",
      "execution_count": 194,
      "metadata": {},
      "outputs": [
        {
          "name": "stdout",
          "output_type": "stream",
          "text": [
            "Creazione tabella pivot con trending topic\n",
            "Calcolo del CTR direttamente sul pivot table\n",
            "Somma totale dei clicks: 31645\n",
            "Somma totale delle impressions: 4425730\n",
            "Rows: 582\n"
          ]
        },
        {
          "data": {
            "text/html": [
              "<div>\n",
              "<style scoped>\n",
              "    .dataframe tbody tr th:only-of-type {\n",
              "        vertical-align: middle;\n",
              "    }\n",
              "\n",
              "    .dataframe tbody tr th {\n",
              "        vertical-align: top;\n",
              "    }\n",
              "\n",
              "    .dataframe thead th {\n",
              "        text-align: right;\n",
              "    }\n",
              "</style>\n",
              "<table border=\"1\" class=\"dataframe\">\n",
              "  <thead>\n",
              "    <tr style=\"text-align: right;\">\n",
              "      <th></th>\n",
              "      <th>clicks</th>\n",
              "      <th>impressions</th>\n",
              "      <th>ctr</th>\n",
              "      <th>weighted avg position</th>\n",
              "      <th>query</th>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>Trending Lemmas</th>\n",
              "      <th></th>\n",
              "      <th></th>\n",
              "      <th></th>\n",
              "      <th></th>\n",
              "      <th></th>\n",
              "    </tr>\n",
              "  </thead>\n",
              "  <tbody>\n",
              "    <tr>\n",
              "      <th>seo</th>\n",
              "      <td>449</td>\n",
              "      <td>756257</td>\n",
              "      <td>0.06%</td>\n",
              "      <td>46</td>\n",
              "      <td>7281</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>google</th>\n",
              "      <td>1004</td>\n",
              "      <td>565177</td>\n",
              "      <td>0.18%</td>\n",
              "      <td>40</td>\n",
              "      <td>11981</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>web</th>\n",
              "      <td>607</td>\n",
              "      <td>333674</td>\n",
              "      <td>0.18%</td>\n",
              "      <td>37</td>\n",
              "      <td>3322</td>\n",
              "    </tr>\n",
              "  </tbody>\n",
              "</table>\n",
              "</div>"
            ],
            "text/plain": [
              "                 clicks  impressions   ctr  weighted avg position  query\n",
              "Trending Lemmas                                                         \n",
              "seo                 449       756257 0.06%                     46   7281\n",
              "google             1004       565177 0.18%                     40  11981\n",
              "web                 607       333674 0.18%                     37   3322"
            ]
          },
          "execution_count": 194,
          "metadata": {},
          "output_type": "execute_result"
        }
      ],
      "source": [
        "#pvt LEMMI - Lemmas topic table con spaCy\n",
        "print('Creazione tabella pivot con trending topic')\n",
        "\n",
        "# Crea una tabella pivot con multi-livello di indici\n",
        "pvt_lemmy = raw_df.pivot_table(\n",
        "    index='Strongest lemma', \n",
        "    values=['clicks', 'impressions', 'weighted avg position', 'query'], \n",
        "    aggfunc={\n",
        "        'clicks': 'sum',\n",
        "        'impressions': 'sum',\n",
        "        'weighted avg position': lambda x: weighted_mean(x, raw_df.loc[x.index, 'impressions']),\n",
        "        'query': 'count'  # Conteggio delle query\n",
        "    }\n",
        ")\n",
        "print('Calcolo del CTR direttamente sul pivot table')\n",
        "# Calcolo del CTR direttamente sul pivot table\n",
        "pvt_lemmy['ctr'] = (pvt_lemmy['clicks'] / pvt_lemmy['impressions']) * 100\n",
        "\n",
        "\n",
        "# Ordina la tabella pivot in base alla somma di impressions\n",
        "pvt_lemmy.sort_values(by='impressions', axis=0, ascending=False, inplace=True)\n",
        "pvt_lemmy = pvt_lemmy.reindex(columns=['clicks', 'impressions', 'ctr', 'weighted avg position','query'])\n",
        "\n",
        "# Applica la formattazione alla colonna CTR\n",
        "pvt_lemmy['ctr'] = pvt_lemmy['ctr'].apply(format_ctr)\n",
        "# Converte i valori di 'weighted avg position' da decimali a interi\n",
        "pvt_lemmy['weighted avg position'] = pvt_lemmy['weighted avg position'].astype(int)\n",
        "\n",
        "# Rinomina la colonna 'spacy_noun' in 'Trending Topics'\n",
        "pvt_lemmy.index = pvt_lemmy.index.rename(\"Trending Lemmas\")\n",
        "\n",
        "# cancella i topic con meno di 2 query\n",
        "pvt_lemmy = pvt_lemmy[pvt_lemmy['query'] >= 2]\n",
        "# cancella i topic con meno di 100 impressions\n",
        "pvt_lemmy = pvt_lemmy[pvt_lemmy['impressions'] >= 100]\n",
        "\n",
        "# Stampa la somma totale dei clicks e delle impressions\n",
        "total_clicks = pvt_lemmy['clicks'].sum()\n",
        "total_impressions = pvt_lemmy['impressions'].sum()\n",
        "\n",
        "print(\"Somma totale dei clicks:\", total_clicks)\n",
        "print(\"Somma totale delle impressions:\", total_impressions)\n",
        "\n",
        "\n",
        "# Mostra la tabella pivot ordinata\n",
        "print(\"Rows: \" + str(pvt_lemmy.shape[0]))\n",
        "pvt_lemmy.head(3)"
      ]
    },
    {
      "cell_type": "code",
      "execution_count": 195,
      "metadata": {},
      "outputs": [
        {
          "name": "stdout",
          "output_type": "stream",
          "text": [
            "Creazione tabella pivot con trending stemming\n",
            "Somma totale dei clicks: 31203\n",
            "Somma totale delle impressions: 4461002\n",
            "Rows: 531\n"
          ]
        },
        {
          "data": {
            "text/html": [
              "<div>\n",
              "<style scoped>\n",
              "    .dataframe tbody tr th:only-of-type {\n",
              "        vertical-align: middle;\n",
              "    }\n",
              "\n",
              "    .dataframe tbody tr th {\n",
              "        vertical-align: top;\n",
              "    }\n",
              "\n",
              "    .dataframe thead th {\n",
              "        text-align: right;\n",
              "    }\n",
              "</style>\n",
              "<table border=\"1\" class=\"dataframe\">\n",
              "  <thead>\n",
              "    <tr style=\"text-align: right;\">\n",
              "      <th></th>\n",
              "      <th>clicks</th>\n",
              "      <th>impressions</th>\n",
              "      <th>ctr</th>\n",
              "      <th>weighted avg position</th>\n",
              "      <th>query</th>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>Trending Stemming</th>\n",
              "      <th></th>\n",
              "      <th></th>\n",
              "      <th></th>\n",
              "      <th></th>\n",
              "      <th></th>\n",
              "    </tr>\n",
              "  </thead>\n",
              "  <tbody>\n",
              "    <tr>\n",
              "      <th>seo</th>\n",
              "      <td>452</td>\n",
              "      <td>756836</td>\n",
              "      <td>0.06%</td>\n",
              "      <td>46</td>\n",
              "      <td>7217</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>googl</th>\n",
              "      <td>1155</td>\n",
              "      <td>638149</td>\n",
              "      <td>0.18%</td>\n",
              "      <td>40</td>\n",
              "      <td>13589</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>web</th>\n",
              "      <td>342</td>\n",
              "      <td>225195</td>\n",
              "      <td>0.15%</td>\n",
              "      <td>32</td>\n",
              "      <td>2128</td>\n",
              "    </tr>\n",
              "  </tbody>\n",
              "</table>\n",
              "</div>"
            ],
            "text/plain": [
              "                   clicks  impressions   ctr  weighted avg position  query\n",
              "Trending Stemming                                                         \n",
              "seo                   452       756836 0.06%                     46   7217\n",
              "googl                1155       638149 0.18%                     40  13589\n",
              "web                   342       225195 0.15%                     32   2128"
            ]
          },
          "execution_count": 195,
          "metadata": {},
          "output_type": "execute_result"
        }
      ],
      "source": [
        "#pvt spacy trending stemming\n",
        "print('Creazione tabella pivot con trending stemming')\n",
        "\n",
        "# Crea una tabella pivot con multi-livello di indici\n",
        "pvt_stem = raw_df.pivot_table(\n",
        "    index='Strongest word stem', \n",
        "    values=['clicks', 'impressions', 'weighted avg position', 'query'], \n",
        "    aggfunc={\n",
        "        'clicks': 'sum',\n",
        "        'impressions': 'sum',\n",
        "        'weighted avg position': lambda x: weighted_mean(x, raw_df.loc[x.index, 'impressions']),\n",
        "        'query': 'count'  # Conteggio delle query\n",
        "    }\n",
        ")\n",
        "\n",
        "# Calcolo del CTR direttamente sul pivot table\n",
        "pvt_stem['ctr'] = (pvt_stem['clicks'] / pvt_stem['impressions']) * 100\n",
        "\n",
        "\n",
        "\n",
        "# Ordina la tabella pivot in base alla somma di impressions\n",
        "pvt_stem.sort_values(by='impressions', axis=0, ascending=False, inplace=True)\n",
        "pvt_stem = pvt_stem.reindex(columns=['clicks', 'impressions', 'ctr', 'weighted avg position', 'query'])\n",
        "\n",
        "# Converte i valori di 'weighted avg position' da decimali a interi\n",
        "pvt_stem['weighted avg position'] = pvt_stem['weighted avg position'].astype(int)\n",
        "# Applica la formattazione alla colonna CTR\n",
        "pvt_stem['ctr'] = pvt_stem['ctr'].apply(format_ctr)\n",
        "\n",
        "\n",
        "# Rinomina la colonna 'Strongest word stem' in 'Trending Stemming'\n",
        "pvt_stem.index = pvt_stem.index.rename(\"Trending Stemming\")\n",
        "\n",
        "# Filtra gli stemmi con meno di 2 query e meno di 100 impressions\n",
        "pvt_stem = pvt_stem[pvt_stem['query'] >= 2]\n",
        "pvt_stem = pvt_stem[pvt_stem['impressions'] >= 100]\n",
        "\n",
        "# Stampa la somma totale dei clicks e delle impressions\n",
        "total_clicks = pvt_stem['clicks'].sum()\n",
        "total_impressions = pvt_stem['impressions'].sum()\n",
        "\n",
        "print(\"Somma totale dei clicks:\", total_clicks)\n",
        "print(\"Somma totale delle impressions:\", total_impressions)\n",
        "\n",
        "# Mostra la tabella pivot ordinata\n",
        "print(\"Rows: \" + str(pvt_stem.shape[0]))\n",
        "pvt_stem.head(3)"
      ]
    },
    {
      "cell_type": "code",
      "execution_count": 196,
      "metadata": {},
      "outputs": [],
      "source": [
        "# calcolo brand per rimozione query brand e calcolo CTR medio del sito web"
      ]
    },
    {
      "cell_type": "code",
      "execution_count": 197,
      "metadata": {},
      "outputs": [
        {
          "name": "stdout",
          "output_type": "stream",
          "text": [
            "Rows: 2\n"
          ]
        },
        {
          "data": {
            "text/html": [
              "<div>\n",
              "<style scoped>\n",
              "    .dataframe tbody tr th:only-of-type {\n",
              "        vertical-align: middle;\n",
              "    }\n",
              "\n",
              "    .dataframe tbody tr th {\n",
              "        vertical-align: top;\n",
              "    }\n",
              "\n",
              "    .dataframe thead th {\n",
              "        text-align: right;\n",
              "    }\n",
              "</style>\n",
              "<table border=\"1\" class=\"dataframe\">\n",
              "  <thead>\n",
              "    <tr style=\"text-align: right;\">\n",
              "      <th></th>\n",
              "      <th>counts</th>\n",
              "      <th>Count %</th>\n",
              "      <th>Total Clicks</th>\n",
              "      <th>Clicks %</th>\n",
              "      <th>Total Impressions</th>\n",
              "      <th>Imp %</th>\n",
              "      <th>ctr</th>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>cats</th>\n",
              "      <th></th>\n",
              "      <th></th>\n",
              "      <th></th>\n",
              "      <th></th>\n",
              "      <th></th>\n",
              "      <th></th>\n",
              "      <th></th>\n",
              "    </tr>\n",
              "  </thead>\n",
              "  <tbody>\n",
              "    <tr>\n",
              "      <th>Non-branded</th>\n",
              "      <td>75435</td>\n",
              "      <td>99.99%</td>\n",
              "      <td>31615</td>\n",
              "      <td>98.43%</td>\n",
              "      <td>4172709</td>\n",
              "      <td>99.92%</td>\n",
              "      <td>0.76%</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>Brand</th>\n",
              "      <td>7</td>\n",
              "      <td>0.01%</td>\n",
              "      <td>504</td>\n",
              "      <td>1.57%</td>\n",
              "      <td>3247</td>\n",
              "      <td>0.08%</td>\n",
              "      <td>15.52%</td>\n",
              "    </tr>\n",
              "  </tbody>\n",
              "</table>\n",
              "</div>"
            ],
            "text/plain": [
              "             counts  Count %  Total Clicks  Clicks %  Total Impressions  \\\n",
              "cats                                                                      \n",
              "Non-branded   75435   99.99%         31615    98.43%            4172709   \n",
              "Brand             7    0.01%           504     1.57%               3247   \n",
              "\n",
              "             Imp %    ctr  \n",
              "cats                       \n",
              "Non-branded 99.92%  0.76%  \n",
              "Brand        0.08% 15.52%  "
            ]
          },
          "execution_count": 197,
          "metadata": {},
          "output_type": "execute_result"
        }
      ],
      "source": [
        "# inizio analisi BRAND\n",
        "# Rimuove i duplicati basati sulla colonna 'query'\n",
        "raw_df_unique = raw_df.copy().drop_duplicates(subset=['query'])\n",
        "\n",
        "# Aggiunge una colonna 'Brand/Non-branded' che indica se la query contiene il termine del brand\n",
        "raw_df_unique['Brand/Non-branded'] = np.where(\n",
        "   raw_df_unique['query'].str.contains(query_brand, regex=True, case=False), 'Brand', 'Non-branded'\n",
        ")\n",
        "# Aggiunge una colonna 'Brand/Non-branded' che indica se la query contiene il termine del brand\n",
        "# anche alla lista con i duplicati che servirà per la cannibalizzazione\n",
        "raw_df['Brand/Non-branded'] = np.where(\n",
        "   raw_df['query'].str.contains(query_brand, regex=True, case=False), 'Brand', 'Non-branded'\n",
        ")\n",
        "# Calcola il conteggio dei valori nella colonna 'Brand/Non-branded'\n",
        "brand_count_df = raw_df_unique['Brand/Non-branded'].value_counts().rename_axis('cats').to_frame('counts')\n",
        "# Calcola la percentuale del conteggio rispetto al totale\n",
        "brand_count_df['Count %'] = brand_count_df['counts']/sum(brand_count_df['counts'])\n",
        "pd.options.display.float_format = '{:.2%}'.format\n",
        "# Calcola la somma dei click e delle impressioni per ciascuna categoria\n",
        "clicks_by_category = raw_df_unique.groupby('Brand/Non-branded')['clicks'].sum()\n",
        "# Calcola la somma delle impressioni per ciascuna categoria\n",
        "impressions_by_category = raw_df_unique.groupby('Brand/Non-branded')['impressions'].sum()\n",
        "# Aggiungi le colonne 'Total Clicks' e 'Total Impressions' al dataframe brand_count_df\n",
        "brand_count_df['Total Clicks'] = clicks_by_category\n",
        "brand_count_df['Clicks %'] = brand_count_df['Total Clicks']/sum(brand_count_df['Total Clicks'])\n",
        "brand_count_df['Total Impressions'] = impressions_by_category\n",
        "brand_count_df['Imp %'] = brand_count_df['Total Impressions']/sum(brand_count_df['Total Impressions'])\n",
        "\n",
        "\n",
        "# Calcola il CTR e aggiungi come colonna al dataframe\n",
        "#brand_count_df['ctr'] = (brand_count_df['Total Clicks'] / brand_count_df['Total Impressions']) * 100\n",
        "brand_count_df['ctr'] = (brand_count_df['Total Clicks'] / brand_count_df['Total Impressions'])\n",
        "\n",
        "print(\"Rows: \" + str(brand_count_df.shape[0]))\n",
        "brand_count_df.head(5)"
      ]
    },
    {
      "cell_type": "code",
      "execution_count": 198,
      "metadata": {},
      "outputs": [],
      "source": [
        "# Scegli uno degli stili stampati e sostituiscilo in plt.style.use()\n",
        "# #print(plt.style.available)\n"
      ]
    },
    {
      "cell_type": "code",
      "execution_count": 199,
      "metadata": {},
      "outputs": [
        {
          "data": {
            "image/png": 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",
            "text/plain": [
              "<Figure size 1000x600 with 2 Axes>"
            ]
          },
          "metadata": {},
          "output_type": "display_data"
        }
      ],
      "source": [
        "fig, ax1 = plt.subplots(figsize=(10, 6))  # Aumenta la dimensione per una migliore leggibilità\n",
        "\n",
        "# Imposta lo stile del grafico\n",
        "#plt.style.use('seaborn-v0_8-poster')\n",
        "\n",
        "# Crea le posizioni delle barre\n",
        "bar_width = 0.35\n",
        "x_pos_counts = np.arange(len(brand_count_df.index))\n",
        "x_pos_clicks = x_pos_counts + bar_width\n",
        "\n",
        "# Crea l'asse Y1 per il numero di query (counts)\n",
        "ax1.bar(x_pos_counts, brand_count_df['counts'], label='Counts', alpha=0.8, color='#1f77b4', width=bar_width)\n",
        "ax1.set_xlabel('Category', fontsize=12)\n",
        "ax1.set_ylabel('Counts', fontsize=12, color='#1f77b4')\n",
        "ax1.tick_params(axis='y', labelcolor='#1f77b4')\n",
        "ax1.set_xticks(x_pos_counts)\n",
        "ax1.set_xticklabels(brand_count_df.index, fontsize=10)\n",
        "\n",
        "# Crea un secondo asse Y per i click\n",
        "ax2 = ax1.twinx()\n",
        "ax2.bar(x_pos_clicks, brand_count_df['Total Clicks'], label='Total Clicks', alpha=0.8, color='#ff7f0e', width=bar_width)\n",
        "ax2.set_ylabel('Clicks', fontsize=12, color='#ff7f0e')\n",
        "ax2.tick_params(axis='y', labelcolor='#ff7f0e')\n",
        "\n",
        "# Aggiungi le etichette dei valori\n",
        "for i, val in enumerate(brand_count_df['counts']):\n",
        "    ax1.annotate(f'{val:.0f}', (x_pos_counts[i], val), ha='center', va='bottom', fontsize=10)\n",
        "\n",
        "for i, val in enumerate(brand_count_df['Total Clicks']):\n",
        "    ax2.annotate(f'{val:.0f}', (x_pos_clicks[i], val), ha='center', va='bottom', fontsize=10)\n",
        "\n",
        "# Aggiungi la legenda\n",
        "fig.legend(loc='upper center', bbox_to_anchor=(0.5, 1.05), ncol=2, fontsize=10)\n",
        "\n",
        "# Titolo del grafico\n",
        "plt.title('Comparison of Clicks and Counts for Brand and Non-branded Queries', fontsize=14)\n",
        "\n",
        "# Salva il grafico con risoluzione più alta\n",
        "plt.savefig(f'{new_output_dir}/{file_name}_clicks_and_count_brand_not_branded.png', bbox_inches='tight', dpi=300)\n",
        "\n",
        "plt.show()\n",
        "plt.close(fig)\n"
      ]
    },
    {
      "cell_type": "code",
      "execution_count": 200,
      "metadata": {},
      "outputs": [
        {
          "name": "stdout",
          "output_type": "stream",
          "text": [
            "La categoria 'Brand' ha 7 righe.\n"
          ]
        },
        {
          "data": {
            "image/png": 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",
            "text/plain": [
              "<Figure size 1200x600 with 2 Axes>"
            ]
          },
          "metadata": {},
          "output_type": "display_data"
        }
      ],
      "source": [
        "# brand pie\n",
        "###############################################################\n",
        "\n",
        "# Metodo 2: Conteggio delle righe per la categoria \"Brand\"\n",
        "brand_row_count = brand_count_df.loc[(brand_count_df.index == 'Brand') & (brand_count_df['counts'] >= 1), 'counts'].sum()\n",
        "\n",
        "if brand_row_count == 0:\n",
        "    print(\"La categoria 'Brand' ha zero righe.\")\n",
        "else:\n",
        "    print(f\"La categoria 'Brand' ha {brand_row_count} righe.\")\n",
        "    def create_pie_chart(data, labels, title, ax):\n",
        "        explode = (0.1, 0)  # esplode la prima fetta\n",
        "        #colors = ['orange', 'purple']  # usa colori personalizzati\n",
        "        colors = ['#ff7f0e','#1f77b4']  # usa colori personalizzati\n",
        "        ax.pie(data, explode=explode, labels=labels, autopct='%1.2f%%', shadow=True, colors=colors, startangle=140)\n",
        "        ax.axis('equal')\n",
        "        ax.set_title(title)\n",
        "\n",
        "    fig, (axa, axb) = plt.subplots(1, 2, figsize=(12, 6))\n",
        "\n",
        "    create_pie_chart(brand_count_df['counts'], brand_count_df.index, 'Counts for Brand and Non-Brand Queries', axa)\n",
        "    create_pie_chart(brand_count_df['Total Clicks'], brand_count_df.index, 'Clicks for Brand and Non-Brand Queries', axb)\n",
        "\n",
        "    # Aggiungi la firma\n",
        "    axa.text(0.05, 0.05, 'by evemilano.com', transform=axa.transAxes, fontsize=10,\n",
        "            verticalalignment='bottom', horizontalalignment='right', color='grey', alpha=0.5)\n",
        "\n",
        "    # Mostra i grafici\n",
        "    plt.tight_layout()\n",
        "    #plt.savefig(f'{output_dir}/GSC_EXT_{property_name}_{now_str}_pie_graph.png')\n",
        "    plt.savefig(f'{new_output_dir}/{file_name}_pie_graph.png')\n",
        "    plt.show()\n",
        "    plt.close(fig)\n",
        "\n"
      ]
    },
    {
      "cell_type": "code",
      "execution_count": 201,
      "metadata": {},
      "outputs": [
        {
          "name": "stdout",
          "output_type": "stream",
          "text": [
            "Somma totale dei clicks: 567\n",
            "Somma totale delle impressions: 25157\n",
            "Rows: 258\n"
          ]
        }
      ],
      "source": [
        "# creazione database sole query BRAND e NO BRAND\n",
        "#####################################\n",
        "if brand_row_count > 0:\n",
        "    #df_nobrand = raw_df.loc[raw_df['Brand/Non-branded'] == 'Non-branded']\n",
        "    df_nobrand = raw_df.loc[raw_df['Brand/Non-branded'] == 'Non-branded'].copy()\n",
        "    # Compila i valori vuoti\n",
        "    df_nobrand.fillna(0, inplace = True)\n",
        "    # Arrotonda i valori di posizione\n",
        "    #df_nobrand['position'] = df_nobrand['position'].round().astype(int)\n",
        "    df_nobrand.loc[:, 'weighted avg position'] = df_nobrand['weighted avg position'].round().astype(int)\n",
        "    # Crea un dataframe per le query brand\n",
        "    df_brand = raw_df.loc[raw_df['Brand/Non-branded'] == 'Brand']\n",
        "\n",
        "\n",
        "    # Stampa la somma totale dei clicks e delle impressions\n",
        "    total_clicks = df_brand['clicks'].sum()\n",
        "    total_impressions = df_brand['impressions'].sum()\n",
        "\n",
        "    print(\"Somma totale dei clicks:\", total_clicks)\n",
        "    print(\"Somma totale delle impressions:\", total_impressions)\n",
        "    print(\"Rows: \" + str(df_brand.shape[0]))\n",
        "    df_brand.head(12)\n",
        "else: \n",
        "    print(\"La categoria 'Brand' ha zero righe.\")\n",
        "    df_nobrand = raw_df.copy()\n",
        "    df_brand = pd.DataFrame()\n"
      ]
    },
    {
      "cell_type": "code",
      "execution_count": 202,
      "metadata": {},
      "outputs": [],
      "source": [
        "# vecchio metodo per il database delle query brand\n",
        "# somma tutte le impression di query * URL (conta impressione e click anche dei sitelink)\n",
        "# script bloccato da if False:\n",
        "if False:\n",
        "    # crea pivot brand (!)\n",
        "    # Crea una copia del dataframe df_brand\n",
        "    df_brand_pivot = df_brand.copy()\n",
        "    # Elimina la colonna \"page\"\n",
        "    df_brand_pivot.drop(columns=['page'], inplace=True)\n",
        "    # Crea la pivot table\n",
        "\n",
        "\n",
        "    # Creazione della tabella pivot\n",
        "    pivot_b = df_brand_pivot.pivot_table(\n",
        "        index='query', \n",
        "        values=['clicks', 'impressions', 'weighted avg position'], \n",
        "        aggfunc={\n",
        "            'clicks': 'sum',\n",
        "            'impressions': 'sum',\n",
        "            'weighted avg position': lambda x: weighted_mean(x, df_brand_pivot.loc[x.index, 'impressions']),\n",
        "        }\n",
        "    )\n",
        "\n",
        "    # Calcolo del CTR\n",
        "    pivot_b['ctr'] = (pivot_b['clicks'] / pivot_b['impressions']) \n",
        "\n",
        "    # Riordina le colonne\n",
        "    sorted_pivot = pivot_b.reindex(columns=['clicks', 'impressions', 'ctr', 'weighted avg position'])\n",
        "    # Ordina la pivot table per 'impressions' in ordine decrescente\n",
        "    sorted_pivot = sorted_pivot.sort_values(by='impressions', ascending=False)\n",
        "    # Arrotonda i valori nella colonna 'position' e li converte in interi\n",
        "    sorted_pivot['weighted avg position'] = sorted_pivot['weighted avg position'].round().astype(int)\n",
        "    # Mostra le prime righe della pivot table\n",
        "    print(\"Rows: \" + str(sorted_pivot.shape[0]))\n",
        "\n",
        "    sorted_pivot.head(5)\n"
      ]
    },
    {
      "cell_type": "code",
      "execution_count": 203,
      "metadata": {},
      "outputs": [
        {
          "data": {
            "text/html": [
              "<div>\n",
              "<style scoped>\n",
              "    .dataframe tbody tr th:only-of-type {\n",
              "        vertical-align: middle;\n",
              "    }\n",
              "\n",
              "    .dataframe tbody tr th {\n",
              "        vertical-align: top;\n",
              "    }\n",
              "\n",
              "    .dataframe thead th {\n",
              "        text-align: right;\n",
              "    }\n",
              "</style>\n",
              "<table border=\"1\" class=\"dataframe\">\n",
              "  <thead>\n",
              "    <tr style=\"text-align: right;\">\n",
              "      <th></th>\n",
              "      <th>query</th>\n",
              "      <th>page</th>\n",
              "      <th>clicks</th>\n",
              "      <th>impressions</th>\n",
              "      <th>ctr</th>\n",
              "      <th>weighted avg position</th>\n",
              "      <th>Char</th>\n",
              "      <th>Stemming</th>\n",
              "      <th>Stems Ordered by frequency</th>\n",
              "      <th>Strongest word stem</th>\n",
              "      <th>Lemmatized</th>\n",
              "      <th>Lemmas Ordered by frequency</th>\n",
              "      <th>Strongest lemma</th>\n",
              "      <th>spacy_nouns</th>\n",
              "      <th>Brand/Non-branded</th>\n",
              "    </tr>\n",
              "  </thead>\n",
              "  <tbody>\n",
              "    <tr>\n",
              "      <th>718</th>\n",
              "      <td>eve milano</td>\n",
              "      <td>https://www.evemilano.com/</td>\n",
              "      <td>157</td>\n",
              "      <td>946</td>\n",
              "      <td>16.60%</td>\n",
              "      <td>1</td>\n",
              "      <td>10</td>\n",
              "      <td>eve mil</td>\n",
              "      <td>mil eve</td>\n",
              "      <td>mil</td>\n",
              "      <td>eve Milano</td>\n",
              "      <td>Milano eve</td>\n",
              "      <td>Milano</td>\n",
              "      <td>other</td>\n",
              "      <td>Brand</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>825</th>\n",
              "      <td>eve milano</td>\n",
              "      <td>https://www.evemilano.com/guide-seo/</td>\n",
              "      <td>6</td>\n",
              "      <td>855</td>\n",
              "      <td>0.70%</td>\n",
              "      <td>1</td>\n",
              "      <td>10</td>\n",
              "      <td>eve mil</td>\n",
              "      <td>mil eve</td>\n",
              "      <td>mil</td>\n",
              "      <td>eve Milano</td>\n",
              "      <td>Milano eve</td>\n",
              "      <td>Milano</td>\n",
              "      <td>other</td>\n",
              "      <td>Brand</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>886</th>\n",
              "      <td>eve milano</td>\n",
              "      <td>https://www.evemilano.com/contatti/</td>\n",
              "      <td>1</td>\n",
              "      <td>812</td>\n",
              "      <td>0.12%</td>\n",
              "      <td>1</td>\n",
              "      <td>10</td>\n",
              "      <td>eve mil</td>\n",
              "      <td>mil eve</td>\n",
              "      <td>mil</td>\n",
              "      <td>eve Milano</td>\n",
              "      <td>Milano eve</td>\n",
              "      <td>Milano</td>\n",
              "      <td>other</td>\n",
              "      <td>Brand</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>977</th>\n",
              "      <td>site:www.evemilano.com</td>\n",
              "      <td>https://www.evemilano.com/blog/</td>\n",
              "      <td>0</td>\n",
              "      <td>763</td>\n",
              "      <td>0.00%</td>\n",
              "      <td>9</td>\n",
              "      <td>22</td>\n",
              "      <td>site:www.evemilano.com</td>\n",
              "      <td>site:www.evemilano.com</td>\n",
              "      <td>site:www.evemilano.com</td>\n",
              "      <td>sire www.evemilano.com</td>\n",
              "      <td>sire www.evemilano.com</td>\n",
              "      <td>sire</td>\n",
              "      <td>other</td>\n",
              "      <td>Brand</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>978</th>\n",
              "      <td>site:www.evemilano.com</td>\n",
              "      <td>https://www.evemilano.com/</td>\n",
              "      <td>0</td>\n",
              "      <td>763</td>\n",
              "      <td>0.00%</td>\n",
              "      <td>1</td>\n",
              "      <td>22</td>\n",
              "      <td>site:www.evemilano.com</td>\n",
              "      <td>site:www.evemilano.com</td>\n",
              "      <td>site:www.evemilano.com</td>\n",
              "      <td>sire www.evemilano.com</td>\n",
              "      <td>sire www.evemilano.com</td>\n",
              "      <td>sire</td>\n",
              "      <td>other</td>\n",
              "      <td>Brand</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>...</th>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>90162</th>\n",
              "      <td>giovanni sacheli</td>\n",
              "      <td>https://www.evemilano.com/ottimizzare-css/</td>\n",
              "      <td>0</td>\n",
              "      <td>1</td>\n",
              "      <td>0.00%</td>\n",
              "      <td>6</td>\n",
              "      <td>16</td>\n",
              "      <td>giovann sachel</td>\n",
              "      <td>giovann sachel</td>\n",
              "      <td>giovann</td>\n",
              "      <td>Giovanni sacheli</td>\n",
              "      <td>Giovanni sacheli</td>\n",
              "      <td>Giovanni</td>\n",
              "      <td>other</td>\n",
              "      <td>Brand</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>90164</th>\n",
              "      <td>giovanni sacheli</td>\n",
              "      <td>https://www.evemilano.com/content-audit/</td>\n",
              "      <td>0</td>\n",
              "      <td>1</td>\n",
              "      <td>0.00%</td>\n",
              "      <td>5</td>\n",
              "      <td>16</td>\n",
              "      <td>giovann sachel</td>\n",
              "      <td>giovann sachel</td>\n",
              "      <td>giovann</td>\n",
              "      <td>Giovanni sacheli</td>\n",
              "      <td>Giovanni sacheli</td>\n",
              "      <td>Giovanni</td>\n",
              "      <td>other</td>\n",
              "      <td>Brand</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>90165</th>\n",
              "      <td>giovanni sacheli</td>\n",
              "      <td>https://www.evemilano.com/contatti/?utm_source...</td>\n",
              "      <td>0</td>\n",
              "      <td>1</td>\n",
              "      <td>0.00%</td>\n",
              "      <td>13</td>\n",
              "      <td>16</td>\n",
              "      <td>giovann sachel</td>\n",
              "      <td>giovann sachel</td>\n",
              "      <td>giovann</td>\n",
              "      <td>Giovanni sacheli</td>\n",
              "      <td>Giovanni sacheli</td>\n",
              "      <td>Giovanni</td>\n",
              "      <td>other</td>\n",
              "      <td>Brand</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>90166</th>\n",
              "      <td>giovanni sacheli</td>\n",
              "      <td>https://www.evemilano.com/cls-tools/</td>\n",
              "      <td>0</td>\n",
              "      <td>1</td>\n",
              "      <td>0.00%</td>\n",
              "      <td>6</td>\n",
              "      <td>16</td>\n",
              "      <td>giovann sachel</td>\n",
              "      <td>giovann sachel</td>\n",
              "      <td>giovann</td>\n",
              "      <td>Giovanni sacheli</td>\n",
              "      <td>Giovanni sacheli</td>\n",
              "      <td>Giovanni</td>\n",
              "      <td>other</td>\n",
              "      <td>Brand</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>90168</th>\n",
              "      <td>giovanni sacheli</td>\n",
              "      <td>https://www.evemilano.com/?utm_source=googlemy...</td>\n",
              "      <td>0</td>\n",
              "      <td>1</td>\n",
              "      <td>0.00%</td>\n",
              "      <td>11</td>\n",
              "      <td>16</td>\n",
              "      <td>giovann sachel</td>\n",
              "      <td>giovann sachel</td>\n",
              "      <td>giovann</td>\n",
              "      <td>Giovanni sacheli</td>\n",
              "      <td>Giovanni sacheli</td>\n",
              "      <td>Giovanni</td>\n",
              "      <td>other</td>\n",
              "      <td>Brand</td>\n",
              "    </tr>\n",
              "  </tbody>\n",
              "</table>\n",
              "<p>258 rows × 15 columns</p>\n",
              "</div>"
            ],
            "text/plain": [
              "                        query  \\\n",
              "718                eve milano   \n",
              "825                eve milano   \n",
              "886                eve milano   \n",
              "977    site:www.evemilano.com   \n",
              "978    site:www.evemilano.com   \n",
              "...                       ...   \n",
              "90162        giovanni sacheli   \n",
              "90164        giovanni sacheli   \n",
              "90165        giovanni sacheli   \n",
              "90166        giovanni sacheli   \n",
              "90168        giovanni sacheli   \n",
              "\n",
              "                                                    page  clicks  impressions  \\\n",
              "718                           https://www.evemilano.com/     157          946   \n",
              "825                 https://www.evemilano.com/guide-seo/       6          855   \n",
              "886                  https://www.evemilano.com/contatti/       1          812   \n",
              "977                      https://www.evemilano.com/blog/       0          763   \n",
              "978                           https://www.evemilano.com/       0          763   \n",
              "...                                                  ...     ...          ...   \n",
              "90162         https://www.evemilano.com/ottimizzare-css/       0            1   \n",
              "90164           https://www.evemilano.com/content-audit/       0            1   \n",
              "90165  https://www.evemilano.com/contatti/?utm_source...       0            1   \n",
              "90166               https://www.evemilano.com/cls-tools/       0            1   \n",
              "90168  https://www.evemilano.com/?utm_source=googlemy...       0            1   \n",
              "\n",
              "         ctr  weighted avg position  Char                Stemming  \\\n",
              "718   16.60%                      1    10                 eve mil   \n",
              "825    0.70%                      1    10                 eve mil   \n",
              "886    0.12%                      1    10                 eve mil   \n",
              "977    0.00%                      9    22  site:www.evemilano.com   \n",
              "978    0.00%                      1    22  site:www.evemilano.com   \n",
              "...      ...                    ...   ...                     ...   \n",
              "90162  0.00%                      6    16          giovann sachel   \n",
              "90164  0.00%                      5    16          giovann sachel   \n",
              "90165  0.00%                     13    16          giovann sachel   \n",
              "90166  0.00%                      6    16          giovann sachel   \n",
              "90168  0.00%                     11    16          giovann sachel   \n",
              "\n",
              "      Stems Ordered by frequency     Strongest word stem  \\\n",
              "718                      mil eve                     mil   \n",
              "825                      mil eve                     mil   \n",
              "886                      mil eve                     mil   \n",
              "977       site:www.evemilano.com  site:www.evemilano.com   \n",
              "978       site:www.evemilano.com  site:www.evemilano.com   \n",
              "...                          ...                     ...   \n",
              "90162             giovann sachel                 giovann   \n",
              "90164             giovann sachel                 giovann   \n",
              "90165             giovann sachel                 giovann   \n",
              "90166             giovann sachel                 giovann   \n",
              "90168             giovann sachel                 giovann   \n",
              "\n",
              "                   Lemmatized Lemmas Ordered by frequency Strongest lemma  \\\n",
              "718                eve Milano                  Milano eve          Milano   \n",
              "825                eve Milano                  Milano eve          Milano   \n",
              "886                eve Milano                  Milano eve          Milano   \n",
              "977    sire www.evemilano.com      sire www.evemilano.com            sire   \n",
              "978    sire www.evemilano.com      sire www.evemilano.com            sire   \n",
              "...                       ...                         ...             ...   \n",
              "90162        Giovanni sacheli            Giovanni sacheli        Giovanni   \n",
              "90164        Giovanni sacheli            Giovanni sacheli        Giovanni   \n",
              "90165        Giovanni sacheli            Giovanni sacheli        Giovanni   \n",
              "90166        Giovanni sacheli            Giovanni sacheli        Giovanni   \n",
              "90168        Giovanni sacheli            Giovanni sacheli        Giovanni   \n",
              "\n",
              "      spacy_nouns Brand/Non-branded  \n",
              "718         other             Brand  \n",
              "825         other             Brand  \n",
              "886         other             Brand  \n",
              "977         other             Brand  \n",
              "978         other             Brand  \n",
              "...           ...               ...  \n",
              "90162       other             Brand  \n",
              "90164       other             Brand  \n",
              "90165       other             Brand  \n",
              "90166       other             Brand  \n",
              "90168       other             Brand  \n",
              "\n",
              "[258 rows x 15 columns]"
            ]
          },
          "execution_count": 203,
          "metadata": {},
          "output_type": "execute_result"
        }
      ],
      "source": [
        "df_brand"
      ]
    },
    {
      "cell_type": "code",
      "execution_count": 204,
      "metadata": {},
      "outputs": [
        {
          "name": "stdout",
          "output_type": "stream",
          "text": [
            "Somma totale dei clicks: 504\n",
            "Somma totale delle impressions: 3247\n",
            "Rows: 7\n"
          ]
        }
      ],
      "source": [
        "# pvt brand mantenendo solo la prima query per impression (rimuove i sitelink) come fa google search console\n",
        "\n",
        "if brand_row_count == 0:\n",
        "    print(\"La categoria 'Brand' ha zero righe.\")\n",
        "else:\n",
        "    # Ordina il DataFrame per 'query' e 'impressions' in ordine decrescente\n",
        "    df_brand_sorted = df_brand.sort_values(by=['query', 'impressions'], ascending=[True, False])\n",
        "\n",
        "    # Rimuovi i duplicati, mantenendo solo la prima occorrenza (quella con il massimo di 'impressions')\n",
        "    df_brand_unique = df_brand_sorted.drop_duplicates(subset='query')\n",
        "\n",
        "    # Crea la pivot table\n",
        "    pivot_b = df_brand_unique.pivot_table(\n",
        "        index='query', \n",
        "        values=['clicks', 'impressions', 'weighted avg position'], \n",
        "        aggfunc={\n",
        "            'clicks': 'sum',\n",
        "            'impressions': 'sum',\n",
        "            'weighted avg position': lambda x: weighted_mean(x, df_brand_unique.loc[x.index, 'impressions']),\n",
        "        }\n",
        "    )\n",
        "\n",
        "    # Calcolo del CTR\n",
        "    #pivot_b['ctr'] = (pivot_b['clicks'] / pivot_b['impressions']) * 100\n",
        "    pivot_b['ctr'] = (pivot_b['clicks'] / pivot_b['impressions']) \n",
        "\n",
        "    # Riordina le colonne\n",
        "    sorted_pivot = pivot_b.reindex(columns=['clicks', 'impressions', 'ctr', 'weighted avg position'])\n",
        "\n",
        "\n",
        "    # Ordina la pivot table per 'impressions' in ordine decrescente\n",
        "    sorted_pivot = sorted_pivot.sort_values(by='impressions', ascending=False)\n",
        "\n",
        "    # Arrotonda i valori nella colonna 'weighted avg position' e li converte in interi\n",
        "    sorted_pivot['weighted avg position'] = sorted_pivot['weighted avg position'].round().astype(int)\n",
        "\n",
        "\n",
        "\n",
        "    # Stampa la somma totale dei clicks e delle impressions\n",
        "    total_clicks = sorted_pivot['clicks'].sum()\n",
        "    total_impressions = sorted_pivot['impressions'].sum()\n",
        "\n",
        "    print(\"Somma totale dei clicks:\", total_clicks)\n",
        "    print(\"Somma totale delle impressions:\", total_impressions)\n",
        "\n",
        "\n",
        "    print(\"Rows: \" + str(sorted_pivot.shape[0]))\n",
        "\n",
        "    # Mostra le prime righe della pivot table\n",
        "    # EXPORT PVT BRAND\n",
        "    sorted_pivot.head(5)"
      ]
    },
    {
      "cell_type": "code",
      "execution_count": 238,
      "metadata": {},
      "outputs": [
        {
          "name": "stdout",
          "output_type": "stream",
          "text": [
            "Creazione tabella pivot base URL\n",
            "Somma totale dei clicks: 32351\n",
            "Somma totale delle impressions: 5021292\n",
            "Rows: 1363\n"
          ]
        },
        {
          "data": {
            "text/html": [
              "<div>\n",
              "<style scoped>\n",
              "    .dataframe tbody tr th:only-of-type {\n",
              "        vertical-align: middle;\n",
              "    }\n",
              "\n",
              "    .dataframe tbody tr th {\n",
              "        vertical-align: top;\n",
              "    }\n",
              "\n",
              "    .dataframe thead th {\n",
              "        text-align: right;\n",
              "    }\n",
              "</style>\n",
              "<table border=\"1\" class=\"dataframe\">\n",
              "  <thead>\n",
              "    <tr style=\"text-align: right;\">\n",
              "      <th></th>\n",
              "      <th>clicks</th>\n",
              "      <th>impressions</th>\n",
              "      <th>ctr</th>\n",
              "      <th>weighted avg position</th>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>page</th>\n",
              "      <th></th>\n",
              "      <th></th>\n",
              "      <th></th>\n",
              "      <th></th>\n",
              "    </tr>\n",
              "  </thead>\n",
              "  <tbody>\n",
              "    <tr>\n",
              "      <th>https://www.evemilano.com/web-archive/</th>\n",
              "      <td>436</td>\n",
              "      <td>148786</td>\n",
              "      <td>0.29%</td>\n",
              "      <td>8</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>https://www.evemilano.com/proxy-server/</th>\n",
              "      <td>50</td>\n",
              "      <td>137052</td>\n",
              "      <td>0.04%</td>\n",
              "      <td>12</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>https://www.evemilano.com/come-trovare-indirizzo-ip-sito-web/</th>\n",
              "      <td>1100</td>\n",
              "      <td>130048</td>\n",
              "      <td>0.85%</td>\n",
              "      <td>13</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>https://www.evemilano.com/</th>\n",
              "      <td>379</td>\n",
              "      <td>106634</td>\n",
              "      <td>0.36%</td>\n",
              "      <td>48</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>https://www.evemilano.com/servizi-seo/</th>\n",
              "      <td>24</td>\n",
              "      <td>106493</td>\n",
              "      <td>0.02%</td>\n",
              "      <td>45</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>https://www.evemilano.com/servizi-web-marketing/</th>\n",
              "      <td>6</td>\n",
              "      <td>105631</td>\n",
              "      <td>0.01%</td>\n",
              "      <td>40</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>https://www.evemilano.com/guide-seo/motori-di-ricerca/</th>\n",
              "      <td>244</td>\n",
              "      <td>100909</td>\n",
              "      <td>0.24%</td>\n",
              "      <td>25</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>https://www.evemilano.com/pubblicita-google/consulenza-adwords/</th>\n",
              "      <td>12</td>\n",
              "      <td>94861</td>\n",
              "      <td>0.01%</td>\n",
              "      <td>27</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>https://www.evemilano.com/servizi-seo/posizionamento-siti/</th>\n",
              "      <td>3</td>\n",
              "      <td>91013</td>\n",
              "      <td>0.00%</td>\n",
              "      <td>49</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>https://www.evemilano.com/gdpr/</th>\n",
              "      <td>53</td>\n",
              "      <td>84624</td>\n",
              "      <td>0.06%</td>\n",
              "      <td>11</td>\n",
              "    </tr>\n",
              "  </tbody>\n",
              "</table>\n",
              "</div>"
            ],
            "text/plain": [
              "                                                    clicks  impressions   ctr  \\\n",
              "page                                                                            \n",
              "https://www.evemilano.com/web-archive/                 436       148786 0.29%   \n",
              "https://www.evemilano.com/proxy-server/                 50       137052 0.04%   \n",
              "https://www.evemilano.com/come-trovare-indirizz...    1100       130048 0.85%   \n",
              "https://www.evemilano.com/                             379       106634 0.36%   \n",
              "https://www.evemilano.com/servizi-seo/                  24       106493 0.02%   \n",
              "https://www.evemilano.com/servizi-web-marketing/         6       105631 0.01%   \n",
              "https://www.evemilano.com/guide-seo/motori-di-r...     244       100909 0.24%   \n",
              "https://www.evemilano.com/pubblicita-google/con...      12        94861 0.01%   \n",
              "https://www.evemilano.com/servizi-seo/posiziona...       3        91013 0.00%   \n",
              "https://www.evemilano.com/gdpr/                         53        84624 0.06%   \n",
              "\n",
              "                                                    weighted avg position  \n",
              "page                                                                       \n",
              "https://www.evemilano.com/web-archive/                                  8  \n",
              "https://www.evemilano.com/proxy-server/                                12  \n",
              "https://www.evemilano.com/come-trovare-indirizz...                     13  \n",
              "https://www.evemilano.com/                                             48  \n",
              "https://www.evemilano.com/servizi-seo/                                 45  \n",
              "https://www.evemilano.com/servizi-web-marketing/                       40  \n",
              "https://www.evemilano.com/guide-seo/motori-di-r...                     25  \n",
              "https://www.evemilano.com/pubblicita-google/con...                     27  \n",
              "https://www.evemilano.com/servizi-seo/posiziona...                     49  \n",
              "https://www.evemilano.com/gdpr/                                        11  "
            ]
          },
          "execution_count": 238,
          "metadata": {},
          "output_type": "execute_result"
        }
      ],
      "source": [
        "# Tabella Raw URL con pivot\n",
        "# Crea una tabella pivot con multi-livello di indici\n",
        "print('Creazione tabella pivot base URL')\n",
        "\n",
        "# Crea una tabella pivot con multi-livello di indici\n",
        "final_pivot_tableP = final_data.pivot_table(index=['page'], values=['clicks', 'impressions', 'position'], \n",
        "                                            aggfunc={\n",
        "                                                'clicks': 'sum', \n",
        "                                                'impressions': 'sum', \n",
        "                                                'position': lambda x: weighted_mean(x, final_data.loc[x.index, 'impressions'])\n",
        "                                            })\n",
        "# Calcolo del CTR\n",
        "final_pivot_tableP['ctr'] = (final_pivot_tableP['clicks'] / final_pivot_tableP['impressions']) \n",
        "# Ordina la tabella pivot in base alla somma di impressions\n",
        "final_pivot_tableP.sort_values(by='impressions', axis=0, ascending=False, inplace=True)\n",
        "final_pivot_tableP = final_pivot_tableP.rename(columns={'position': 'weighted avg position'})\n",
        "final_pivot_tableP = final_pivot_tableP.reindex(columns=['clicks', 'impressions', 'ctr', 'weighted avg position'])\n",
        "\n",
        "# Converte i valori di 'weighted avg position' da decimali a interi\n",
        "final_pivot_tableP['weighted avg position'] = final_pivot_tableP['weighted avg position'].astype(int)\n",
        "\n",
        "# Mostra la tabella pivot ordinata\n",
        "# Stampa la somma totale dei clicks e delle impressions\n",
        "total_clicks = final_pivot_tableP['clicks'].sum()\n",
        "total_impressions = final_pivot_tableP['impressions'].sum()\n",
        "\n",
        "print(\"Somma totale dei clicks:\", total_clicks)\n",
        "print(\"Somma totale delle impressions:\", total_impressions)\n",
        "\n",
        "print(\"Rows: \" + str(final_pivot_tableP.shape[0]))\n",
        "final_pivot_tableP.head(10)"
      ]
    },
    {
      "cell_type": "code",
      "execution_count": 239,
      "metadata": {},
      "outputs": [
        {
          "name": "stdout",
          "output_type": "stream",
          "text": [
            "Creazione tabella pivot base QUERY\n",
            "Calcolo del CTR\n",
            "Somma totale dei clicks: 32311\n",
            "Somma totale delle impressions: 4545130\n",
            "Rows: 75442\n"
          ]
        },
        {
          "data": {
            "text/html": [
              "<div>\n",
              "<style scoped>\n",
              "    .dataframe tbody tr th:only-of-type {\n",
              "        vertical-align: middle;\n",
              "    }\n",
              "\n",
              "    .dataframe tbody tr th {\n",
              "        vertical-align: top;\n",
              "    }\n",
              "\n",
              "    .dataframe thead th {\n",
              "        text-align: right;\n",
              "    }\n",
              "</style>\n",
              "<table border=\"1\" class=\"dataframe\">\n",
              "  <thead>\n",
              "    <tr style=\"text-align: right;\">\n",
              "      <th></th>\n",
              "      <th>clicks</th>\n",
              "      <th>impressions</th>\n",
              "      <th>ctr</th>\n",
              "      <th>weighted avg position</th>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>query</th>\n",
              "      <th></th>\n",
              "      <th></th>\n",
              "      <th></th>\n",
              "      <th></th>\n",
              "    </tr>\n",
              "  </thead>\n",
              "  <tbody>\n",
              "    <tr>\n",
              "      <th>web archive</th>\n",
              "      <td>200</td>\n",
              "      <td>62371</td>\n",
              "      <td>0.32%</td>\n",
              "      <td>5</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>proxy</th>\n",
              "      <td>5</td>\n",
              "      <td>51043</td>\n",
              "      <td>0.01%</td>\n",
              "      <td>10</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>webarchive</th>\n",
              "      <td>88</td>\n",
              "      <td>43088</td>\n",
              "      <td>0.20%</td>\n",
              "      <td>5</td>\n",
              "    </tr>\n",
              "  </tbody>\n",
              "</table>\n",
              "</div>"
            ],
            "text/plain": [
              "             clicks  impressions   ctr  weighted avg position\n",
              "query                                                        \n",
              "web archive     200        62371 0.32%                      5\n",
              "proxy             5        51043 0.01%                     10\n",
              "webarchive       88        43088 0.20%                      5"
            ]
          },
          "execution_count": 239,
          "metadata": {},
          "output_type": "execute_result"
        }
      ],
      "source": [
        "# tabella raw query\n",
        "# Crea una tabella pivot con multi-livello di indici\n",
        "print('Creazione tabella pivot base QUERY')\n",
        "query_pivot_tableP = final_data1.pivot_table(index=['query'], values=['clicks', 'impressions',  'position'], \n",
        "                                            aggfunc={\n",
        "                                                'clicks': 'sum', \n",
        "                                                'impressions': 'sum', \n",
        "                                                'position': lambda x: weighted_mean(x, final_data1.loc[x.index, 'impressions'])\n",
        "                                            })\n",
        "# Calcolo del CTR\n",
        "print('Calcolo del CTR')\n",
        "query_pivot_tableP['ctr'] = (query_pivot_tableP['clicks'] / query_pivot_tableP['impressions']) * 100\n",
        "\n",
        "# Applica la formattazione alla colonna CTR\n",
        "query_pivot_tableP['ctr'] = query_pivot_tableP['ctr'].apply(format_ctr)\n",
        "# Converte i valori di 'weighted avg position' da decimali a interi\n",
        "query_pivot_tableP['position'] = query_pivot_tableP['position'].astype(int)\n",
        "\n",
        "# Ordina la tabella pivot in base alla somma di impressions\n",
        "query_pivot_tableP.sort_values(by='impressions', axis=0, ascending=False, inplace=True)\n",
        "query_pivot_tableP = query_pivot_tableP.reindex(columns=['clicks', 'impressions', 'ctr', 'position'])\n",
        "\n",
        "# Rinomina la colonna 'ctr' in 'Weighted Average CTR' e 'position' in 'Weighted Average Position'\n",
        "query_pivot_tableP = query_pivot_tableP.rename(columns={'position': 'weighted avg position'})\n",
        "\n",
        "# Stampa la somma totale dei clicks e delle impressions\n",
        "total_clicks = query_pivot_tableP['clicks'].sum()\n",
        "total_impressions = query_pivot_tableP['impressions'].sum()\n",
        "\n",
        "print(\"Somma totale dei clicks:\", total_clicks)\n",
        "print(\"Somma totale delle impressions:\", total_impressions)\n",
        "\n",
        "# Mostra la tabella pivot ordinata\n",
        "print(\"Rows: \" + str(query_pivot_tableP.shape[0]))\n",
        "query_pivot_tableP.head(3)\n"
      ]
    },
    {
      "cell_type": "code",
      "execution_count": 240,
      "metadata": {},
      "outputs": [
        {
          "data": {
            "text/html": [
              "<div>\n",
              "<style scoped>\n",
              "    .dataframe tbody tr th:only-of-type {\n",
              "        vertical-align: middle;\n",
              "    }\n",
              "\n",
              "    .dataframe tbody tr th {\n",
              "        vertical-align: top;\n",
              "    }\n",
              "\n",
              "    .dataframe thead th {\n",
              "        text-align: right;\n",
              "    }\n",
              "</style>\n",
              "<table border=\"1\" class=\"dataframe\">\n",
              "  <thead>\n",
              "    <tr style=\"text-align: right;\">\n",
              "      <th></th>\n",
              "      <th>position</th>\n",
              "      <th>website_avg_ctr_by_pos</th>\n",
              "      <th>query_count</th>\n",
              "    </tr>\n",
              "  </thead>\n",
              "  <tbody>\n",
              "    <tr>\n",
              "      <th>0</th>\n",
              "      <td>1</td>\n",
              "      <td>13.94%</td>\n",
              "      <td>3127</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>1</th>\n",
              "      <td>2</td>\n",
              "      <td>8.44%</td>\n",
              "      <td>1361</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>2</th>\n",
              "      <td>3</td>\n",
              "      <td>4.12%</td>\n",
              "      <td>1256</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>3</th>\n",
              "      <td>4</td>\n",
              "      <td>3.19%</td>\n",
              "      <td>1396</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>4</th>\n",
              "      <td>5</td>\n",
              "      <td>0.97%</td>\n",
              "      <td>1639</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>5</th>\n",
              "      <td>6</td>\n",
              "      <td>1.32%</td>\n",
              "      <td>1813</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>6</th>\n",
              "      <td>7</td>\n",
              "      <td>1.04%</td>\n",
              "      <td>1796</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>7</th>\n",
              "      <td>8</td>\n",
              "      <td>0.27%</td>\n",
              "      <td>2008</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>8</th>\n",
              "      <td>9</td>\n",
              "      <td>0.51%</td>\n",
              "      <td>2130</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>9</th>\n",
              "      <td>10</td>\n",
              "      <td>0.30%</td>\n",
              "      <td>1990</td>\n",
              "    </tr>\n",
              "  </tbody>\n",
              "</table>\n",
              "</div>"
            ],
            "text/plain": [
              "   position  website_avg_ctr_by_pos  query_count\n",
              "0         1                  13.94%         3127\n",
              "1         2                   8.44%         1361\n",
              "2         3                   4.12%         1256\n",
              "3         4                   3.19%         1396\n",
              "4         5                   0.97%         1639\n",
              "5         6                   1.32%         1813\n",
              "6         7                   1.04%         1796\n",
              "7         8                   0.27%         2008\n",
              "8         9                   0.51%         2130\n",
              "9        10                   0.30%         1990"
            ]
          },
          "execution_count": 240,
          "metadata": {},
          "output_type": "execute_result"
        }
      ],
      "source": [
        "# CALCOLO TABELLA WEBSITE CTR BY POS per chiavi NOBRAND\n",
        "# Verifica il tipo di dati della colonna 'ctr'\n",
        "if df_nobrand['ctr'].dtype == 'O':  # 'O' sta per 'object', che è tipicamente usato per le stringhe in pandas\n",
        "    # Converti la colonna 'ctr' da percentuale (stringa) a float\n",
        "    df_nobrand['ctr'] = df_nobrand['ctr'].str.rstrip('%').astype('float') / 100\n",
        "\n",
        "# Funzione per calcolare la media ponderata\n",
        "def weighted_mean(values, weights):\n",
        "    return np.sum(values * weights) / np.sum(weights)\n",
        "\n",
        "# Raggruppa per 'Weighted Avg Position' e calcola la media ponderata del CTR\n",
        "query_analysis = df_nobrand.groupby('weighted avg position').apply(\n",
        "    lambda x: weighted_mean(x['ctr'], x['impressions'])\n",
        ").reset_index()\n",
        "\n",
        "# Rinomina le colonne\n",
        "query_analysis = query_analysis.rename(\n",
        "    columns={0: 'website_avg_ctr_by_pos', 'weighted avg position': 'position'}\n",
        ")\n",
        "\n",
        "query_analysis['position'] = np.round(query_analysis['position'].astype(float).astype(int))\n",
        "\n",
        "# Conta le query per ciascuna posizione in df_nobrand\n",
        "query_count = df_nobrand.groupby('weighted avg position').size().reset_index(name='query_count')\n",
        "\n",
        "# Converti 'Weighted Avg Position' in valori interi per il merge\n",
        "query_count['weighted avg position'] = np.round(query_count['weighted avg position'].astype(float) ).astype(int)\n",
        "\n",
        "# Aggiungi la colonna query_count a query_analysis\n",
        "query_analysis = query_analysis.merge(query_count, left_on='position', right_on='weighted avg position', how='left')\n",
        "\n",
        "# Rimuovi la colonna aggiuntiva 'Weighted Avg Position' risultante dal merge\n",
        "query_analysis.drop('weighted avg position', axis=1, inplace=True)\n",
        "\n",
        "# Ordina i risultati per 'position'\n",
        "query_analysis.sort_values(by='position', ascending=True, inplace=True)\n",
        "\n",
        "# Visualizza i risultati\n",
        "query_analysis.head(10)\n"
      ]
    },
    {
      "cell_type": "code",
      "execution_count": 241,
      "metadata": {},
      "outputs": [
        {
          "data": {
            "image/png": 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            "text/plain": [
              "<Figure size 1500x900 with 2 Axes>"
            ]
          },
          "metadata": {},
          "output_type": "display_data"
        }
      ],
      "source": [
        "# gfx test 2 invertito\n",
        "\n",
        "# Assumi che query_analysis sia già definito e caricato\n",
        "\n",
        "# Assicurati che il DataFrame sia ordinato in base alla 'position'\n",
        "query_analysis = query_analysis.sort_values(by='position')\n",
        "\n",
        "# Seleziona solo le prime 10 posizioni\n",
        "top_10_query_analysis = query_analysis.head(10)\n",
        "\n",
        "# Imposta le dimensioni del grafico\n",
        "plt.figure(figsize=(15, 9))\n",
        "\n",
        "# Crea l'asse per il conteggio delle query\n",
        "ax1 = plt.gca()  # Get current axis\n",
        "ax1.bar(top_10_query_analysis['position'], top_10_query_analysis['query_count'], color='g', alpha=0.6, label='Query Count')\n",
        "ax1.set_xlabel('Position')\n",
        "ax1.set_ylabel('Query Count', color='g')\n",
        "ax1.tick_params(axis='y', labelcolor='g')\n",
        "\n",
        "# Crea un secondo asse per il CTR\n",
        "ax2 = ax1.twinx()  # Crea un secondo asse che condivide lo stesso asse x\n",
        "ax2.plot(top_10_query_analysis['position'], top_10_query_analysis['website_avg_ctr_by_pos'] * 100, color='b', marker='o', label='CTR')\n",
        "ax2.set_ylabel('CTR (%)', color='b')\n",
        "ax2.tick_params(axis='y', labelcolor='b')\n",
        "\n",
        "# Aggiungi titoli e legenda\n",
        "plt.title('Query Count and CTR by Position (Top 10 Positions)')\n",
        "ax1.legend(loc='upper left')\n",
        "ax2.legend(loc='upper right')\n",
        "\n",
        "# Aggiungi la firma\n",
        "ax1.text(0.05, 0.005, 'by evemilano.com', transform=ax1.transAxes, fontsize=10,\n",
        "        verticalalignment='bottom', horizontalalignment='right', color='grey', alpha=0.5)\n",
        "\n",
        "\n",
        "\n",
        "# Salva l'immagine\n",
        "file_name = 'output_file_name'  # Sostituisci con il nome del file di output desiderato\n",
        "plt.savefig(f'{new_output_dir}/{file_name}_query_count_and_ctr_by_position.png', bbox_inches='tight')\n",
        "\n",
        "# Mostra il grafico\n",
        "plt.show()\n",
        "\n",
        "# Chiudi la figura per liberare memoria\n",
        "plt.close()\n"
      ]
    },
    {
      "cell_type": "code",
      "execution_count": 242,
      "metadata": {},
      "outputs": [
        {
          "name": "stdout",
          "output_type": "stream",
          "text": [
            "Missing positions in mapping: []\n",
            "Somma totale dei clicks: 32351\n",
            "Somma totale delle impressions: 5021292\n"
          ]
        },
        {
          "data": {
            "text/html": [
              "<div>\n",
              "<style scoped>\n",
              "    .dataframe tbody tr th:only-of-type {\n",
              "        vertical-align: middle;\n",
              "    }\n",
              "\n",
              "    .dataframe tbody tr th {\n",
              "        vertical-align: top;\n",
              "    }\n",
              "\n",
              "    .dataframe thead th {\n",
              "        text-align: right;\n",
              "    }\n",
              "</style>\n",
              "<table border=\"1\" class=\"dataframe\">\n",
              "  <thead>\n",
              "    <tr style=\"text-align: right;\">\n",
              "      <th></th>\n",
              "      <th>page</th>\n",
              "      <th>clicks</th>\n",
              "      <th>impressions</th>\n",
              "      <th>ctr</th>\n",
              "      <th>weighted avg position</th>\n",
              "      <th>website_avg_ctr_by_pos</th>\n",
              "    </tr>\n",
              "  </thead>\n",
              "  <tbody>\n",
              "    <tr>\n",
              "      <th>0</th>\n",
              "      <td>https://www.evemilano.com/web-archive/</td>\n",
              "      <td>436</td>\n",
              "      <td>148786</td>\n",
              "      <td>0.29%</td>\n",
              "      <td>8</td>\n",
              "      <td>0.27%</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>1</th>\n",
              "      <td>https://www.evemilano.com/proxy-server/</td>\n",
              "      <td>50</td>\n",
              "      <td>137052</td>\n",
              "      <td>0.04%</td>\n",
              "      <td>12</td>\n",
              "      <td>0.48%</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>2</th>\n",
              "      <td>https://www.evemilano.com/come-trovare-indiriz...</td>\n",
              "      <td>1100</td>\n",
              "      <td>130048</td>\n",
              "      <td>0.85%</td>\n",
              "      <td>13</td>\n",
              "      <td>0.57%</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>3</th>\n",
              "      <td>https://www.evemilano.com/</td>\n",
              "      <td>379</td>\n",
              "      <td>106634</td>\n",
              "      <td>0.36%</td>\n",
              "      <td>48</td>\n",
              "      <td>0.07%</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>4</th>\n",
              "      <td>https://www.evemilano.com/servizi-seo/</td>\n",
              "      <td>24</td>\n",
              "      <td>106493</td>\n",
              "      <td>0.02%</td>\n",
              "      <td>45</td>\n",
              "      <td>0.19%</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>5</th>\n",
              "      <td>https://www.evemilano.com/servizi-web-marketing/</td>\n",
              "      <td>6</td>\n",
              "      <td>105631</td>\n",
              "      <td>0.01%</td>\n",
              "      <td>40</td>\n",
              "      <td>0.08%</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>6</th>\n",
              "      <td>https://www.evemilano.com/guide-seo/motori-di-...</td>\n",
              "      <td>244</td>\n",
              "      <td>100909</td>\n",
              "      <td>0.24%</td>\n",
              "      <td>25</td>\n",
              "      <td>0.45%</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>7</th>\n",
              "      <td>https://www.evemilano.com/pubblicita-google/co...</td>\n",
              "      <td>12</td>\n",
              "      <td>94861</td>\n",
              "      <td>0.01%</td>\n",
              "      <td>27</td>\n",
              "      <td>1.59%</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>8</th>\n",
              "      <td>https://www.evemilano.com/servizi-seo/posizion...</td>\n",
              "      <td>3</td>\n",
              "      <td>91013</td>\n",
              "      <td>0.00%</td>\n",
              "      <td>49</td>\n",
              "      <td>0.15%</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>9</th>\n",
              "      <td>https://www.evemilano.com/gdpr/</td>\n",
              "      <td>53</td>\n",
              "      <td>84624</td>\n",
              "      <td>0.06%</td>\n",
              "      <td>11</td>\n",
              "      <td>0.42%</td>\n",
              "    </tr>\n",
              "  </tbody>\n",
              "</table>\n",
              "</div>"
            ],
            "text/plain": [
              "                                                page  clicks  impressions  \\\n",
              "0             https://www.evemilano.com/web-archive/     436       148786   \n",
              "1            https://www.evemilano.com/proxy-server/      50       137052   \n",
              "2  https://www.evemilano.com/come-trovare-indiriz...    1100       130048   \n",
              "3                         https://www.evemilano.com/     379       106634   \n",
              "4             https://www.evemilano.com/servizi-seo/      24       106493   \n",
              "5   https://www.evemilano.com/servizi-web-marketing/       6       105631   \n",
              "6  https://www.evemilano.com/guide-seo/motori-di-...     244       100909   \n",
              "7  https://www.evemilano.com/pubblicita-google/co...      12        94861   \n",
              "8  https://www.evemilano.com/servizi-seo/posizion...       3        91013   \n",
              "9                    https://www.evemilano.com/gdpr/      53        84624   \n",
              "\n",
              "    ctr  weighted avg position  website_avg_ctr_by_pos  \n",
              "0 0.29%                      8                   0.27%  \n",
              "1 0.04%                     12                   0.48%  \n",
              "2 0.85%                     13                   0.57%  \n",
              "3 0.36%                     48                   0.07%  \n",
              "4 0.02%                     45                   0.19%  \n",
              "5 0.01%                     40                   0.08%  \n",
              "6 0.24%                     25                   0.45%  \n",
              "7 0.01%                     27                   1.59%  \n",
              "8 0.00%                     49                   0.15%  \n",
              "9 0.06%                     11                   0.42%  "
            ]
          },
          "execution_count": 242,
          "metadata": {},
          "output_type": "execute_result"
        }
      ],
      "source": [
        "# file raw scaricabile con posizione media del sito web\n",
        "raw_dfP = final_pivot_tableP.copy()\n",
        "raw_dfP = raw_dfP.reset_index()\n",
        "# Assicurati che la colonna 'position' in query_analysis sia dello stesso tipo di 'weighted avg position' in raw_dfP\n",
        "query_analysis['position'] = query_analysis['position'].astype(int)\n",
        "\n",
        "# Crea un dizionario per il mapping\n",
        "ctr_mapping = dict(zip(query_analysis['position'], query_analysis['website_avg_ctr_by_pos']))\n",
        "\n",
        "# Applica il mapping\n",
        "raw_dfP['website_avg_ctr_by_pos'] = raw_dfP['weighted avg position'].map(ctr_mapping)\n",
        "\n",
        "# Verifica se ci sono valori mancanti (NaN) e il motivo\n",
        "missing_positions = raw_dfP[raw_dfP['website_avg_ctr_by_pos'].isna()]['weighted avg position'].unique()\n",
        "print(\"Missing positions in mapping:\", missing_positions)\n",
        "\n",
        "# Stampa la somma totale dei clicks e delle impressions\n",
        "total_clicks = raw_dfP['clicks'].sum()\n",
        "total_impressions = raw_dfP['impressions'].sum()\n",
        "print(\"Somma totale dei clicks:\", total_clicks)\n",
        "print(\"Somma totale delle impressions:\", total_impressions)\n",
        "# Visualizza il risultato\n",
        "raw_dfP.head(10)\n"
      ]
    },
    {
      "cell_type": "code",
      "execution_count": 243,
      "metadata": {},
      "outputs": [
        {
          "name": "stdout",
          "output_type": "stream",
          "text": [
            "Numero di righe in raw_df con '#' nella colonna 'page': 0\n",
            "Numero di righe in raw_dfP con '#' nella colonna 'page': 908\n"
          ]
        }
      ],
      "source": [
        "# Conta il numero di righe dove la colonna 'page' contiene il carattere '#'\n",
        "num_rows_with_hash = raw_df['page'].str.contains('#', na=False).sum()\n",
        "# Stampa il risultato\n",
        "print(\"Numero di righe in raw_df con '#' nella colonna 'page':\", num_rows_with_hash)\n",
        "# Conta il numero di righe dove la colonna 'page' contiene il carattere '#'\n",
        "num_rows_with_hash = raw_dfP['page'].str.contains('#', na=False).sum()\n",
        "# Stampa il risultato\n",
        "print(\"Numero di righe in raw_dfP con '#' nella colonna 'page':\", num_rows_with_hash)\n"
      ]
    },
    {
      "cell_type": "code",
      "execution_count": 244,
      "metadata": {},
      "outputs": [
        {
          "name": "stdout",
          "output_type": "stream",
          "text": [
            "Rows: 1363\n",
            "Somma totale dei clicks: 32351\n",
            "Somma totale delle impressions: 5021292\n"
          ]
        },
        {
          "data": {
            "text/html": [
              "<div>\n",
              "<style scoped>\n",
              "    .dataframe tbody tr th:only-of-type {\n",
              "        vertical-align: middle;\n",
              "    }\n",
              "\n",
              "    .dataframe tbody tr th {\n",
              "        vertical-align: top;\n",
              "    }\n",
              "\n",
              "    .dataframe thead th {\n",
              "        text-align: right;\n",
              "    }\n",
              "</style>\n",
              "<table border=\"1\" class=\"dataframe\">\n",
              "  <thead>\n",
              "    <tr style=\"text-align: right;\">\n",
              "      <th></th>\n",
              "      <th>page</th>\n",
              "      <th>clicks</th>\n",
              "      <th>impressions</th>\n",
              "      <th>ctr</th>\n",
              "      <th>website_avg_ctr_by_pos</th>\n",
              "      <th>comparison</th>\n",
              "      <th>weighted avg position</th>\n",
              "    </tr>\n",
              "  </thead>\n",
              "  <tbody>\n",
              "    <tr>\n",
              "      <th>0</th>\n",
              "      <td>https://www.evemilano.com/web-archive/</td>\n",
              "      <td>436</td>\n",
              "      <td>148786</td>\n",
              "      <td>0.29%</td>\n",
              "      <td>0.27%</td>\n",
              "      <td>greater</td>\n",
              "      <td>8</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>1</th>\n",
              "      <td>https://www.evemilano.com/proxy-server/</td>\n",
              "      <td>50</td>\n",
              "      <td>137052</td>\n",
              "      <td>0.04%</td>\n",
              "      <td>0.48%</td>\n",
              "      <td>lower</td>\n",
              "      <td>12</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>2</th>\n",
              "      <td>https://www.evemilano.com/come-trovare-indiriz...</td>\n",
              "      <td>1100</td>\n",
              "      <td>130048</td>\n",
              "      <td>0.85%</td>\n",
              "      <td>0.57%</td>\n",
              "      <td>greater</td>\n",
              "      <td>13</td>\n",
              "    </tr>\n",
              "  </tbody>\n",
              "</table>\n",
              "</div>"
            ],
            "text/plain": [
              "                                                page  clicks  impressions  \\\n",
              "0             https://www.evemilano.com/web-archive/     436       148786   \n",
              "1            https://www.evemilano.com/proxy-server/      50       137052   \n",
              "2  https://www.evemilano.com/come-trovare-indiriz...    1100       130048   \n",
              "\n",
              "    ctr  website_avg_ctr_by_pos comparison  weighted avg position  \n",
              "0 0.29%                   0.27%    greater                      8  \n",
              "1 0.04%                   0.48%      lower                     12  \n",
              "2 0.85%                   0.57%    greater                     13  "
            ]
          },
          "execution_count": 244,
          "metadata": {},
          "output_type": "execute_result"
        }
      ],
      "source": [
        "# Funzione per confrontare i CTR\n",
        "def compare_ctr(row):\n",
        "    if row['ctr'] > row['website_avg_ctr_by_pos']:\n",
        "        return 'greater'\n",
        "    elif row['ctr'] < row['website_avg_ctr_by_pos']:\n",
        "        return 'lower'\n",
        "    else:\n",
        "        return 'equal'\n",
        "\n",
        "# Applica la funzione a ciascuna riga per creare la colonna 'comparison'\n",
        "raw_dfP['comparison'] = raw_dfP.apply(compare_ctr, axis=1)\n",
        "\n",
        "print(\"Rows: \" + str(raw_dfP.shape[0]))\n",
        "# Specifica il nuovo ordine delle colonne\n",
        "new_columns_order = ['page', 'clicks', 'impressions', 'ctr', 'website_avg_ctr_by_pos', 'comparison', 'weighted avg position']\n",
        "\n",
        "# Stampa la somma totale dei clicks e delle impressions\n",
        "total_clicks = raw_dfP['clicks'].sum()\n",
        "total_impressions = raw_dfP['impressions'].sum()\n",
        "\n",
        "print(\"Somma totale dei clicks:\", total_clicks)\n",
        "print(\"Somma totale delle impressions:\", total_impressions)\n",
        "\n",
        "# Riordina le colonne in raw_dfP\n",
        "raw_dfP = raw_dfP.reindex(columns=new_columns_order)\n",
        "\n",
        "raw_dfP.head(3)"
      ]
    },
    {
      "cell_type": "code",
      "execution_count": 245,
      "metadata": {},
      "outputs": [
        {
          "name": "stdout",
          "output_type": "stream",
          "text": [
            "Creazione tabella pivot con le cartelle di primo livello\n",
            "Somma totale dei clicks: 21127\n",
            "Somma totale delle impressions: 3573774\n"
          ]
        },
        {
          "data": {
            "text/html": [
              "<div>\n",
              "<style scoped>\n",
              "    .dataframe tbody tr th:only-of-type {\n",
              "        vertical-align: middle;\n",
              "    }\n",
              "\n",
              "    .dataframe tbody tr th {\n",
              "        vertical-align: top;\n",
              "    }\n",
              "\n",
              "    .dataframe thead th {\n",
              "        text-align: right;\n",
              "    }\n",
              "</style>\n",
              "<table border=\"1\" class=\"dataframe\">\n",
              "  <thead>\n",
              "    <tr style=\"text-align: right;\">\n",
              "      <th></th>\n",
              "      <th>clicks</th>\n",
              "      <th>impressions</th>\n",
              "      <th>url_count</th>\n",
              "      <th>ctr</th>\n",
              "      <th>click/URL</th>\n",
              "      <th>imp/URL</th>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>first_level_folder</th>\n",
              "      <th></th>\n",
              "      <th></th>\n",
              "      <th></th>\n",
              "      <th></th>\n",
              "      <th></th>\n",
              "      <th></th>\n",
              "    </tr>\n",
              "  </thead>\n",
              "  <tbody>\n",
              "    <tr>\n",
              "      <th>come-funzionano-le-espressioni-regolari-regex</th>\n",
              "      <td>1631</td>\n",
              "      <td>83965</td>\n",
              "      <td>22</td>\n",
              "      <td>1.94%</td>\n",
              "      <td>7413.64%</td>\n",
              "      <td>381659.09%</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>chrome-dev-tools</th>\n",
              "      <td>51</td>\n",
              "      <td>16670</td>\n",
              "      <td>21</td>\n",
              "      <td>0.31%</td>\n",
              "      <td>242.86%</td>\n",
              "      <td>79380.95%</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>category</th>\n",
              "      <td>1</td>\n",
              "      <td>29008</td>\n",
              "      <td>20</td>\n",
              "      <td>0.00%</td>\n",
              "      <td>5.00%</td>\n",
              "      <td>145040.00%</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>pagerank</th>\n",
              "      <td>52</td>\n",
              "      <td>26334</td>\n",
              "      <td>20</td>\n",
              "      <td>0.20%</td>\n",
              "      <td>260.00%</td>\n",
              "      <td>131670.00%</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>kpi</th>\n",
              "      <td>46</td>\n",
              "      <td>59121</td>\n",
              "      <td>20</td>\n",
              "      <td>0.08%</td>\n",
              "      <td>230.00%</td>\n",
              "      <td>295605.00%</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>...</th>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>contatti</th>\n",
              "      <td>2</td>\n",
              "      <td>21418</td>\n",
              "      <td>3</td>\n",
              "      <td>0.01%</td>\n",
              "      <td>66.67%</td>\n",
              "      <td>713933.33%</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>seo-manager</th>\n",
              "      <td>3</td>\n",
              "      <td>6139</td>\n",
              "      <td>3</td>\n",
              "      <td>0.05%</td>\n",
              "      <td>100.00%</td>\n",
              "      <td>204633.33%</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>wp-content</th>\n",
              "      <td>0</td>\n",
              "      <td>2</td>\n",
              "      <td>2</td>\n",
              "      <td>0.00%</td>\n",
              "      <td>0.00%</td>\n",
              "      <td>100.00%</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>privacy</th>\n",
              "      <td>0</td>\n",
              "      <td>99</td>\n",
              "      <td>2</td>\n",
              "      <td>0.00%</td>\n",
              "      <td>0.00%</td>\n",
              "      <td>4950.00%</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>servizi-web-marketing</th>\n",
              "      <td>6</td>\n",
              "      <td>119672</td>\n",
              "      <td>2</td>\n",
              "      <td>0.01%</td>\n",
              "      <td>300.00%</td>\n",
              "      <td>5983600.00%</td>\n",
              "    </tr>\n",
              "  </tbody>\n",
              "</table>\n",
              "<p>136 rows × 6 columns</p>\n",
              "</div>"
            ],
            "text/plain": [
              "                                               clicks  impressions  url_count  \\\n",
              "first_level_folder                                                              \n",
              "come-funzionano-le-espressioni-regolari-regex    1631        83965         22   \n",
              "chrome-dev-tools                                   51        16670         21   \n",
              "category                                            1        29008         20   \n",
              "pagerank                                           52        26334         20   \n",
              "kpi                                                46        59121         20   \n",
              "...                                               ...          ...        ...   \n",
              "contatti                                            2        21418          3   \n",
              "seo-manager                                         3         6139          3   \n",
              "wp-content                                          0            2          2   \n",
              "privacy                                             0           99          2   \n",
              "servizi-web-marketing                               6       119672          2   \n",
              "\n",
              "                                                ctr  click/URL     imp/URL  \n",
              "first_level_folder                                                          \n",
              "come-funzionano-le-espressioni-regolari-regex 1.94%   7413.64%  381659.09%  \n",
              "chrome-dev-tools                              0.31%    242.86%   79380.95%  \n",
              "category                                      0.00%      5.00%  145040.00%  \n",
              "pagerank                                      0.20%    260.00%  131670.00%  \n",
              "kpi                                           0.08%    230.00%  295605.00%  \n",
              "...                                             ...        ...         ...  \n",
              "contatti                                      0.01%     66.67%  713933.33%  \n",
              "seo-manager                                   0.05%    100.00%  204633.33%  \n",
              "wp-content                                    0.00%      0.00%     100.00%  \n",
              "privacy                                       0.00%      0.00%    4950.00%  \n",
              "servizi-web-marketing                         0.01%    300.00% 5983600.00%  \n",
              "\n",
              "[136 rows x 6 columns]"
            ]
          },
          "execution_count": 245,
          "metadata": {},
          "output_type": "execute_result"
        }
      ],
      "source": [
        "# Tabella pivot con le cartelle di primo livello\n",
        "print('Creazione tabella pivot con le cartelle di primo livello')\n",
        "# Definisci una funzione lambda per estrarre la cartella di primo livello dall'URL\n",
        "get_first_level_folder = lambda url: url.split('/')[3]\n",
        "\n",
        "# Crea una nuova colonna nel dataframe con la cartella di primo livello per ogni URL\n",
        "raw_dfP['first_level_folder'] = raw_dfP['page'].apply(get_first_level_folder)\n",
        "\n",
        "# Raggruppa il dataframe in base alla cartella di primo livello e calcola le somme di 'clicks' e 'impressions' e il conteggio degli URL\n",
        "trending_folders = raw_dfP.groupby('first_level_folder').agg({'clicks': 'sum', 'impressions': 'sum', 'page': 'count'})\n",
        "\n",
        "# Rinomina la colonna 'page' in 'count'\n",
        "trending_folders.rename(columns={'page': 'url_count'}, inplace=True)\n",
        "\n",
        "# Calcola CTR medio\n",
        "trending_folders['ctr'] = trending_folders['clicks'] / trending_folders['impressions']\n",
        "\n",
        "# Utilizza .loc per creare nuove colonne\n",
        "trending_folders.loc[:, 'click/URL'] = trending_folders['clicks'] / trending_folders['url_count']\n",
        "trending_folders.loc[:, 'imp/URL'] = trending_folders['impressions'] / trending_folders['url_count']\n",
        "\n",
        "# Ordina il dataframe risultante in base alle impressions\n",
        "trending_folders.sort_values('url_count', ascending=False, inplace=True)\n",
        "\n",
        "# cancella righe se non hanno almeno 2 URL in cartella\n",
        "trending_folders = trending_folders[trending_folders['url_count'] >= 2]\n",
        "\n",
        "# Stampa la somma totale dei clicks e delle impressions\n",
        "total_clicks = trending_folders['clicks'].sum()\n",
        "total_impressions = trending_folders['impressions'].sum()\n",
        "\n",
        "print(\"Somma totale dei clicks:\", total_clicks)\n",
        "print(\"Somma totale delle impressions:\", total_impressions)\n",
        "\n",
        "trending_folders"
      ]
    },
    {
      "cell_type": "code",
      "execution_count": 246,
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 352
        },
        "id": "UJQJjtJ9fna5",
        "outputId": "be6f847f-5b2d-43fa-e869-d37f5b2d4b18"
      },
      "outputs": [
        {
          "name": "stdout",
          "output_type": "stream",
          "text": [
            "Somma totale dei clicks: 24903\n",
            "Somma totale delle impressions: 3763566\n",
            "6847\n"
          ]
        },
        {
          "data": {
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              "<div>\n",
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              "\n",
              "    .dataframe tbody tr th {\n",
              "        vertical-align: top;\n",
              "    }\n",
              "\n",
              "    .dataframe thead th {\n",
              "        text-align: right;\n",
              "    }\n",
              "</style>\n",
              "<table border=\"1\" class=\"dataframe\">\n",
              "  <thead>\n",
              "    <tr style=\"text-align: right;\">\n",
              "      <th></th>\n",
              "      <th>query</th>\n",
              "      <th>page</th>\n",
              "      <th>clicks</th>\n",
              "      <th>impressions</th>\n",
              "      <th>ctr</th>\n",
              "      <th>position</th>\n",
              "      <th>Char</th>\n",
              "      <th>Stemming</th>\n",
              "      <th>Stems Ordered by frequency</th>\n",
              "      <th>Strongest word stem</th>\n",
              "      <th>Lemmatized</th>\n",
              "      <th>Lemmas Ordered by frequency</th>\n",
              "      <th>Strongest lemma</th>\n",
              "      <th>spacy_nouns</th>\n",
              "      <th>Brand/Non-branded</th>\n",
              "    </tr>\n",
              "  </thead>\n",
              "  <tbody>\n",
              "    <tr>\n",
              "      <th>0</th>\n",
              "      <td>web archive</td>\n",
              "      <td>https://www.evemilano.com/web-archive/</td>\n",
              "      <td>200</td>\n",
              "      <td>62371</td>\n",
              "      <td>0.32%</td>\n",
              "      <td>5</td>\n",
              "      <td>11</td>\n",
              "      <td>web archiv</td>\n",
              "      <td>web archiv</td>\n",
              "      <td>web</td>\n",
              "      <td>web archive</td>\n",
              "      <td>web archive</td>\n",
              "      <td>web</td>\n",
              "      <td>web</td>\n",
              "      <td>Non-branded</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>1</th>\n",
              "      <td>proxy</td>\n",
              "      <td>https://www.evemilano.com/proxy-server/</td>\n",
              "      <td>5</td>\n",
              "      <td>51043</td>\n",
              "      <td>0.01%</td>\n",
              "      <td>10</td>\n",
              "      <td>5</td>\n",
              "      <td>proxy</td>\n",
              "      <td>proxy</td>\n",
              "      <td>proxy</td>\n",
              "      <td>proxy</td>\n",
              "      <td>proxy</td>\n",
              "      <td>proxy</td>\n",
              "      <td>proxy</td>\n",
              "      <td>Non-branded</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>2</th>\n",
              "      <td>webarchive</td>\n",
              "      <td>https://www.evemilano.com/web-archive/</td>\n",
              "      <td>88</td>\n",
              "      <td>43088</td>\n",
              "      <td>0.20%</td>\n",
              "      <td>5</td>\n",
              "      <td>10</td>\n",
              "      <td>webarc</td>\n",
              "      <td>webarc</td>\n",
              "      <td>webarc</td>\n",
              "      <td>Webarchive</td>\n",
              "      <td>Webarchive</td>\n",
              "      <td>Webarchive</td>\n",
              "      <td>webarchive</td>\n",
              "      <td>Non-branded</td>\n",
              "    </tr>\n",
              "  </tbody>\n",
              "</table>\n",
              "</div>"
            ],
            "text/plain": [
              "         query                                     page  clicks  impressions  \\\n",
              "0  web archive   https://www.evemilano.com/web-archive/     200        62371   \n",
              "1        proxy  https://www.evemilano.com/proxy-server/       5        51043   \n",
              "2   webarchive   https://www.evemilano.com/web-archive/      88        43088   \n",
              "\n",
              "    ctr  position  Char    Stemming Stems Ordered by frequency  \\\n",
              "0 0.32%         5    11  web archiv                 web archiv   \n",
              "1 0.01%        10     5       proxy                      proxy   \n",
              "2 0.20%         5    10      webarc                     webarc   \n",
              "\n",
              "  Strongest word stem   Lemmatized Lemmas Ordered by frequency  \\\n",
              "0                 web  web archive                 web archive   \n",
              "1               proxy        proxy                       proxy   \n",
              "2              webarc   Webarchive                  Webarchive   \n",
              "\n",
              "  Strongest lemma spacy_nouns Brand/Non-branded  \n",
              "0             web         web       Non-branded  \n",
              "1           proxy       proxy       Non-branded  \n",
              "2      Webarchive  webarchive       Non-branded  "
            ]
          },
          "execution_count": 246,
          "metadata": {},
          "output_type": "execute_result"
        }
      ],
      "source": [
        "# Applico filtri al dataframe nobrand\n",
        "##########################################\n",
        "# rimuovo le query deboli\n",
        "# formattazione position\n",
        "# opzioni impostate a inizio script position e impressions\n",
        "#df_new = df_nobrand.loc[(raw_df['Weighted Avg Position'] <= max_pos) & (raw_df['impressions'] >= min_imp),:]\n",
        "df_new = df_nobrand.loc[(raw_df['weighted avg position'] <= max_pos) & (raw_df['impressions'] >= min_imp),:].copy()\n",
        "\n",
        "# Rimuovi il simbolo di percentuale e converti in float, poi in int\n",
        "df_new['weighted avg position'] = df_new['weighted avg position'].astype(int)\n",
        "\n",
        "# rinomina colonna position\n",
        "df_new = df_new.rename(columns={'weighted avg position': 'position'})\n",
        "\n",
        "# ordino i dati per impressioni e click\n",
        "df_new = df_new.sort_values(by=['impressions', 'clicks'],ascending=False)\n",
        "\n",
        "if 'match_queries' in df_new.columns:\n",
        "    df_new = df_new.drop(columns=['match_queries'])\n",
        "\n",
        "# Stampa la somma totale dei clicks e delle impressions\n",
        "total_clicks = df_new['clicks'].sum()\n",
        "total_impressions = df_new['impressions'].sum()\n",
        "\n",
        "print(\"Somma totale dei clicks:\", total_clicks)\n",
        "print(\"Somma totale delle impressions:\", total_impressions)\n",
        "\n",
        "print(df_new.shape[0])\n",
        "df_new.head(3)"
      ]
    },
    {
      "cell_type": "code",
      "execution_count": 247,
      "metadata": {},
      "outputs": [
        {
          "data": {
            "text/html": [
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              "        vertical-align: top;\n",
              "    }\n",
              "\n",
              "    .dataframe thead th {\n",
              "        text-align: right;\n",
              "    }\n",
              "</style>\n",
              "<table border=\"1\" class=\"dataframe\">\n",
              "  <thead>\n",
              "    <tr style=\"text-align: right;\">\n",
              "      <th></th>\n",
              "      <th>query</th>\n",
              "      <th>page</th>\n",
              "      <th>clicks</th>\n",
              "      <th>impressions</th>\n",
              "      <th>ctr</th>\n",
              "      <th>position</th>\n",
              "      <th>Char</th>\n",
              "      <th>Stemming</th>\n",
              "      <th>Stems Ordered by frequency</th>\n",
              "      <th>Strongest word stem</th>\n",
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              "      <th>Lemmas Ordered by frequency</th>\n",
              "      <th>Strongest lemma</th>\n",
              "      <th>spacy_nouns</th>\n",
              "      <th>Brand/Non-branded</th>\n",
              "      <th>website_avg_ctr_by_pos</th>\n",
              "      <th>comparison</th>\n",
              "    </tr>\n",
              "  </thead>\n",
              "  <tbody>\n",
              "    <tr>\n",
              "      <th>0</th>\n",
              "      <td>web archive</td>\n",
              "      <td>https://www.evemilano.com/web-archive/</td>\n",
              "      <td>200</td>\n",
              "      <td>62371</td>\n",
              "      <td>0.32%</td>\n",
              "      <td>5</td>\n",
              "      <td>11</td>\n",
              "      <td>web archiv</td>\n",
              "      <td>web archiv</td>\n",
              "      <td>web</td>\n",
              "      <td>web archive</td>\n",
              "      <td>web archive</td>\n",
              "      <td>web</td>\n",
              "      <td>web</td>\n",
              "      <td>Non-branded</td>\n",
              "      <td>0.97%</td>\n",
              "      <td>lower</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>1</th>\n",
              "      <td>proxy</td>\n",
              "      <td>https://www.evemilano.com/proxy-server/</td>\n",
              "      <td>5</td>\n",
              "      <td>51043</td>\n",
              "      <td>0.01%</td>\n",
              "      <td>10</td>\n",
              "      <td>5</td>\n",
              "      <td>proxy</td>\n",
              "      <td>proxy</td>\n",
              "      <td>proxy</td>\n",
              "      <td>proxy</td>\n",
              "      <td>proxy</td>\n",
              "      <td>proxy</td>\n",
              "      <td>proxy</td>\n",
              "      <td>Non-branded</td>\n",
              "      <td>0.30%</td>\n",
              "      <td>lower</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>2</th>\n",
              "      <td>webarchive</td>\n",
              "      <td>https://www.evemilano.com/web-archive/</td>\n",
              "      <td>88</td>\n",
              "      <td>43088</td>\n",
              "      <td>0.20%</td>\n",
              "      <td>5</td>\n",
              "      <td>10</td>\n",
              "      <td>webarc</td>\n",
              "      <td>webarc</td>\n",
              "      <td>webarc</td>\n",
              "      <td>Webarchive</td>\n",
              "      <td>Webarchive</td>\n",
              "      <td>Webarchive</td>\n",
              "      <td>webarchive</td>\n",
              "      <td>Non-branded</td>\n",
              "      <td>0.97%</td>\n",
              "      <td>lower</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>3</th>\n",
              "      <td>indirizzo ip</td>\n",
              "      <td>https://www.evemilano.com/come-trovare-indiriz...</td>\n",
              "      <td>28</td>\n",
              "      <td>41172</td>\n",
              "      <td>0.07%</td>\n",
              "      <td>3</td>\n",
              "      <td>12</td>\n",
              "      <td>indirizz ip</td>\n",
              "      <td>ip indirizz</td>\n",
              "      <td>ip</td>\n",
              "      <td>indirizzo ip</td>\n",
              "      <td>ip indirizzo</td>\n",
              "      <td>ip</td>\n",
              "      <td>indirizzo ip</td>\n",
              "      <td>Non-branded</td>\n",
              "      <td>4.12%</td>\n",
              "      <td>lower</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>4</th>\n",
              "      <td>gdpr acronimo</td>\n",
              "      <td>https://www.evemilano.com/gdpr/</td>\n",
              "      <td>26</td>\n",
              "      <td>32356</td>\n",
              "      <td>0.08%</td>\n",
              "      <td>8</td>\n",
              "      <td>13</td>\n",
              "      <td>gdpr acronim</td>\n",
              "      <td>gdpr acronim</td>\n",
              "      <td>gdpr</td>\n",
              "      <td>gdpr acronimo</td>\n",
              "      <td>gdpr acronimo</td>\n",
              "      <td>gdpr</td>\n",
              "      <td>gdpr</td>\n",
              "      <td>Non-branded</td>\n",
              "      <td>0.27%</td>\n",
              "      <td>lower</td>\n",
              "    </tr>\n",
              "  </tbody>\n",
              "</table>\n",
              "</div>"
            ],
            "text/plain": [
              "           query                                               page  clicks  \\\n",
              "0    web archive             https://www.evemilano.com/web-archive/     200   \n",
              "1          proxy            https://www.evemilano.com/proxy-server/       5   \n",
              "2     webarchive             https://www.evemilano.com/web-archive/      88   \n",
              "3   indirizzo ip  https://www.evemilano.com/come-trovare-indiriz...      28   \n",
              "4  gdpr acronimo                    https://www.evemilano.com/gdpr/      26   \n",
              "\n",
              "   impressions   ctr  position  Char      Stemming Stems Ordered by frequency  \\\n",
              "0        62371 0.32%         5    11    web archiv                 web archiv   \n",
              "1        51043 0.01%        10     5         proxy                      proxy   \n",
              "2        43088 0.20%         5    10        webarc                     webarc   \n",
              "3        41172 0.07%         3    12   indirizz ip                ip indirizz   \n",
              "4        32356 0.08%         8    13  gdpr acronim               gdpr acronim   \n",
              "\n",
              "  Strongest word stem     Lemmatized Lemmas Ordered by frequency  \\\n",
              "0                 web    web archive                 web archive   \n",
              "1               proxy          proxy                       proxy   \n",
              "2              webarc     Webarchive                  Webarchive   \n",
              "3                  ip   indirizzo ip                ip indirizzo   \n",
              "4                gdpr  gdpr acronimo               gdpr acronimo   \n",
              "\n",
              "  Strongest lemma   spacy_nouns Brand/Non-branded  website_avg_ctr_by_pos  \\\n",
              "0             web           web       Non-branded                   0.97%   \n",
              "1           proxy         proxy       Non-branded                   0.30%   \n",
              "2      Webarchive    webarchive       Non-branded                   0.97%   \n",
              "3              ip  indirizzo ip       Non-branded                   4.12%   \n",
              "4            gdpr          gdpr       Non-branded                   0.27%   \n",
              "\n",
              "  comparison  \n",
              "0      lower  \n",
              "1      lower  \n",
              "2      lower  \n",
              "3      lower  \n",
              "4      lower  "
            ]
          },
          "execution_count": 247,
          "metadata": {},
          "output_type": "execute_result"
        }
      ],
      "source": [
        "# implementa colonna avg_ctr_by_pos e comparison\n",
        "##################################################\n",
        "\n",
        "# Assicurati che 'position' in df_new e 'position' in query_analysis siano dello stesso tipo di dati\n",
        "df_new['position'] = df_new['position'].astype(int)\n",
        "query_analysis['position'] = query_analysis['position'].astype(int)\n",
        "\n",
        "# Crea un dizionario per il mapping da query_analysis\n",
        "ctr_mapping = dict(zip(query_analysis['position'], query_analysis['website_avg_ctr_by_pos']))\n",
        "\n",
        "merged_df=df_new.copy()\n",
        "# Applica il mapping per ottenere 'wwebsite_avg_ctr_by_pos' in df_new\n",
        "merged_df['website_avg_ctr_by_pos'] = merged_df['position'].map(ctr_mapping)\n",
        "\n",
        "# Applica la funzione a ciascuna riga per creare la colonna 'comparison'\n",
        "merged_df['comparison'] = merged_df.apply(compare_ctr, axis=1)\n",
        "\n",
        "# Visualizza il DataFrame aggiornato\n",
        "merged_df.head()\n"
      ]
    },
    {
      "cell_type": "code",
      "execution_count": 248,
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "eHGrdA_KmkpZ",
        "outputId": "f7f3a367-71bd-4a71-efcb-c53da4b033f9"
      },
      "outputs": [
        {
          "name": "stdout",
          "output_type": "stream",
          "text": [
            "6847\n"
          ]
        },
        {
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              "    </tr>\n",
              "  </thead>\n",
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              "      <th>0</th>\n",
              "      <td>web archive</td>\n",
              "      <td>https://www.evemilano.com/web-archive/</td>\n",
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              "      <td>62371</td>\n",
              "      <td>0.32%</td>\n",
              "      <td>5</td>\n",
              "      <td>11</td>\n",
              "      <td>web archiv</td>\n",
              "      <td>web archiv</td>\n",
              "      <td>web</td>\n",
              "      <td>web archive</td>\n",
              "      <td>web archive</td>\n",
              "      <td>web</td>\n",
              "      <td>web</td>\n",
              "      <td>Non-branded</td>\n",
              "      <td>0.97%</td>\n",
              "      <td>lower</td>\n",
              "      <td>[web, archive]</td>\n",
              "    </tr>\n",
              "  </tbody>\n",
              "</table>\n",
              "</div>"
            ],
            "text/plain": [
              "         query                                    page  clicks  impressions  \\\n",
              "0  web archive  https://www.evemilano.com/web-archive/     200        62371   \n",
              "\n",
              "    ctr  position  Char    Stemming Stems Ordered by frequency  \\\n",
              "0 0.32%         5    11  web archiv                 web archiv   \n",
              "\n",
              "  Strongest word stem   Lemmatized Lemmas Ordered by frequency  \\\n",
              "0                 web  web archive                 web archive   \n",
              "\n",
              "  Strongest lemma spacy_nouns Brand/Non-branded  website_avg_ctr_by_pos  \\\n",
              "0             web         web       Non-branded                   0.97%   \n",
              "\n",
              "  comparison termini_singoli  \n",
              "0      lower  [web, archive]  "
            ]
          },
          "execution_count": 248,
          "metadata": {},
          "output_type": "execute_result"
        }
      ],
      "source": [
        "# nuova colonna con termini singoli\n",
        "# crea una copia\n",
        "merged_df2 = merged_df.copy()\n",
        "# creare una nuova colonna che contiene solo i termini singoli di ciascuna riga, senza stopword\n",
        "merged_df2[\"termini_singoli\"] = merged_df2[\"query\"].str.split()\n",
        "# rimuovi stopwords\n",
        "merged_df2[\"termini_singoli\"] = merged_df2[\"termini_singoli\"].apply(lambda x: [term for term in x if term not in stopwords])\n",
        "print(merged_df2.shape[0])\n",
        "merged_df2.head(1)"
      ]
    },
    {
      "cell_type": "code",
      "execution_count": 249,
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "VRDu8fjLf-4q",
        "outputId": "0fa8a567-6e8a-4d5f-f530-3dfd1017cc54"
      },
      "outputs": [
        {
          "name": "stderr",
          "output_type": "stream",
          "text": [
            "100%|██████████| 6847/6847 [00:00<00:00, 377456.49it/s]\n"
          ]
        },
        {
          "name": "stdout",
          "output_type": "stream",
          "text": [
            "Single keywords: ['web', 'archive', 'proxy', 'webarchive', 'indirizzo', 'ip', 'gdpr', 'acronimo', 'consulenza', 'seo', 'agenzia', 'seo', 'gdpr', 'significato', 'regex', 'posizionamento', 'siti', 'web', 'kpi', 'significato', 'servizi', 'seo', 'consulente', 'seo', 'proxy', 'server', 'consulente', 'web', 'marketing', 'motori', 'ricerca', 'usati', 'seo', 'copywriting', 'regular', 'expression', 'consulenza', 'web', 'marketing', 'seo', 'audit', 'server', 'proxy', 'motori', 'ricerca', 'pubblicità', 'google', 'consulenza', 'seo', 'agenzia', 'seo', 'proxy', 'significato', 'consulente', 'google', 'ads', 'certbot', 'preventivo', 'seo', 'consulente', 'seo', 'milano', 'link', 'building', 'my', 'business', 'consulente', 'web', 'audit', 'seo', 'ipv4', 'adsense', 'dns', 'posizionamento', 'siti', 'consulenza', 'adwords', 'consulente', 'adwords', 'consulenza', 'google', 'ads', 'posizionamento', 'siti', 'internet', 'protocollo', 'http', \"l'indirizzo\", 'sito', 'redirect', 'agenzia', 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'200', 'preconnect', 'vs', 'dns-prefetch', 'spazio', 'archiviazione', 'online', 'gratis', 'ppc', 'google', 'ads', 'trasferire', 'dominio', 'wordpress', 'google', 'ads', 'cpa', 'regex', 'lettere', 'accentate', 'sitemap', 'seo', 'eliminare', 'spazi', 'vuoti', 'cella', 'excel', 'seo', 'quando', 'fare', 'campagne', 'ads', 'https://topvisor.com/support/rankings/tracker/compare/', 'corsi', 'seo', 'aziendali', 'consulenza', 'facebook', 'ads', 'milano', 'campagna', 'google', 'gdpr', 'cos', 'confrontare', 'due', 'pdf', 'campagne', 'marketing', 'google', 'ads', 'analisi', 'web', 'online', 'apparire', 'google', 'maps', 'gratis', 'google', 'sitemap', 'rimuovere', 'url', 'ricerca', 'google', 'httrack', 'agenzia', 'wordpress', 'milano', 'internet', 'archive', 'search', 'maps', 'google', 'esempi', 'copywriting', 'social', 'network', 'wordpress', 'pay', 'to', 'click', 'giuda', 'seo', '2019', 'gestione', 'adwords', 'e-shop', 'generar', 'sitemap', 'prestashop', 'quando', 'ottimizzi', 'campagna', 'sem,', 'parole', 'chiave', 'corrispondenza', 'inversa', '_________', 'annunci', 'utenti', 'effettuano', 'ricerche', 'pertinenti', 'attività.', 'specialisti', 'seo', 'milano', 'wordpress', 'aggiornamenti', 'automatici', 'consulente', 'pubblicità', 'online', 'servizi', 'webmaster', 'campagna', 'search', 'primo', 'secondo', 'terzo', 'google', 'search', 'quality', 'evaluator', 'guidelines', 'seo', 'maintenance', 'blog', 'web', 'marketing', 'seo', 'google', 'assistenza', 'https://topvisor.com/support/rankings/se/lang/', 'professionista', 'seo', 'milano', 'indirizzo', 'sito', 'web', 'sito', 'wordpress', 'appare', 'google', 'motore', 'ricerca', 'google', 'pagina', '“serp', '(search', 'engine', 'results', 'page)”', 'è:', 'google', 'search', 'console', 'seo', 'sem', 'root', 'seo', 'google', 'alert', 'funziona', 'link', 'canonico', 'cosa', 'serve', 'google', 'seo', 'search', 'marketing', 'strategie', 'seo', 'aziende', 'studi', 'professionali', 'certificato', 'google', 'adwords']\n",
            "Recurrence of keywords: [('seo', 1157), ('google', 1104), ('web', 445), ('sito', 378), ('wordpress', 353), ('milano', 288), ('ads', 278), ('ricerca', 264), ('adwords', 243), ('agenzia', 214), ('marketing', 201), ('corso', 190), ('consulente', 166), ('consulenza', 161), ('excel', 148), (\"cos'è\", 145), ('online', 139), ('motori', 135), ('dominio', 130), ('posizionamento', 124), ('analisi', 121), ('ip', 119), ('cosa', 116), ('siti', 107), ('link', 104), ('campagne', 103), ('html', 103), ('hosting', 101), ('chiave', 101), ('pubblicità', 96), ('tag', 92), ('parole', 91), ('eliminare', 89), ('indirizzo', 84), ('search', 81), ('significato', 80), ('gratis', 80), ('proxy', 79), ('internet', 78), ('url', 77), ('blog', 76), ('servizi', 74), ('http', 67), ('cloud', 66), ('analytics', 65), ('meta', 65), ('server', 64), ('gestione', 64), ('kpi', 63), ('costo', 62), ('redirect', 58), ('spazi', 58), ('ppc', 58), ('audit', 57), ('dns', 57), ('copywriting', 56), ('business', 56), ('corsi', 56), ('campagna', 56), ('click', 52), ('sitemap', 52), ('cms', 51), ('indicizzazione', 50), ('my', 49), ('guida', 49), ('png', 49), ('webmaster', 48), ('livello', 46), ('pay', 45), ('motore', 45), ('python', 45), ('costi', 45), ('jpg', 45), ('frog', 43), ('immagini', 43), ('cos', 43), ('creare', 43), ('vs', 42), ('prestashop', 41), ('ecommerce', 40), ('magento', 40), ('cancellare', 39), ('screaming', 39), ('file', 39), ('chrome', 38), ('console', 37), ('trovare', 37), ('ottimizzazione', 37), ('esempio', 36), ('indicizzare', 36), ('robots', 35), ('sem', 35), ('migliori', 35), ('gdpr', 34), ('strumenti', 33), ('app', 33), ('noindex', 33), ('costa', 33), ('esperto', 32), ('miglior', 32), ('to', 32), ('ipv4', 31), ('ipv6', 31), ('webp', 31), ('certificazione', 31), ('free', 30), ('fare', 30), ('funnel', 30), ('advertising', 30), ('esempi', 30), ('no', 29), ('rimuovere', 29), ('servizio', 28), ('pagina', 28), ('copywriter', 28), ('annunci', 28), ('facebook', 28), ('cronologia', 27), ('dati', 27), ('cpa', 27), ('local', 27), ('funziona', 27), ('spazio', 27), ('prezzi', 26), ('domini', 26), ('page', 26), ('togliere', 26), ('migliore', 26), ('javascript', 26), ('agenzie', 25), ('remarketing', 25), ('testo', 25), ('cella', 25), ('aziendale', 24), ('test', 24), ('foto', 24), ('log', 24), ('canonical', 23), ('primo', 23), ('significa', 23), ('mobile', 23), ('posizionare', 23), ('gratuito', 23), ('italiano', 23), ('como', 23), ('archive', 22), ('building', 22), ('adsense', 22), ('content', 22), ('txt', 22), ('robots.txt', 22), ('lugano', 22), ('regex', 21), ('preventivo', 21), ('manager', 21), ('img', 21), ('header', 21), ('keyword', 21), ('htaccess', 21), ('aruba', 21), ('performance', 21), ('caratteri', 21), ('aziendali', 20), ('backlink', 20), ('rel', 20), ('index', 20), ('ubuntu', 20), ('defer', 19), ('traffico', 19), ('verifica', 19), ('digital', 19), ('rimozione', 19), ('pagerank', 18), ('strutturati', 18), ('agent', 18), ('register.it', 18), ('serve', 18), ('storage', 18), ('cache', 18), ('agency', 18), ('pubblicitarie', 18), ('404', 18), ('corrispondenza', 18), ('trasferire', 18), ('italia', 18), ('certificato', 18), ('src', 17), ('sistrix', 17), ('competitor', 17), ('cdn', 17), ('register', 17), ('avanzato', 17), ('secondo', 17), ('migrazione', 17), ('user', 17), ('jquery', 17), ('hreflang', 17), ('pwa', 17), ('alternative', 17), ('assistenza', 17), ('partner', 17), ('prezzo', 17), ('status', 17), ('guide', 17), ('terzo', 16), ('text', 16), ('create', 16), ('nofollow', 16), ('progressive', 16), ('alt', 16), ('disallow', 16), ('rete', 16), ('quality', 16), ('archiviazione', 16), ('carattere', 16), ('aziende', 16), ('contenuti', 16), ('banner', 16), ('trova', 15), ('xml', 15), ('virtual', 15), ('301', 15), ('budget', 15), ('noopener', 15), ('nginx', 15), ('base', 15), ('aumentare', 15), ('differenza', 15), ('site', 15), ('pdf', 15), ('guadagnare', 15), ('acronimo', 14), (\"l'indirizzo\", 14), ('environment', 14), ('apache', 14), ('sviluppo', 14), ('locale', 14), ('database', 14), ('scheda', 14), ('for', 14), ('mcc', 13), ('googlebot', 13), ('crawler', 13), ('stress', 13), ('schema', 13), ('e-commerce', 13), ('csv', 13), ('rewrite', 13), ('shopify', 13), ('elenco', 13), ('code', 13), ('scegliere', 13), ('display', 13), ('what', 13), ('is', 13), ('editor', 13), ('cellulari', 13), ('principali', 12), ('utf-8', 12), ('inglese', 12), ('ssh', 12), ('key', 12), ('pagine', 12), ('title', 12), ('commenti', 12), ('plugin', 12), ('2', 12), ('multilingua', 12), ('fail2ban', 11), ('professionale', 11), ('elimina', 11), ('annulla', 11), ('ottimizzare', 11), ('rank', 11), ('competitors', 11), ('progetto', 11), ('codice', 11), ('ranking', 11), ('dsa', 11), ('drupal', 11), ('social', 11), ('network', 11), ('immagine', 11), ('tool', 11), ('php', 11), ('formula', 11), ('pubblicitari', 11), ('due', 11), ('css', 11), ('italiani', 11), ('venv', 10), ('target', 10), ('noreferrer', 10), ('cerca', 10), ('certificata', 10), 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('linguaggio', 1), ('internetarchive', 1), ('arch', 1), ('elaborato', 1), ('correttamente', 1), ('context', 1), ('query.', 1), ('src=url', 1), ('percorso', 1), ('rappresentazione', 1), ('vettoriale', 1), ('contattare', 1), ('manutenzione', 1), ('visite', 1), ('venezia', 1), ('%{request_uri}', 1), ('deferred', 1), ('3.0', 1), ('zend', 1), ('mediapartners-google', 1), ('como,', 1), ('convertitore', 1), ('noreferer', 1), ('regexper', 1), ('stresstest', 1), ('match', 1), ('importa', 1), ('leguide', 1), ('http1.1', 1), ('cf7', 1), ('$', 1), ('footer', 1), ('può', 1), ('(chiamato', 1), ('crawler)?', 1), ('spocket', 1), ('https://socialcrawlytics.com/spocket/', 1), ('professionalizzanti', 1), ('calcolato', 1), ('ambito', 1), ('servono', 1), ('registrarsi', 1), ('regx', 1), ('public', 1), ('certificate', 1), ('gtmetrics', 1), ('approvazione', 1), ('us', 1), ('googlemybusiness', 1), ('specializzato', 1), ('ping', 1), ('balanced', 1), ('scorecard', 1), ('wp_options', 1), ('csr', 1), ('top', 1), ('suggerimento', 1), ('wikipedia', 1), ('web-archive', 1), ('bing', 1), ('inspector', 1), ('retriveal', 1), ('strategy', 1), ('automatico', 1), ('organici', 1), ('websrchive', 1), ('\"gdpr\"?', 1), ('.io', 1), ('windows', 1), ('risalire', 1), ('consolle', 1), ('maddaloni', 1), ('es', 1), ('anti', 1), ('technical', 1), ('accentate', 1), ('https://topvisor.com/support/rankings/tracker/compare/', 1), ('httrack', 1), ('generar', 1), ('https://topvisor.com/support/rankings/se/lang/', 1), ('appare', 1), ('“serp', 1), ('(search', 1), ('results', 1), ('page)”', 1), ('è:', 1), ('root', 1), ('studi', 1)]\n"
          ]
        },
        {
          "name": "stderr",
          "output_type": "stream",
          "text": [
            "Calcolo ricorrenze: 100%|██████████| 6847/6847 [00:00<00:00, 15900.56it/s]"
          ]
        },
        {
          "name": "stdout",
          "output_type": "stream",
          "text": [
            "6847\n"
          ]
        },
        {
          "name": "stderr",
          "output_type": "stream",
          "text": [
            "\n"
          ]
        },
        {
          "data": {
            "text/html": [
              "<div>\n",
              "<style scoped>\n",
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              "    }\n",
              "\n",
              "    .dataframe thead th {\n",
              "        text-align: right;\n",
              "    }\n",
              "</style>\n",
              "<table border=\"1\" class=\"dataframe\">\n",
              "  <thead>\n",
              "    <tr style=\"text-align: right;\">\n",
              "      <th></th>\n",
              "      <th>query</th>\n",
              "      <th>page</th>\n",
              "      <th>clicks</th>\n",
              "      <th>impressions</th>\n",
              "      <th>ctr</th>\n",
              "      <th>position</th>\n",
              "      <th>Char</th>\n",
              "      <th>Stemming</th>\n",
              "      <th>Stems Ordered by frequency</th>\n",
              "      <th>Strongest word stem</th>\n",
              "      <th>Lemmatized</th>\n",
              "      <th>Lemmas Ordered by frequency</th>\n",
              "      <th>Strongest lemma</th>\n",
              "      <th>spacy_nouns</th>\n",
              "      <th>Brand/Non-branded</th>\n",
              "      <th>website_avg_ctr_by_pos</th>\n",
              "      <th>comparison</th>\n",
              "      <th>main_query</th>\n",
              "    </tr>\n",
              "  </thead>\n",
              "  <tbody>\n",
              "    <tr>\n",
              "      <th>0</th>\n",
              "      <td>web archive</td>\n",
              "      <td>https://www.evemilano.com/web-archive/</td>\n",
              "      <td>200</td>\n",
              "      <td>62371</td>\n",
              "      <td>0.32%</td>\n",
              "      <td>5</td>\n",
              "      <td>11</td>\n",
              "      <td>web archiv</td>\n",
              "      <td>web archiv</td>\n",
              "      <td>web</td>\n",
              "      <td>web archive</td>\n",
              "      <td>web archive</td>\n",
              "      <td>web</td>\n",
              "      <td>web</td>\n",
              "      <td>Non-branded</td>\n",
              "      <td>0.97%</td>\n",
              "      <td>lower</td>\n",
              "      <td>web</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>1</th>\n",
              "      <td>proxy</td>\n",
              "      <td>https://www.evemilano.com/proxy-server/</td>\n",
              "      <td>5</td>\n",
              "      <td>51043</td>\n",
              "      <td>0.01%</td>\n",
              "      <td>10</td>\n",
              "      <td>5</td>\n",
              "      <td>proxy</td>\n",
              "      <td>proxy</td>\n",
              "      <td>proxy</td>\n",
              "      <td>proxy</td>\n",
              "      <td>proxy</td>\n",
              "      <td>proxy</td>\n",
              "      <td>proxy</td>\n",
              "      <td>Non-branded</td>\n",
              "      <td>0.30%</td>\n",
              "      <td>lower</td>\n",
              "      <td>proxy</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>2</th>\n",
              "      <td>webarchive</td>\n",
              "      <td>https://www.evemilano.com/web-archive/</td>\n",
              "      <td>88</td>\n",
              "      <td>43088</td>\n",
              "      <td>0.20%</td>\n",
              "      <td>5</td>\n",
              "      <td>10</td>\n",
              "      <td>webarc</td>\n",
              "      <td>webarc</td>\n",
              "      <td>webarc</td>\n",
              "      <td>Webarchive</td>\n",
              "      <td>Webarchive</td>\n",
              "      <td>Webarchive</td>\n",
              "      <td>webarchive</td>\n",
              "      <td>Non-branded</td>\n",
              "      <td>0.97%</td>\n",
              "      <td>lower</td>\n",
              "      <td>webarchive</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>3</th>\n",
              "      <td>indirizzo ip</td>\n",
              "      <td>https://www.evemilano.com/come-trovare-indiriz...</td>\n",
              "      <td>28</td>\n",
              "      <td>41172</td>\n",
              "      <td>0.07%</td>\n",
              "      <td>3</td>\n",
              "      <td>12</td>\n",
              "      <td>indirizz ip</td>\n",
              "      <td>ip indirizz</td>\n",
              "      <td>ip</td>\n",
              "      <td>indirizzo ip</td>\n",
              "      <td>ip indirizzo</td>\n",
              "      <td>ip</td>\n",
              "      <td>indirizzo ip</td>\n",
              "      <td>Non-branded</td>\n",
              "      <td>4.12%</td>\n",
              "      <td>lower</td>\n",
              "      <td>ip</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>4</th>\n",
              "      <td>gdpr acronimo</td>\n",
              "      <td>https://www.evemilano.com/gdpr/</td>\n",
              "      <td>26</td>\n",
              "      <td>32356</td>\n",
              "      <td>0.08%</td>\n",
              "      <td>8</td>\n",
              "      <td>13</td>\n",
              "      <td>gdpr acronim</td>\n",
              "      <td>gdpr acronim</td>\n",
              "      <td>gdpr</td>\n",
              "      <td>gdpr acronimo</td>\n",
              "      <td>gdpr acronimo</td>\n",
              "      <td>gdpr</td>\n",
              "      <td>gdpr</td>\n",
              "      <td>Non-branded</td>\n",
              "      <td>0.27%</td>\n",
              "      <td>lower</td>\n",
              "      <td>gdpr</td>\n",
              "    </tr>\n",
              "  </tbody>\n",
              "</table>\n",
              "</div>"
            ],
            "text/plain": [
              "           query                                               page  clicks  \\\n",
              "0    web archive             https://www.evemilano.com/web-archive/     200   \n",
              "1          proxy            https://www.evemilano.com/proxy-server/       5   \n",
              "2     webarchive             https://www.evemilano.com/web-archive/      88   \n",
              "3   indirizzo ip  https://www.evemilano.com/come-trovare-indiriz...      28   \n",
              "4  gdpr acronimo                    https://www.evemilano.com/gdpr/      26   \n",
              "\n",
              "   impressions   ctr  position  Char      Stemming Stems Ordered by frequency  \\\n",
              "0        62371 0.32%         5    11    web archiv                 web archiv   \n",
              "1        51043 0.01%        10     5         proxy                      proxy   \n",
              "2        43088 0.20%         5    10        webarc                     webarc   \n",
              "3        41172 0.07%         3    12   indirizz ip                ip indirizz   \n",
              "4        32356 0.08%         8    13  gdpr acronim               gdpr acronim   \n",
              "\n",
              "  Strongest word stem     Lemmatized Lemmas Ordered by frequency  \\\n",
              "0                 web    web archive                 web archive   \n",
              "1               proxy          proxy                       proxy   \n",
              "2              webarc     Webarchive                  Webarchive   \n",
              "3                  ip   indirizzo ip                ip indirizzo   \n",
              "4                gdpr  gdpr acronimo               gdpr acronimo   \n",
              "\n",
              "  Strongest lemma   spacy_nouns Brand/Non-branded  website_avg_ctr_by_pos  \\\n",
              "0             web           web       Non-branded                   0.97%   \n",
              "1           proxy         proxy       Non-branded                   0.30%   \n",
              "2      Webarchive    webarchive       Non-branded                   0.97%   \n",
              "3              ip  indirizzo ip       Non-branded                   4.12%   \n",
              "4            gdpr          gdpr       Non-branded                   0.27%   \n",
              "\n",
              "  comparison  main_query  \n",
              "0      lower         web  \n",
              "1      lower       proxy  \n",
              "2      lower  webarchive  \n",
              "3      lower          ip  \n",
              "4      lower        gdpr  "
            ]
          },
          "execution_count": 249,
          "metadata": {},
          "output_type": "execute_result"
        }
      ],
      "source": [
        "# CALCOLO DEI TERMINI PIU FREQUENTI #\n",
        "#####################################\n",
        "merged_df3 = pd.DataFrame()\n",
        "merged_df3 = merged_df2.copy()\n",
        "# Crea una lista vuota per inserire i termini singoli\n",
        "terms = []\n",
        "# Itera su ogni riga della colonna \"termini_singoli\"\n",
        "for row in tqdm(merged_df3['termini_singoli']):\n",
        "    # Estrae tutti gli elementi della lista\n",
        "    for term in row:\n",
        "        # Aggiunge il termine alla lista\n",
        "        terms.append(term)\n",
        "print(\"Single keywords: \"+str(terms))\n",
        "# Conta quante volte ogni termine appare nella lista\n",
        "term_counts = Counter(terms)\n",
        "# Ordina i termini in base al numero di occorrenze\n",
        "sorted_terms = sorted(term_counts.items(), key=lambda x: x[1], reverse=True)\n",
        "print(\"Recurrence of keywords: \"+str(sorted_terms))\n",
        "# crea una nuova colonna nel dataframe\n",
        "merged_df3['main_query'] = None\n",
        "# Creare un dizionario di termini e frequenze\n",
        "term_freq = dict(sorted_terms)\n",
        "for index, row in tqdm(merged_df3.iterrows(), total=merged_df3.shape[0], desc=\"Calcolo ricorrenze\"):\n",
        "  terms = row['termini_singoli']\n",
        "  max_term = None\n",
        "  max_freq = 0\n",
        "  # Utilizzare il dizionario per ottenere la frequenza dei termini\n",
        "  for term in terms:\n",
        "    freq = term_freq.get(term, 0)\n",
        "    if freq > max_freq:\n",
        "      max_term = term\n",
        "      max_freq = freq\n",
        "  # crea la colonna main_query\n",
        "  merged_df3.at[index, 'main_query'] = max_term\n",
        "# cancella colonna usata per calcoli\n",
        "del merged_df3[\"termini_singoli\"]\n",
        "print(merged_df3.shape[0])\n",
        "merged_df3.head(5)"
      ]
    },
    {
      "cell_type": "code",
      "execution_count": 250,
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "_6PXLAbBAWJM",
        "outputId": "8101284e-b1be-4353-c60b-eb46c5fbf111"
      },
      "outputs": [
        {
          "name": "stdout",
          "output_type": "stream",
          "text": [
            "6847\n"
          ]
        },
        {
          "data": {
            "text/html": [
              "<div>\n",
              "<style scoped>\n",
              "    .dataframe tbody tr th:only-of-type {\n",
              "        vertical-align: middle;\n",
              "    }\n",
              "\n",
              "    .dataframe tbody tr th {\n",
              "        vertical-align: top;\n",
              "    }\n",
              "\n",
              "    .dataframe thead th {\n",
              "        text-align: right;\n",
              "    }\n",
              "</style>\n",
              "<table border=\"1\" class=\"dataframe\">\n",
              "  <thead>\n",
              "    <tr style=\"text-align: right;\">\n",
              "      <th></th>\n",
              "      <th>query</th>\n",
              "      <th>page</th>\n",
              "      <th>clicks</th>\n",
              "      <th>impressions</th>\n",
              "      <th>ctr</th>\n",
              "      <th>position</th>\n",
              "      <th>Char</th>\n",
              "      <th>Stemming</th>\n",
              "      <th>Stems Ordered by frequency</th>\n",
              "      <th>Strongest word stem</th>\n",
              "      <th>...</th>\n",
              "      <th>Strongest lemma</th>\n",
              "      <th>spacy_nouns</th>\n",
              "      <th>Brand/Non-branded</th>\n",
              "      <th>website_avg_ctr_by_pos</th>\n",
              "      <th>comparison</th>\n",
              "      <th>main_query</th>\n",
              "      <th>folder_lv1</th>\n",
              "      <th>folder_lv2</th>\n",
              "      <th>folder_lv3</th>\n",
              "      <th>folder_lv4</th>\n",
              "    </tr>\n",
              "  </thead>\n",
              "  <tbody>\n",
              "    <tr>\n",
              "      <th>0</th>\n",
              "      <td>web archive</td>\n",
              "      <td>https://www.evemilano.com/web-archive/</td>\n",
              "      <td>200</td>\n",
              "      <td>62371</td>\n",
              "      <td>0.32%</td>\n",
              "      <td>5</td>\n",
              "      <td>11</td>\n",
              "      <td>web archiv</td>\n",
              "      <td>web archiv</td>\n",
              "      <td>web</td>\n",
              "      <td>...</td>\n",
              "      <td>web</td>\n",
              "      <td>web</td>\n",
              "      <td>Non-branded</td>\n",
              "      <td>0.97%</td>\n",
              "      <td>lower</td>\n",
              "      <td>web</td>\n",
              "      <td>web-archive</td>\n",
              "      <td></td>\n",
              "      <td></td>\n",
              "      <td></td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>1</th>\n",
              "      <td>proxy</td>\n",
              "      <td>https://www.evemilano.com/proxy-server/</td>\n",
              "      <td>5</td>\n",
              "      <td>51043</td>\n",
              "      <td>0.01%</td>\n",
              "      <td>10</td>\n",
              "      <td>5</td>\n",
              "      <td>proxy</td>\n",
              "      <td>proxy</td>\n",
              "      <td>proxy</td>\n",
              "      <td>...</td>\n",
              "      <td>proxy</td>\n",
              "      <td>proxy</td>\n",
              "      <td>Non-branded</td>\n",
              "      <td>0.30%</td>\n",
              "      <td>lower</td>\n",
              "      <td>proxy</td>\n",
              "      <td>proxy-server</td>\n",
              "      <td></td>\n",
              "      <td></td>\n",
              "      <td></td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>2</th>\n",
              "      <td>webarchive</td>\n",
              "      <td>https://www.evemilano.com/web-archive/</td>\n",
              "      <td>88</td>\n",
              "      <td>43088</td>\n",
              "      <td>0.20%</td>\n",
              "      <td>5</td>\n",
              "      <td>10</td>\n",
              "      <td>webarc</td>\n",
              "      <td>webarc</td>\n",
              "      <td>webarc</td>\n",
              "      <td>...</td>\n",
              "      <td>Webarchive</td>\n",
              "      <td>webarchive</td>\n",
              "      <td>Non-branded</td>\n",
              "      <td>0.97%</td>\n",
              "      <td>lower</td>\n",
              "      <td>webarchive</td>\n",
              "      <td>web-archive</td>\n",
              "      <td></td>\n",
              "      <td></td>\n",
              "      <td></td>\n",
              "    </tr>\n",
              "  </tbody>\n",
              "</table>\n",
              "<p>3 rows × 22 columns</p>\n",
              "</div>"
            ],
            "text/plain": [
              "         query                                     page  clicks  impressions  \\\n",
              "0  web archive   https://www.evemilano.com/web-archive/     200        62371   \n",
              "1        proxy  https://www.evemilano.com/proxy-server/       5        51043   \n",
              "2   webarchive   https://www.evemilano.com/web-archive/      88        43088   \n",
              "\n",
              "    ctr  position  Char    Stemming Stems Ordered by frequency  \\\n",
              "0 0.32%         5    11  web archiv                 web archiv   \n",
              "1 0.01%        10     5       proxy                      proxy   \n",
              "2 0.20%         5    10      webarc                     webarc   \n",
              "\n",
              "  Strongest word stem  ... Strongest lemma spacy_nouns Brand/Non-branded  \\\n",
              "0                 web  ...             web         web       Non-branded   \n",
              "1               proxy  ...           proxy       proxy       Non-branded   \n",
              "2              webarc  ...      Webarchive  webarchive       Non-branded   \n",
              "\n",
              "  website_avg_ctr_by_pos comparison  main_query    folder_lv1 folder_lv2  \\\n",
              "0                  0.97%      lower         web   web-archive              \n",
              "1                  0.30%      lower       proxy  proxy-server              \n",
              "2                  0.97%      lower  webarchive   web-archive              \n",
              "\n",
              "  folder_lv3 folder_lv4  \n",
              "0                        \n",
              "1                        \n",
              "2                        \n",
              "\n",
              "[3 rows x 22 columns]"
            ]
          },
          "execution_count": 250,
          "metadata": {},
          "output_type": "execute_result"
        }
      ],
      "source": [
        "# crea 3 colonne con split URL path\n",
        "###################################\n",
        "# crea copia db\n",
        "merged_df4 = merged_df3.copy()\n",
        "# funzione per splittare url ad ogni /\n",
        "def extract_folders(url):\n",
        "    try:\n",
        "        # Utilizziamo un'espressione regolare per estrarre le cartelle logiche dall'URL\n",
        "        match = re.match(r'https?://[^/]+(/.*)', url)\n",
        "        if match:\n",
        "            path = match.group(1)\n",
        "            folders = path.split('/')\n",
        "            # Se l'URL ha meno di 3 cartelle, aggiungiamo le cartelle mancanti\n",
        "            while len(folders) < 3:\n",
        "                folders.append('')\n",
        "            # Restituiamo la lista di cartelle\n",
        "            return folders\n",
        "        else:\n",
        "            # L'URL non ha un percorso valido, restituisci una lista vuota\n",
        "            return [''] * 3\n",
        "    except:\n",
        "        # In caso di errore, restituisci una lista vuota\n",
        "        print(f\"Errore: Impossibile estrarre cartelle da {url}\")\n",
        "        return [''] * 3\n",
        "\n",
        "# Creiamo le nuove colonne del DataFrame utilizzando il metodo apply\n",
        "folders = merged_df4['page'].apply(extract_folders)\n",
        "merged_df4['folder_lv1'] = folders.apply(lambda x: x[1] if len(x) > 1 else '')\n",
        "merged_df4['folder_lv2'] = folders.apply(lambda x: x[2] if len(x) > 2 else '')\n",
        "merged_df4['folder_lv3'] = folders.apply(lambda x: x[3] if len(x) > 3 else '')\n",
        "merged_df4['folder_lv4'] = folders.apply(lambda x: x[4] if len(x) > 4 else '')\n",
        "print(merged_df4.shape[0])\n",
        "merged_df4.head(3)"
      ]
    },
    {
      "cell_type": "code",
      "execution_count": 251,
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "yyAlQdD24bSN",
        "outputId": "e9c30bcb-644f-4332-e577-78fe6fda1a23"
      },
      "outputs": [
        {
          "name": "stdout",
          "output_type": "stream",
          "text": [
            "Processing completed.847\n"
          ]
        },
        {
          "data": {
            "text/html": [
              "<div>\n",
              "<style scoped>\n",
              "    .dataframe tbody tr th:only-of-type {\n",
              "        vertical-align: middle;\n",
              "    }\n",
              "\n",
              "    .dataframe tbody tr th {\n",
              "        vertical-align: top;\n",
              "    }\n",
              "\n",
              "    .dataframe thead th {\n",
              "        text-align: right;\n",
              "    }\n",
              "</style>\n",
              "<table border=\"1\" class=\"dataframe\">\n",
              "  <thead>\n",
              "    <tr style=\"text-align: right;\">\n",
              "      <th></th>\n",
              "      <th>query</th>\n",
              "      <th>page</th>\n",
              "      <th>clicks</th>\n",
              "      <th>impressions</th>\n",
              "      <th>ctr</th>\n",
              "      <th>position</th>\n",
              "      <th>Char</th>\n",
              "      <th>Stemming</th>\n",
              "      <th>Stems Ordered by frequency</th>\n",
              "      <th>Strongest word stem</th>\n",
              "      <th>...</th>\n",
              "      <th>spacy_nouns</th>\n",
              "      <th>Brand/Non-branded</th>\n",
              "      <th>website_avg_ctr_by_pos</th>\n",
              "      <th>comparison</th>\n",
              "      <th>main_query</th>\n",
              "      <th>folder_lv1</th>\n",
              "      <th>folder_lv2</th>\n",
              "      <th>folder_lv3</th>\n",
              "      <th>folder_lv4</th>\n",
              "      <th>top_5_queries</th>\n",
              "    </tr>\n",
              "  </thead>\n",
              "  <tbody>\n",
              "    <tr>\n",
              "      <th>0</th>\n",
              "      <td>web archive</td>\n",
              "      <td>https://www.evemilano.com/web-archive/</td>\n",
              "      <td>200</td>\n",
              "      <td>62371</td>\n",
              "      <td>0.32%</td>\n",
              "      <td>5</td>\n",
              "      <td>11</td>\n",
              "      <td>web archiv</td>\n",
              "      <td>web archiv</td>\n",
              "      <td>web</td>\n",
              "      <td>...</td>\n",
              "      <td>web</td>\n",
              "      <td>Non-branded</td>\n",
              "      <td>0.97%</td>\n",
              "      <td>lower</td>\n",
              "      <td>web</td>\n",
              "      <td>web-archive</td>\n",
              "      <td></td>\n",
              "      <td></td>\n",
              "      <td></td>\n",
              "      <td>web archive, webarchive, archive web, web.arch...</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>1</th>\n",
              "      <td>proxy</td>\n",
              "      <td>https://www.evemilano.com/proxy-server/</td>\n",
              "      <td>5</td>\n",
              "      <td>51043</td>\n",
              "      <td>0.01%</td>\n",
              "      <td>10</td>\n",
              "      <td>5</td>\n",
              "      <td>proxy</td>\n",
              "      <td>proxy</td>\n",
              "      <td>proxy</td>\n",
              "      <td>...</td>\n",
              "      <td>proxy</td>\n",
              "      <td>Non-branded</td>\n",
              "      <td>0.30%</td>\n",
              "      <td>lower</td>\n",
              "      <td>proxy</td>\n",
              "      <td>proxy-server</td>\n",
              "      <td></td>\n",
              "      <td></td>\n",
              "      <td></td>\n",
              "      <td>proxy, proxy server, server proxy, proxy signi...</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>2</th>\n",
              "      <td>webarchive</td>\n",
              "      <td>https://www.evemilano.com/web-archive/</td>\n",
              "      <td>88</td>\n",
              "      <td>43088</td>\n",
              "      <td>0.20%</td>\n",
              "      <td>5</td>\n",
              "      <td>10</td>\n",
              "      <td>webarc</td>\n",
              "      <td>webarc</td>\n",
              "      <td>webarc</td>\n",
              "      <td>...</td>\n",
              "      <td>webarchive</td>\n",
              "      <td>Non-branded</td>\n",
              "      <td>0.97%</td>\n",
              "      <td>lower</td>\n",
              "      <td>webarchive</td>\n",
              "      <td>web-archive</td>\n",
              "      <td></td>\n",
              "      <td></td>\n",
              "      <td></td>\n",
              "      <td>web archive, webarchive, archive web, web.arch...</td>\n",
              "    </tr>\n",
              "  </tbody>\n",
              "</table>\n",
              "<p>3 rows × 23 columns</p>\n",
              "</div>"
            ],
            "text/plain": [
              "         query                                     page  clicks  impressions  \\\n",
              "0  web archive   https://www.evemilano.com/web-archive/     200        62371   \n",
              "1        proxy  https://www.evemilano.com/proxy-server/       5        51043   \n",
              "2   webarchive   https://www.evemilano.com/web-archive/      88        43088   \n",
              "\n",
              "    ctr  position  Char    Stemming Stems Ordered by frequency  \\\n",
              "0 0.32%         5    11  web archiv                 web archiv   \n",
              "1 0.01%        10     5       proxy                      proxy   \n",
              "2 0.20%         5    10      webarc                     webarc   \n",
              "\n",
              "  Strongest word stem  ... spacy_nouns Brand/Non-branded  \\\n",
              "0                 web  ...         web       Non-branded   \n",
              "1               proxy  ...       proxy       Non-branded   \n",
              "2              webarc  ...  webarchive       Non-branded   \n",
              "\n",
              "  website_avg_ctr_by_pos comparison  main_query    folder_lv1 folder_lv2  \\\n",
              "0                  0.97%      lower         web   web-archive              \n",
              "1                  0.30%      lower       proxy  proxy-server              \n",
              "2                  0.97%      lower  webarchive   web-archive              \n",
              "\n",
              "  folder_lv3 folder_lv4                                      top_5_queries  \n",
              "0                        web archive, webarchive, archive web, web.arch...  \n",
              "1                        proxy, proxy server, server proxy, proxy signi...  \n",
              "2                        web archive, webarchive, archive web, web.arch...  \n",
              "\n",
              "[3 rows x 23 columns]"
            ]
          },
          "execution_count": 251,
          "metadata": {},
          "output_type": "execute_result"
        }
      ],
      "source": [
        "# aggiungi colonna con 5 termini più frequenti per l'URL\n",
        "########################################################\n",
        "# copia db\n",
        "merged_df5 = merged_df4.copy()\n",
        "# crea una nuova colonna vuota\n",
        "merged_df5 = merged_df5.assign(top_5_queries='')\n",
        "\n",
        "# per ogni URL mostra le 5 parole chiave con maggiori impressioni\n",
        "df_grouped = merged_df5.groupby('page').apply(lambda x: x.nlargest(5, 'impressions')['query'].tolist())\n",
        "# crea nuova colonna top_5_queries\n",
        "merged_df5['top_5_queries'] = merged_df5['page'].map(df_grouped)\n",
        "# unisci le 5 parole chiave in una stringa separata da virgola\n",
        "\n",
        "total_rows = merged_df5.shape[0]\n",
        "for i, row in merged_df5.iterrows():\n",
        "    progress = f\"Processing row {i+1}/{total_rows}\"\n",
        "    print(progress, end='\\r')\n",
        "    merged_df5.at[i, 'top_5_queries'] = ', '.join(row['top_5_queries'])\n",
        "\n",
        "# trasforma il valore posizione in intero\n",
        "merged_df5['position'] = merged_df5['position'].astype(int)\n",
        "\n",
        "print(\"Processing completed.\")\n",
        "merged_df5.head(3)"
      ]
    },
    {
      "cell_type": "code",
      "execution_count": 252,
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "iqw-n64BqK_1",
        "outputId": "f0796b75-eb9c-45a1-bbf0-030aad2ffc7a"
      },
      "outputs": [],
      "source": [
        "# riorganizza le colonne FINAL OUTPUT\n",
        "final_df = merged_df5.copy()\n",
        "# Crea una lista delle colonne nell'ordine desiderato\n",
        "column_order = [\"query\", \"Char\", \"page\", \"clicks\", \"impressions\", \"position\", \"ctr\",\"website_avg_ctr_by_pos\", \"comparison\", \"Stems Ordered by frequency\", \"Strongest word stem\",\"Lemmatized\",\"Lemmas Ordered by frequency\",\"Strongest lemma\",\"spacy_nouns\",\"main_query\",\"top_5_queries\",\"folder_lv1\",\"folder_lv2\",\"folder_lv3\",\"Brand/Non-branded\"]\n",
        "# Utilizza il metodo reindex per riordinare le colonne del dataframe\n",
        "final_df = final_df.reindex(columns=column_order)\n",
        "#final_df.head(5)"
      ]
    },
    {
      "cell_type": "code",
      "execution_count": 253,
      "metadata": {},
      "outputs": [
        {
          "name": "stdout",
          "output_type": "stream",
          "text": [
            "Somma totale dei clicks: 24903\n",
            "Somma totale delle impressions: 3763566\n"
          ]
        },
        {
          "data": {
            "text/html": [
              "<div>\n",
              "<style scoped>\n",
              "    .dataframe tbody tr th:only-of-type {\n",
              "        vertical-align: middle;\n",
              "    }\n",
              "\n",
              "    .dataframe tbody tr th {\n",
              "        vertical-align: top;\n",
              "    }\n",
              "\n",
              "    .dataframe thead th {\n",
              "        text-align: right;\n",
              "    }\n",
              "</style>\n",
              "<table border=\"1\" class=\"dataframe\">\n",
              "  <thead>\n",
              "    <tr style=\"text-align: right;\">\n",
              "      <th></th>\n",
              "      <th>query</th>\n",
              "      <th>Char</th>\n",
              "      <th>page</th>\n",
              "      <th>clicks</th>\n",
              "      <th>impressions</th>\n",
              "      <th>position</th>\n",
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              "      <th>comparison</th>\n",
              "      <th>Stems Ordered by frequency</th>\n",
              "      <th>...</th>\n",
              "      <th>Lemmatized</th>\n",
              "      <th>Lemmas Ordered by frequency</th>\n",
              "      <th>Strongest lemma</th>\n",
              "      <th>spacy_nouns</th>\n",
              "      <th>main_query</th>\n",
              "      <th>top_5_queries</th>\n",
              "      <th>folder_lv1</th>\n",
              "      <th>folder_lv2</th>\n",
              "      <th>folder_lv3</th>\n",
              "      <th>Brand/Non-branded</th>\n",
              "    </tr>\n",
              "  </thead>\n",
              "  <tbody>\n",
              "    <tr>\n",
              "      <th>0</th>\n",
              "      <td>web archive</td>\n",
              "      <td>11</td>\n",
              "      <td>https://www.evemilano.com/web-archive/</td>\n",
              "      <td>200</td>\n",
              "      <td>62371</td>\n",
              "      <td>5</td>\n",
              "      <td>0.32%</td>\n",
              "      <td>0.97%</td>\n",
              "      <td>lower</td>\n",
              "      <td>web archiv</td>\n",
              "      <td>...</td>\n",
              "      <td>web archive</td>\n",
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              "      <td></td>\n",
              "      <td></td>\n",
              "      <td>Non-branded</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>1</th>\n",
              "      <td>proxy</td>\n",
              "      <td>5</td>\n",
              "      <td>https://www.evemilano.com/proxy-server/</td>\n",
              "      <td>5</td>\n",
              "      <td>51043</td>\n",
              "      <td>10</td>\n",
              "      <td>0.01%</td>\n",
              "      <td>0.30%</td>\n",
              "      <td>lower</td>\n",
              "      <td>proxy</td>\n",
              "      <td>...</td>\n",
              "      <td>proxy</td>\n",
              "      <td>proxy</td>\n",
              "      <td>proxy</td>\n",
              "      <td>proxy</td>\n",
              "      <td>proxy</td>\n",
              "      <td>proxy, proxy server, server proxy, proxy signi...</td>\n",
              "      <td>proxy-server</td>\n",
              "      <td></td>\n",
              "      <td></td>\n",
              "      <td>Non-branded</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>2</th>\n",
              "      <td>webarchive</td>\n",
              "      <td>10</td>\n",
              "      <td>https://www.evemilano.com/web-archive/</td>\n",
              "      <td>88</td>\n",
              "      <td>43088</td>\n",
              "      <td>5</td>\n",
              "      <td>0.20%</td>\n",
              "      <td>0.97%</td>\n",
              "      <td>lower</td>\n",
              "      <td>webarc</td>\n",
              "      <td>...</td>\n",
              "      <td>Webarchive</td>\n",
              "      <td>Webarchive</td>\n",
              "      <td>Webarchive</td>\n",
              "      <td>webarchive</td>\n",
              "      <td>webarchive</td>\n",
              "      <td>web archive, webarchive, archive web, web.arch...</td>\n",
              "      <td>web-archive</td>\n",
              "      <td></td>\n",
              "      <td></td>\n",
              "      <td>Non-branded</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>3</th>\n",
              "      <td>indirizzo ip</td>\n",
              "      <td>12</td>\n",
              "      <td>https://www.evemilano.com/come-trovare-indiriz...</td>\n",
              "      <td>28</td>\n",
              "      <td>41172</td>\n",
              "      <td>3</td>\n",
              "      <td>0.07%</td>\n",
              "      <td>4.12%</td>\n",
              "      <td>lower</td>\n",
              "      <td>ip indirizz</td>\n",
              "      <td>...</td>\n",
              "      <td>indirizzo ip</td>\n",
              "      <td>ip indirizzo</td>\n",
              "      <td>ip</td>\n",
              "      <td>indirizzo ip</td>\n",
              "      <td>ip</td>\n",
              "      <td>indirizzo ip, l'indirizzo di un sito, trova in...</td>\n",
              "      <td>come-trovare-indirizzo-ip-sito-web</td>\n",
              "      <td></td>\n",
              "      <td></td>\n",
              "      <td>Non-branded</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>4</th>\n",
              "      <td>gdpr acronimo</td>\n",
              "      <td>13</td>\n",
              "      <td>https://www.evemilano.com/gdpr/</td>\n",
              "      <td>26</td>\n",
              "      <td>32356</td>\n",
              "      <td>8</td>\n",
              "      <td>0.08%</td>\n",
              "      <td>0.27%</td>\n",
              "      <td>lower</td>\n",
              "      <td>gdpr acronim</td>\n",
              "      <td>...</td>\n",
              "      <td>gdpr acronimo</td>\n",
              "      <td>gdpr acronimo</td>\n",
              "      <td>gdpr</td>\n",
              "      <td>gdpr</td>\n",
              "      <td>gdpr</td>\n",
              "      <td>gdpr acronimo, gdpr significato, gdpr, acronim...</td>\n",
              "      <td>gdpr</td>\n",
              "      <td></td>\n",
              "      <td></td>\n",
              "      <td>Non-branded</td>\n",
              "    </tr>\n",
              "  </tbody>\n",
              "</table>\n",
              "<p>5 rows × 21 columns</p>\n",
              "</div>"
            ],
            "text/plain": [
              "           query  Char                                               page  \\\n",
              "0    web archive    11             https://www.evemilano.com/web-archive/   \n",
              "1          proxy     5            https://www.evemilano.com/proxy-server/   \n",
              "2     webarchive    10             https://www.evemilano.com/web-archive/   \n",
              "3   indirizzo ip    12  https://www.evemilano.com/come-trovare-indiriz...   \n",
              "4  gdpr acronimo    13                    https://www.evemilano.com/gdpr/   \n",
              "\n",
              "   clicks  impressions  position   ctr  website_avg_ctr_by_pos comparison  \\\n",
              "0     200        62371         5 0.32%                   0.97%      lower   \n",
              "1       5        51043        10 0.01%                   0.30%      lower   \n",
              "2      88        43088         5 0.20%                   0.97%      lower   \n",
              "3      28        41172         3 0.07%                   4.12%      lower   \n",
              "4      26        32356         8 0.08%                   0.27%      lower   \n",
              "\n",
              "  Stems Ordered by frequency  ...     Lemmatized Lemmas Ordered by frequency  \\\n",
              "0                 web archiv  ...    web archive                 web archive   \n",
              "1                      proxy  ...          proxy                       proxy   \n",
              "2                     webarc  ...     Webarchive                  Webarchive   \n",
              "3                ip indirizz  ...   indirizzo ip                ip indirizzo   \n",
              "4               gdpr acronim  ...  gdpr acronimo               gdpr acronimo   \n",
              "\n",
              "  Strongest lemma   spacy_nouns  main_query  \\\n",
              "0             web           web         web   \n",
              "1           proxy         proxy       proxy   \n",
              "2      Webarchive    webarchive  webarchive   \n",
              "3              ip  indirizzo ip          ip   \n",
              "4            gdpr          gdpr        gdpr   \n",
              "\n",
              "                                       top_5_queries  \\\n",
              "0  web archive, webarchive, archive web, web.arch...   \n",
              "1  proxy, proxy server, server proxy, proxy signi...   \n",
              "2  web archive, webarchive, archive web, web.arch...   \n",
              "3  indirizzo ip, l'indirizzo di un sito, trova in...   \n",
              "4  gdpr acronimo, gdpr significato, gdpr, acronim...   \n",
              "\n",
              "                           folder_lv1 folder_lv2 folder_lv3 Brand/Non-branded  \n",
              "0                         web-archive                             Non-branded  \n",
              "1                        proxy-server                             Non-branded  \n",
              "2                         web-archive                             Non-branded  \n",
              "3  come-trovare-indirizzo-ip-sito-web                             Non-branded  \n",
              "4                                gdpr                             Non-branded  \n",
              "\n",
              "[5 rows x 21 columns]"
            ]
          },
          "execution_count": 253,
          "metadata": {},
          "output_type": "execute_result"
        }
      ],
      "source": [
        "# Stampa la somma totale dei clicks e delle impressions\n",
        "total_clicks = final_df['clicks'].sum()\n",
        "total_impressions = final_df['impressions'].sum()\n",
        "\n",
        "print(\"Somma totale dei clicks:\", total_clicks)\n",
        "print(\"Somma totale delle impressions:\", total_impressions)\n",
        "\n",
        "final_df.head(5)"
      ]
    },
    {
      "cell_type": "code",
      "execution_count": 254,
      "metadata": {},
      "outputs": [
        {
          "data": {
            "text/html": [
              "<div>\n",
              "<style scoped>\n",
              "    .dataframe tbody tr th:only-of-type {\n",
              "        vertical-align: middle;\n",
              "    }\n",
              "\n",
              "    .dataframe tbody tr th {\n",
              "        vertical-align: top;\n",
              "    }\n",
              "\n",
              "    .dataframe thead th {\n",
              "        text-align: right;\n",
              "    }\n",
              "</style>\n",
              "<table border=\"1\" class=\"dataframe\">\n",
              "  <thead>\n",
              "    <tr style=\"text-align: right;\">\n",
              "      <th></th>\n",
              "      <th></th>\n",
              "      <th>clicks</th>\n",
              "      <th>ctr</th>\n",
              "      <th>impressions</th>\n",
              "      <th>position</th>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>query</th>\n",
              "      <th>page</th>\n",
              "      <th></th>\n",
              "      <th></th>\n",
              "      <th></th>\n",
              "      <th></th>\n",
              "    </tr>\n",
              "  </thead>\n",
              "  <tbody>\n",
              "    <tr>\n",
              "      <th>agenzia seo</th>\n",
              "      <th>https://www.evemilano.com/servizi-seo/agenzia/</th>\n",
              "      <td>2</td>\n",
              "      <td>0.01%</td>\n",
              "      <td>27130</td>\n",
              "      <td>71</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>agenzia seo</th>\n",
              "      <th>https://www.evemilano.com/</th>\n",
              "      <td>2</td>\n",
              "      <td>0.02%</td>\n",
              "      <td>11101</td>\n",
              "      <td>88</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>agenzia seo</th>\n",
              "      <th>https://www.evemilano.com/about-me/collaborazioni-agenzie/</th>\n",
              "      <td>0</td>\n",
              "      <td>0.00%</td>\n",
              "      <td>727</td>\n",
              "      <td>87</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>agenzia seo</th>\n",
              "      <th>https://www.evemilano.com/?utm_source=googlemybusiness&amp;utm_medium=referral&amp;utm_campaign=Scheda%20EVE%20Milano</th>\n",
              "      <td>0</td>\n",
              "      <td>0.00%</td>\n",
              "      <td>314</td>\n",
              "      <td>12</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>consulenza seo</th>\n",
              "      <th>https://www.evemilano.com/</th>\n",
              "      <td>0</td>\n",
              "      <td>0.00%</td>\n",
              "      <td>27454</td>\n",
              "      <td>30</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>consulenza seo</th>\n",
              "      <th>https://www.evemilano.com/servizi-seo/</th>\n",
              "      <td>0</td>\n",
              "      <td>0.00%</td>\n",
              "      <td>11301</td>\n",
              "      <td>68</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>consulenza seo</th>\n",
              "      <th>https://www.evemilano.com/?utm_source=googlemybusiness&amp;utm_medium=referral&amp;utm_campaign=Scheda%20EVE%20Milano</th>\n",
              "      <td>0</td>\n",
              "      <td>0.00%</td>\n",
              "      <td>432</td>\n",
              "      <td>16</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>consulente seo</th>\n",
              "      <th>https://www.evemilano.com/</th>\n",
              "      <td>1</td>\n",
              "      <td>0.01%</td>\n",
              "      <td>17815</td>\n",
              "      <td>78</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>consulente seo</th>\n",
              "      <th>https://www.evemilano.com/servizi-seo/</th>\n",
              "      <td>0</td>\n",
              "      <td>0.00%</td>\n",
              "      <td>4437</td>\n",
              "      <td>97</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>consulente seo</th>\n",
              "      <th>https://www.evemilano.com/?utm_source=googlemybusiness&amp;utm_medium=referral&amp;utm_campaign=Scheda%20EVE%20Milano</th>\n",
              "      <td>0</td>\n",
              "      <td>0.00%</td>\n",
              "      <td>601</td>\n",
              "      <td>16</td>\n",
              "    </tr>\n",
              "  </tbody>\n",
              "</table>\n",
              "</div>"
            ],
            "text/plain": [
              "                                                                   clicks  \\\n",
              "query          page                                                         \n",
              "agenzia seo    https://www.evemilano.com/servizi-seo/agenzia/           2   \n",
              "agenzia seo    https://www.evemilano.com/                               2   \n",
              "agenzia seo    https://www.evemilano.com/about-me/collaborazio...       0   \n",
              "agenzia seo    https://www.evemilano.com/?utm_source=googlemyb...       0   \n",
              "consulenza seo https://www.evemilano.com/                               0   \n",
              "consulenza seo https://www.evemilano.com/servizi-seo/                   0   \n",
              "consulenza seo https://www.evemilano.com/?utm_source=googlemyb...       0   \n",
              "consulente seo https://www.evemilano.com/                               1   \n",
              "consulente seo https://www.evemilano.com/servizi-seo/                   0   \n",
              "consulente seo https://www.evemilano.com/?utm_source=googlemyb...       0   \n",
              "\n",
              "                                                                    ctr  \\\n",
              "query          page                                                       \n",
              "agenzia seo    https://www.evemilano.com/servizi-seo/agenzia/     0.01%   \n",
              "agenzia seo    https://www.evemilano.com/                         0.02%   \n",
              "agenzia seo    https://www.evemilano.com/about-me/collaborazio... 0.00%   \n",
              "agenzia seo    https://www.evemilano.com/?utm_source=googlemyb... 0.00%   \n",
              "consulenza seo https://www.evemilano.com/                         0.00%   \n",
              "consulenza seo https://www.evemilano.com/servizi-seo/             0.00%   \n",
              "consulenza seo https://www.evemilano.com/?utm_source=googlemyb... 0.00%   \n",
              "consulente seo https://www.evemilano.com/                         0.01%   \n",
              "consulente seo https://www.evemilano.com/servizi-seo/             0.00%   \n",
              "consulente seo https://www.evemilano.com/?utm_source=googlemyb... 0.00%   \n",
              "\n",
              "                                                                   impressions  \\\n",
              "query          page                                                              \n",
              "agenzia seo    https://www.evemilano.com/servizi-seo/agenzia/            27130   \n",
              "agenzia seo    https://www.evemilano.com/                                11101   \n",
              "agenzia seo    https://www.evemilano.com/about-me/collaborazio...          727   \n",
              "agenzia seo    https://www.evemilano.com/?utm_source=googlemyb...          314   \n",
              "consulenza seo https://www.evemilano.com/                                27454   \n",
              "consulenza seo https://www.evemilano.com/servizi-seo/                    11301   \n",
              "consulenza seo https://www.evemilano.com/?utm_source=googlemyb...          432   \n",
              "consulente seo https://www.evemilano.com/                                17815   \n",
              "consulente seo https://www.evemilano.com/servizi-seo/                     4437   \n",
              "consulente seo https://www.evemilano.com/?utm_source=googlemyb...          601   \n",
              "\n",
              "                                                                   position  \n",
              "query          page                                                          \n",
              "agenzia seo    https://www.evemilano.com/servizi-seo/agenzia/            71  \n",
              "agenzia seo    https://www.evemilano.com/                                88  \n",
              "agenzia seo    https://www.evemilano.com/about-me/collaborazio...        87  \n",
              "agenzia seo    https://www.evemilano.com/?utm_source=googlemyb...        12  \n",
              "consulenza seo https://www.evemilano.com/                                30  \n",
              "consulenza seo https://www.evemilano.com/servizi-seo/                    68  \n",
              "consulenza seo https://www.evemilano.com/?utm_source=googlemyb...        16  \n",
              "consulente seo https://www.evemilano.com/                                78  \n",
              "consulente seo https://www.evemilano.com/servizi-seo/                    97  \n",
              "consulente seo https://www.evemilano.com/?utm_source=googlemyb...        16  "
            ]
          },
          "execution_count": 254,
          "metadata": {},
          "output_type": "execute_result"
        }
      ],
      "source": [
        "# Cannibalizzazione\n",
        "df_cann = final_df.copy()\n",
        "# Calcola la somma delle 'impressions' per ogni 'query'\n",
        "impressions_sums = df_cann.groupby('query')['impressions'].sum()\n",
        "# Crea una nuova colonna nel DataFrame per queste somme\n",
        "df_cann['impressions_sum'] = df_cann['query'].map(impressions_sums)\n",
        "# Crea la tabella pivot utilizzando anche la nuova colonna\n",
        "cann_pivot_table = df_cann.pivot_table(index=['query', 'page'], values=['clicks', 'impressions', 'ctr', 'position', 'impressions_sum'])\n",
        "# Ordina le righe in base alla somma delle 'impressions', quindi in base alle 'impressions' per pagina\n",
        "cann_pivot_table_sorted = cann_pivot_table.sort_values(['impressions_sum', 'impressions','query'], ascending=[False, False, False])\n",
        "# Filtra le righe per mostrare solo le query che appaiono almeno due volte\n",
        "cann_filtered_table = cann_pivot_table_sorted.groupby('query').filter(lambda x: len(x) > 1)\n",
        "# Imposta l'opzione 'multi_sparse' su False per ripetere query in ogni riga\n",
        "pd.set_option('display.multi_sparse', False)\n",
        "# Rimuovi la colonna 'impressions_sum'\n",
        "cann_filtered_table = cann_filtered_table.drop(columns='impressions_sum')\n",
        "# Formatta 'clicks', 'impressions', e 'position' come interi\n",
        "cann_filtered_table['clicks'] = cann_filtered_table['clicks'].astype(int)\n",
        "cann_filtered_table['impressions'] = cann_filtered_table['impressions'].astype(int)\n",
        "cann_filtered_table['position'] = cann_filtered_table['position'].astype(int)\n",
        "# Visualizza il DataFrame aggiornato\n",
        "cann_filtered_table.head(10)"
      ]
    },
    {
      "cell_type": "code",
      "execution_count": 255,
      "metadata": {},
      "outputs": [
        {
          "name": "stdout",
          "output_type": "stream",
          "text": [
            "Somma totale dei clicks: 11455\n",
            "Somma totale delle impressions: 1085891\n"
          ]
        },
        {
          "data": {
            "text/html": [
              "<div>\n",
              "<style scoped>\n",
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              "        vertical-align: middle;\n",
              "    }\n",
              "\n",
              "    .dataframe tbody tr th {\n",
              "        vertical-align: top;\n",
              "    }\n",
              "\n",
              "    .dataframe thead th {\n",
              "        text-align: right;\n",
              "    }\n",
              "</style>\n",
              "<table border=\"1\" class=\"dataframe\">\n",
              "  <thead>\n",
              "    <tr style=\"text-align: right;\">\n",
              "      <th></th>\n",
              "      <th>query</th>\n",
              "      <th>Char</th>\n",
              "      <th>page</th>\n",
              "      <th>clicks</th>\n",
              "      <th>impressions</th>\n",
              "      <th>position</th>\n",
              "      <th>ctr</th>\n",
              "    </tr>\n",
              "  </thead>\n",
              "  <tbody>\n",
              "    <tr>\n",
              "      <th>0</th>\n",
              "      <td>web archive</td>\n",
              "      <td>11</td>\n",
              "      <td>https://www.evemilano.com/web-archive/</td>\n",
              "      <td>200</td>\n",
              "      <td>62371</td>\n",
              "      <td>5</td>\n",
              "      <td>0.32%</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>1</th>\n",
              "      <td>proxy</td>\n",
              "      <td>5</td>\n",
              "      <td>https://www.evemilano.com/proxy-server/</td>\n",
              "      <td>5</td>\n",
              "      <td>51043</td>\n",
              "      <td>10</td>\n",
              "      <td>0.01%</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>2</th>\n",
              "      <td>webarchive</td>\n",
              "      <td>10</td>\n",
              "      <td>https://www.evemilano.com/web-archive/</td>\n",
              "      <td>88</td>\n",
              "      <td>43088</td>\n",
              "      <td>5</td>\n",
              "      <td>0.20%</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>3</th>\n",
              "      <td>indirizzo ip</td>\n",
              "      <td>12</td>\n",
              "      <td>https://www.evemilano.com/come-trovare-indiriz...</td>\n",
              "      <td>28</td>\n",
              "      <td>41172</td>\n",
              "      <td>3</td>\n",
              "      <td>0.07%</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>4</th>\n",
              "      <td>gdpr acronimo</td>\n",
              "      <td>13</td>\n",
              "      <td>https://www.evemilano.com/gdpr/</td>\n",
              "      <td>26</td>\n",
              "      <td>32356</td>\n",
              "      <td>8</td>\n",
              "      <td>0.08%</td>\n",
              "    </tr>\n",
              "  </tbody>\n",
              "</table>\n",
              "</div>"
            ],
            "text/plain": [
              "           query  Char                                               page  \\\n",
              "0    web archive    11             https://www.evemilano.com/web-archive/   \n",
              "1          proxy     5            https://www.evemilano.com/proxy-server/   \n",
              "2     webarchive    10             https://www.evemilano.com/web-archive/   \n",
              "3   indirizzo ip    12  https://www.evemilano.com/come-trovare-indiriz...   \n",
              "4  gdpr acronimo    13                    https://www.evemilano.com/gdpr/   \n",
              "\n",
              "   clicks  impressions  position   ctr  \n",
              "0     200        62371         5 0.32%  \n",
              "1       5        51043        10 0.01%  \n",
              "2      88        43088         5 0.20%  \n",
              "3      28        41172         3 0.07%  \n",
              "4      26        32356         8 0.08%  "
            ]
          },
          "execution_count": 255,
          "metadata": {},
          "output_type": "execute_result"
        }
      ],
      "source": [
        "# Foglio Improve, solo posizioni > 2 < 11\n",
        "df_top_improve = final_df.copy()\n",
        "df_top_improve = df_top_improve[df_top_improve['position'] >= 3]\n",
        "df_top_improve = df_top_improve[df_top_improve['position'] <= 10]\n",
        "# rimuovi colonne inutili\n",
        "df_top_improve = df_top_improve.drop(columns=['website_avg_ctr_by_pos', 'Brand/Non-branded', 'comparison', 'main_query','Strongest word stem','Stems Ordered by frequency','Lemmatized', 'Lemmas Ordered by frequency', 'folder_lv2', 'folder_lv3'])\n",
        "# Stampa la somma totale dei clicks e delle impressions\n",
        "dti_total_clicks = df_top_improve['clicks'].sum()\n",
        "dti_total_impressions = df_top_improve['impressions'].sum()\n",
        "\n",
        "print(\"Somma totale dei clicks:\", dti_total_clicks)\n",
        "print(\"Somma totale delle impressions:\", dti_total_impressions)\n",
        "df_top_improve.head(5)"
      ]
    },
    {
      "cell_type": "code",
      "execution_count": 256,
      "metadata": {
        "id": "2qG0PR2diFUs"
      },
      "outputs": [
        {
          "name": "stdout",
          "output_type": "stream",
          "text": [
            "Somma totale dei clicks: 10016\n",
            "Somma totale delle impressions: 3327854\n"
          ]
        },
        {
          "data": {
            "text/html": [
              "<div>\n",
              "<style scoped>\n",
              "    .dataframe tbody tr th:only-of-type {\n",
              "        vertical-align: middle;\n",
              "    }\n",
              "\n",
              "    .dataframe tbody tr th {\n",
              "        vertical-align: top;\n",
              "    }\n",
              "\n",
              "    .dataframe thead th {\n",
              "        text-align: right;\n",
              "    }\n",
              "</style>\n",
              "<table border=\"1\" class=\"dataframe\">\n",
              "  <thead>\n",
              "    <tr style=\"text-align: right;\">\n",
              "      <th></th>\n",
              "      <th>query</th>\n",
              "      <th>Char</th>\n",
              "      <th>page</th>\n",
              "      <th>clicks</th>\n",
              "      <th>impressions</th>\n",
              "      <th>position</th>\n",
              "      <th>ctr</th>\n",
              "    </tr>\n",
              "  </thead>\n",
              "  <tbody>\n",
              "    <tr>\n",
              "      <th>1</th>\n",
              "      <td>proxy</td>\n",
              "      <td>5</td>\n",
              "      <td>https://www.evemilano.com/proxy-server/</td>\n",
              "      <td>5</td>\n",
              "      <td>51043</td>\n",
              "      <td>10</td>\n",
              "      <td>0.01%</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>4</th>\n",
              "      <td>gdpr acronimo</td>\n",
              "      <td>13</td>\n",
              "      <td>https://www.evemilano.com/gdpr/</td>\n",
              "      <td>26</td>\n",
              "      <td>32356</td>\n",
              "      <td>8</td>\n",
              "      <td>0.08%</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>5</th>\n",
              "      <td>consulenza seo</td>\n",
              "      <td>14</td>\n",
              "      <td>https://www.evemilano.com/</td>\n",
              "      <td>0</td>\n",
              "      <td>27454</td>\n",
              "      <td>30</td>\n",
              "      <td>0.00%</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>6</th>\n",
              "      <td>agenzia seo</td>\n",
              "      <td>11</td>\n",
              "      <td>https://www.evemilano.com/servizi-seo/agenzia/</td>\n",
              "      <td>2</td>\n",
              "      <td>27130</td>\n",
              "      <td>71</td>\n",
              "      <td>0.01%</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>7</th>\n",
              "      <td>gdpr significato</td>\n",
              "      <td>16</td>\n",
              "      <td>https://www.evemilano.com/gdpr/</td>\n",
              "      <td>11</td>\n",
              "      <td>26666</td>\n",
              "      <td>8</td>\n",
              "      <td>0.04%</td>\n",
              "    </tr>\n",
              "  </tbody>\n",
              "</table>\n",
              "</div>"
            ],
            "text/plain": [
              "              query  Char                                            page  \\\n",
              "1             proxy     5         https://www.evemilano.com/proxy-server/   \n",
              "4     gdpr acronimo    13                 https://www.evemilano.com/gdpr/   \n",
              "5    consulenza seo    14                      https://www.evemilano.com/   \n",
              "6       agenzia seo    11  https://www.evemilano.com/servizi-seo/agenzia/   \n",
              "7  gdpr significato    16                 https://www.evemilano.com/gdpr/   \n",
              "\n",
              "   clicks  impressions  position   ctr  \n",
              "1       5        51043        10 0.01%  \n",
              "4      26        32356         8 0.08%  \n",
              "5       0        27454        30 0.00%  \n",
              "6       2        27130        71 0.01%  \n",
              "7      11        26666         8 0.04%  "
            ]
          },
          "execution_count": 256,
          "metadata": {},
          "output_type": "execute_result"
        }
      ],
      "source": [
        "# Foglio Improve, solo posizioni > 6\n",
        "df_improve = final_df.copy()\n",
        "df_improve = df_improve[df_improve['position'] > 5]\n",
        "# rimuovi colonne inutili\n",
        "df_improve = df_improve.drop(columns=['website_avg_ctr_by_pos', 'Brand/Non-branded', 'comparison', 'main_query','top_5_queries','Strongest word stem','Stems Ordered by frequency','Lemmatized', 'Lemmas Ordered by frequency', 'Strongest lemma','spacy_nouns','folder_lv1', 'folder_lv2', 'folder_lv3'])\n",
        "# Stampa la somma totale dei clicks e delle impressions\n",
        "total_clicks = df_improve['clicks'].sum()\n",
        "total_impressions = df_improve['impressions'].sum()\n",
        "\n",
        "print(\"Somma totale dei clicks:\", total_clicks)\n",
        "print(\"Somma totale delle impressions:\", total_impressions)\n",
        "df_improve.head(5)"
      ]
    },
    {
      "cell_type": "code",
      "execution_count": 257,
      "metadata": {},
      "outputs": [
        {
          "name": "stdout",
          "output_type": "stream",
          "text": [
            "Debug - URL: https://www.evemilano.com/web-archive/ - Debug - Include: True - Exclude: False\n",
            "{'User-Agent': 'Mozilla/5.0 (Windows NT 10.0; Win64; x64) AppleWebKit/537.36 (KHTML, like Gecko) Chrome/119.0.0.0 Safari/537.36'}\n",
            "Request 1/1 - https://www.evemilano.com/web-archive/ - Cos’è Web Archive? Scopri i suoi utilizzi pratici\n",
            "Debug - URL: https://www.evemilano.com/proxy-server/ - Debug - Include: True - Exclude: False\n"
          ]
        },
        {
          "data": {
            "text/html": [
              "<div>\n",
              "<style scoped>\n",
              "    .dataframe tbody tr th:only-of-type {\n",
              "        vertical-align: middle;\n",
              "    }\n",
              "\n",
              "    .dataframe tbody tr th {\n",
              "        vertical-align: top;\n",
              "    }\n",
              "\n",
              "    .dataframe thead th {\n",
              "        text-align: right;\n",
              "    }\n",
              "</style>\n",
              "<table border=\"1\" class=\"dataframe\">\n",
              "  <thead>\n",
              "    <tr style=\"text-align: right;\">\n",
              "      <th></th>\n",
              "      <th>query</th>\n",
              "      <th>Char</th>\n",
              "      <th>page</th>\n",
              "      <th>clicks</th>\n",
              "      <th>impressions</th>\n",
              "      <th>position</th>\n",
              "      <th>ctr</th>\n",
              "      <th>website_avg_ctr_by_pos</th>\n",
              "      <th>comparison</th>\n",
              "      <th>Strongest word stem</th>\n",
              "      <th>Strongest lemma</th>\n",
              "      <th>spacy_nouns</th>\n",
              "      <th>main_query</th>\n",
              "      <th>top_5_queries</th>\n",
              "      <th>tag title</th>\n",
              "    </tr>\n",
              "  </thead>\n",
              "  <tbody>\n",
              "    <tr>\n",
              "      <th>0</th>\n",
              "      <td>web archive</td>\n",
              "      <td>11</td>\n",
              "      <td>https://www.evemilano.com/web-archive/</td>\n",
              "      <td>200</td>\n",
              "      <td>62371</td>\n",
              "      <td>5</td>\n",
              "      <td>0.32%</td>\n",
              "      <td>0.97%</td>\n",
              "      <td>lower</td>\n",
              "      <td>web</td>\n",
              "      <td>web</td>\n",
              "      <td>web</td>\n",
              "      <td>web</td>\n",
              "      <td>web archive, webarchive, archive web, web.arch...</td>\n",
              "      <td>Cos’è Web Archive? Scopri i suoi utilizzi pratici</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>1</th>\n",
              "      <td>proxy</td>\n",
              "      <td>5</td>\n",
              "      <td>https://www.evemilano.com/proxy-server/</td>\n",
              "      <td>5</td>\n",
              "      <td>51043</td>\n",
              "      <td>10</td>\n",
              "      <td>0.01%</td>\n",
              "      <td>0.30%</td>\n",
              "      <td>lower</td>\n",
              "      <td>proxy</td>\n",
              "      <td>proxy</td>\n",
              "      <td>proxy</td>\n",
              "      <td>proxy</td>\n",
              "      <td>proxy, proxy server, server proxy, proxy signi...</td>\n",
              "      <td></td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>2</th>\n",
              "      <td>webarchive</td>\n",
              "      <td>10</td>\n",
              "      <td>https://www.evemilano.com/web-archive/</td>\n",
              "      <td>88</td>\n",
              "      <td>43088</td>\n",
              "      <td>5</td>\n",
              "      <td>0.20%</td>\n",
              "      <td>0.97%</td>\n",
              "      <td>lower</td>\n",
              "      <td>webarc</td>\n",
              "      <td>Webarchive</td>\n",
              "      <td>webarchive</td>\n",
              "      <td>webarchive</td>\n",
              "      <td>web archive, webarchive, archive web, web.arch...</td>\n",
              "      <td>Cos’è Web Archive? Scopri i suoi utilizzi pratici</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>3</th>\n",
              "      <td>indirizzo ip</td>\n",
              "      <td>12</td>\n",
              "      <td>https://www.evemilano.com/come-trovare-indiriz...</td>\n",
              "      <td>28</td>\n",
              "      <td>41172</td>\n",
              "      <td>3</td>\n",
              "      <td>0.07%</td>\n",
              "      <td>4.12%</td>\n",
              "      <td>lower</td>\n",
              "      <td>ip</td>\n",
              "      <td>ip</td>\n",
              "      <td>indirizzo ip</td>\n",
              "      <td>ip</td>\n",
              "      <td>indirizzo ip, l'indirizzo di un sito, trova in...</td>\n",
              "      <td></td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>4</th>\n",
              "      <td>gdpr acronimo</td>\n",
              "      <td>13</td>\n",
              "      <td>https://www.evemilano.com/gdpr/</td>\n",
              "      <td>26</td>\n",
              "      <td>32356</td>\n",
              "      <td>8</td>\n",
              "      <td>0.08%</td>\n",
              "      <td>0.27%</td>\n",
              "      <td>lower</td>\n",
              "      <td>gdpr</td>\n",
              "      <td>gdpr</td>\n",
              "      <td>gdpr</td>\n",
              "      <td>gdpr</td>\n",
              "      <td>gdpr acronimo, gdpr significato, gdpr, acronim...</td>\n",
              "      <td></td>\n",
              "    </tr>\n",
              "  </tbody>\n",
              "</table>\n",
              "</div>"
            ],
            "text/plain": [
              "           query  Char                                               page  \\\n",
              "0    web archive    11             https://www.evemilano.com/web-archive/   \n",
              "1          proxy     5            https://www.evemilano.com/proxy-server/   \n",
              "2     webarchive    10             https://www.evemilano.com/web-archive/   \n",
              "3   indirizzo ip    12  https://www.evemilano.com/come-trovare-indiriz...   \n",
              "4  gdpr acronimo    13                    https://www.evemilano.com/gdpr/   \n",
              "\n",
              "   clicks  impressions  position   ctr  website_avg_ctr_by_pos comparison  \\\n",
              "0     200        62371         5 0.32%                   0.97%      lower   \n",
              "1       5        51043        10 0.01%                   0.30%      lower   \n",
              "2      88        43088         5 0.20%                   0.97%      lower   \n",
              "3      28        41172         3 0.07%                   4.12%      lower   \n",
              "4      26        32356         8 0.08%                   0.27%      lower   \n",
              "\n",
              "  Strongest word stem Strongest lemma   spacy_nouns  main_query  \\\n",
              "0                 web             web           web         web   \n",
              "1               proxy           proxy         proxy       proxy   \n",
              "2              webarc      Webarchive    webarchive  webarchive   \n",
              "3                  ip              ip  indirizzo ip          ip   \n",
              "4                gdpr            gdpr          gdpr        gdpr   \n",
              "\n",
              "                                       top_5_queries  \\\n",
              "0  web archive, webarchive, archive web, web.arch...   \n",
              "1  proxy, proxy server, server proxy, proxy signi...   \n",
              "2  web archive, webarchive, archive web, web.arch...   \n",
              "3  indirizzo ip, l'indirizzo di un sito, trova in...   \n",
              "4  gdpr acronimo, gdpr significato, gdpr, acronim...   \n",
              "\n",
              "                                           tag title  \n",
              "0  Cos’è Web Archive? Scopri i suoi utilizzi pratici  \n",
              "1                                                     \n",
              "2  Cos’è Web Archive? Scopri i suoi utilizzi pratici  \n",
              "3                                                     \n",
              "4                                                     "
            ]
          },
          "execution_count": 257,
          "metadata": {},
          "output_type": "execute_result"
        }
      ],
      "source": [
        "# Funzione per ottenere un User-Agent casuale   \n",
        "def get_random_user_agent():\n",
        "    ua = UserAgent()\n",
        "    if user_agent_option == 'random':\n",
        "        return ua.random\n",
        "    elif user_agent_option == 'chrome':\n",
        "        return ua.chrome\n",
        "    elif user_agent_option == 'fixed':\n",
        "        return 'Mozilla/5.0 (Windows NT 10.0; Win64; x64) AppleWebKit/537.36 (KHTML, like Gecko) Chrome/119.0.0.0 Safari/537.36'\n",
        "    else:\n",
        "        print(\"Opzione User-Agent non valida. Utilizzo di un User-Agent casuale.\")\n",
        "        return ua.random\n",
        "    \n",
        "# Funzione per estrarre il tag title da un URL\n",
        "def extract_title(url, session):\n",
        "    headers = {'User-Agent': get_random_user_agent()}\n",
        "    try:\n",
        "        response = session.get(url, headers=headers)\n",
        "        response.raise_for_status()\n",
        "        if 'text/html' not in response.headers.get('Content-Type', ''):\n",
        "            print(f\"Skipping non-HTML content at {url}\")\n",
        "            return None\n",
        "        #soup = BeautifulSoup(response.content, 'html.parser')\n",
        "\n",
        "        try:\n",
        "            soup = BeautifulSoup(response.content, 'html.parser', from_encoding=response.encoding)\n",
        "            print(headers)\n",
        "        except Exception as e:\n",
        "            print(f\"Error Details:\")\n",
        "            print(f\"  - URL: {url}\")\n",
        "            print(f\"  - Exception Type: {type(e).__name__}\")\n",
        "            print(f\"  - Exception Message: {str(e)}\")\n",
        "            if hasattr(e, 'response') and e.response is not None:\n",
        "                print(f\"  - HTTP Status Code: {e.response.status_code}\")\n",
        "                print(f\"  - HTTP Headers: {e.response.headers}\")\n",
        "\n",
        "        title_tag = soup.find('title')\n",
        "        return title_tag.get_text().strip() if title_tag else None\n",
        "    except requests.exceptions.RequestException as e:\n",
        "        print(f\"Error accessing {url}: {e}\")\n",
        "        return None\n",
        "\n",
        "# Funzione per aggiornare raw_dfP con il tag title\n",
        "def update_raw_df_with_titles(raw_dfP, counter_max, include=\"\", exclude=\"\"):\n",
        "    # Converti le stringhe include ed exclude in liste, se non sono vuote\n",
        "    include_list = None if not include else include.split(\"|\")\n",
        "    exclude_list = exclude.split(\"|\") if exclude else None\n",
        "\n",
        "    session = requests.Session()\n",
        "    raw_dfP['tag title'] = ''\n",
        "    counter = 0\n",
        "    total_requests = min(counter_max, len(raw_dfP))  # Il minimo tra counter_max e la lunghezza di raw_dfP\n",
        "    for i, row in raw_dfP.iterrows():\n",
        "        url = row['page']\n",
        "        # Se include_list è None, ignora il filtro di inclusione\n",
        "        should_include = include_list is None or any(folder in url for folder in include_list)\n",
        "        should_exclude = exclude_list is not None and any(folder in url for folder in exclude_list)\n",
        "\n",
        "        # Aggiungi stampe di debug per verificare il processo di filtraggio\n",
        "        print(f\"Debug - URL: {url} - Debug - Include: {should_include} - Exclude: {should_exclude}\")\n",
        "\n",
        "        # Incrementa il contatore solo se l'URL rispetta i criteri di include ed exclude\n",
        "        if should_include and not should_exclude:\n",
        "            if counter >= counter_max:\n",
        "                break\n",
        "            title = extract_title(url, session)\n",
        "            if title:\n",
        "                raw_dfP.at[i, 'tag title'] = title\n",
        "            print(f'Request {counter+1}/{total_requests} - {url} - {raw_dfP.at[i, \"tag title\"]}')\n",
        "            counter += 1\n",
        "            time.sleep(attesa)  # Rate limiting\n",
        "    session.close()\n",
        "    return raw_dfP\n",
        "\n",
        "# Funzione per eseguire il VLOOKUP-like operation\n",
        "def vlookup_titles_into_merged_df(merged_df7, raw_dfP):\n",
        "    # Creare un dizionario di URL e tag title da raw_dfP\n",
        "    title_dict = pd.Series(raw_dfP['tag title'].values, index=raw_dfP['page']).to_dict()\n",
        "    # Mappare il tag title su merged_df7 usando il dizionario\n",
        "    merged_df7['tag title'] = merged_df7['page'].map(title_dict)\n",
        "    return merged_df7\n",
        "\n",
        "# Eseguire le operazioni\n",
        "# Aggiorna raw_dfP con i tag title, passando le variabili include ed exclude\n",
        "raw_dfP = update_raw_df_with_titles(raw_dfP, counter_max, include, exclude)\n",
        "\n",
        "merged_df7= final_df.copy()\n",
        "\n",
        "# Unire i tag title in merged_df7\n",
        "merged_df7 = vlookup_titles_into_merged_df(merged_df7, raw_dfP)\n",
        "\n",
        "# rimuovi colonne\n",
        "merged_df7 = merged_df7.drop(columns=['Stems Ordered by frequency','Lemmas Ordered by frequency','Lemmatized','folder_lv1','folder_lv2','folder_lv3','Brand/Non-branded'])\n",
        "\n",
        "# Visualizzare le prime righe per confermare\n",
        "merged_df7.head()\n"
      ]
    },
    {
      "cell_type": "code",
      "execution_count": 258,
      "metadata": {},
      "outputs": [
        {
          "data": {
            "text/html": [
              "<div>\n",
              "<style scoped>\n",
              "    .dataframe tbody tr th:only-of-type {\n",
              "        vertical-align: middle;\n",
              "    }\n",
              "\n",
              "    .dataframe tbody tr th {\n",
              "        vertical-align: top;\n",
              "    }\n",
              "\n",
              "    .dataframe thead th {\n",
              "        text-align: right;\n",
              "    }\n",
              "</style>\n",
              "<table border=\"1\" class=\"dataframe\">\n",
              "  <thead>\n",
              "    <tr style=\"text-align: right;\">\n",
              "      <th></th>\n",
              "      <th>query</th>\n",
              "      <th>Char</th>\n",
              "      <th>page</th>\n",
              "      <th>clicks</th>\n",
              "      <th>impressions</th>\n",
              "      <th>position</th>\n",
              "      <th>ctr</th>\n",
              "      <th>website_avg_ctr_by_pos</th>\n",
              "      <th>comparison</th>\n",
              "      <th>Strongest word stem</th>\n",
              "      <th>Strongest lemma</th>\n",
              "      <th>spacy_nouns</th>\n",
              "      <th>main_query</th>\n",
              "      <th>top_5_queries</th>\n",
              "      <th>tag title</th>\n",
              "      <th>check</th>\n",
              "    </tr>\n",
              "  </thead>\n",
              "  <tbody>\n",
              "    <tr>\n",
              "      <th>0</th>\n",
              "      <td>web archive</td>\n",
              "      <td>11</td>\n",
              "      <td>https://www.evemilano.com/web-archive/</td>\n",
              "      <td>200</td>\n",
              "      <td>62371</td>\n",
              "      <td>5</td>\n",
              "      <td>0.32%</td>\n",
              "      <td>0.97%</td>\n",
              "      <td>lower</td>\n",
              "      <td>web</td>\n",
              "      <td>web</td>\n",
              "      <td>web</td>\n",
              "      <td>web</td>\n",
              "      <td>web archive, webarchive, archive web, web.arch...</td>\n",
              "      <td>Cos’è Web Archive? Scopri i suoi utilizzi pratici</td>\n",
              "      <td>Missing 3: web.archive, internet, webarchive</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>1</th>\n",
              "      <td>proxy</td>\n",
              "      <td>5</td>\n",
              "      <td>https://www.evemilano.com/proxy-server/</td>\n",
              "      <td>5</td>\n",
              "      <td>51043</td>\n",
              "      <td>10</td>\n",
              "      <td>0.01%</td>\n",
              "      <td>0.30%</td>\n",
              "      <td>lower</td>\n",
              "      <td>proxy</td>\n",
              "      <td>proxy</td>\n",
              "      <td>proxy</td>\n",
              "      <td>proxy</td>\n",
              "      <td>proxy, proxy server, server proxy, proxy signi...</td>\n",
              "      <td></td>\n",
              "      <td>N.A.</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>2</th>\n",
              "      <td>webarchive</td>\n",
              "      <td>10</td>\n",
              "      <td>https://www.evemilano.com/web-archive/</td>\n",
              "      <td>88</td>\n",
              "      <td>43088</td>\n",
              "      <td>5</td>\n",
              "      <td>0.20%</td>\n",
              "      <td>0.97%</td>\n",
              "      <td>lower</td>\n",
              "      <td>webarc</td>\n",
              "      <td>Webarchive</td>\n",
              "      <td>webarchive</td>\n",
              "      <td>webarchive</td>\n",
              "      <td>web archive, webarchive, archive web, web.arch...</td>\n",
              "      <td>Cos’è Web Archive? Scopri i suoi utilizzi pratici</td>\n",
              "      <td>Missing 3: web.archive, internet, webarchive</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>3</th>\n",
              "      <td>indirizzo ip</td>\n",
              "      <td>12</td>\n",
              "      <td>https://www.evemilano.com/come-trovare-indiriz...</td>\n",
              "      <td>28</td>\n",
              "      <td>41172</td>\n",
              "      <td>3</td>\n",
              "      <td>0.07%</td>\n",
              "      <td>4.12%</td>\n",
              "      <td>lower</td>\n",
              "      <td>ip</td>\n",
              "      <td>ip</td>\n",
              "      <td>indirizzo ip</td>\n",
              "      <td>ip</td>\n",
              "      <td>indirizzo ip, l'indirizzo di un sito, trova in...</td>\n",
              "      <td></td>\n",
              "      <td>N.A.</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>4</th>\n",
              "      <td>gdpr acronimo</td>\n",
              "      <td>13</td>\n",
              "      <td>https://www.evemilano.com/gdpr/</td>\n",
              "      <td>26</td>\n",
              "      <td>32356</td>\n",
              "      <td>8</td>\n",
              "      <td>0.08%</td>\n",
              "      <td>0.27%</td>\n",
              "      <td>lower</td>\n",
              "      <td>gdpr</td>\n",
              "      <td>gdpr</td>\n",
              "      <td>gdpr</td>\n",
              "      <td>gdpr</td>\n",
              "      <td>gdpr acronimo, gdpr significato, gdpr, acronim...</td>\n",
              "      <td></td>\n",
              "      <td>N.A.</td>\n",
              "    </tr>\n",
              "  </tbody>\n",
              "</table>\n",
              "</div>"
            ],
            "text/plain": [
              "           query  Char                                               page  \\\n",
              "0    web archive    11             https://www.evemilano.com/web-archive/   \n",
              "1          proxy     5            https://www.evemilano.com/proxy-server/   \n",
              "2     webarchive    10             https://www.evemilano.com/web-archive/   \n",
              "3   indirizzo ip    12  https://www.evemilano.com/come-trovare-indiriz...   \n",
              "4  gdpr acronimo    13                    https://www.evemilano.com/gdpr/   \n",
              "\n",
              "   clicks  impressions  position   ctr  website_avg_ctr_by_pos comparison  \\\n",
              "0     200        62371         5 0.32%                   0.97%      lower   \n",
              "1       5        51043        10 0.01%                   0.30%      lower   \n",
              "2      88        43088         5 0.20%                   0.97%      lower   \n",
              "3      28        41172         3 0.07%                   4.12%      lower   \n",
              "4      26        32356         8 0.08%                   0.27%      lower   \n",
              "\n",
              "  Strongest word stem Strongest lemma   spacy_nouns  main_query  \\\n",
              "0                 web             web           web         web   \n",
              "1               proxy           proxy         proxy       proxy   \n",
              "2              webarc      Webarchive    webarchive  webarchive   \n",
              "3                  ip              ip  indirizzo ip          ip   \n",
              "4                gdpr            gdpr          gdpr        gdpr   \n",
              "\n",
              "                                       top_5_queries  \\\n",
              "0  web archive, webarchive, archive web, web.arch...   \n",
              "1  proxy, proxy server, server proxy, proxy signi...   \n",
              "2  web archive, webarchive, archive web, web.arch...   \n",
              "3  indirizzo ip, l'indirizzo di un sito, trova in...   \n",
              "4  gdpr acronimo, gdpr significato, gdpr, acronim...   \n",
              "\n",
              "                                           tag title  \\\n",
              "0  Cos’è Web Archive? Scopri i suoi utilizzi pratici   \n",
              "1                                                      \n",
              "2  Cos’è Web Archive? Scopri i suoi utilizzi pratici   \n",
              "3                                                      \n",
              "4                                                      \n",
              "\n",
              "                                          check  \n",
              "0  Missing 3: web.archive, internet, webarchive  \n",
              "1                                          N.A.  \n",
              "2  Missing 3: web.archive, internet, webarchive  \n",
              "3                                          N.A.  \n",
              "4                                          N.A.  "
            ]
          },
          "execution_count": 258,
          "metadata": {},
          "output_type": "execute_result"
        }
      ],
      "source": [
        "# Funzione per verificare la presenza delle parole chiave\n",
        "def check_keywords_in_title(row):\n",
        "    # Rimuovi la punteggiatura dalle parole chiave e convertile in minuscolo, poi rimuovi le stopwords.\n",
        "    keywords = set(word.lower().strip(string.punctuation) for phrase in row['top_5_queries'].split(',') \n",
        "                   for word in phrase.lower().split() if word.lower().strip(string.punctuation) not in stopwords)\n",
        "    \n",
        "    # Rimuovi la punteggiatura dal titolo, convertilo in minuscolo e rimuovi le stopwords.\n",
        "    title_words = set(word.lower().strip(string.punctuation) for word in row['tag title'].split() \n",
        "                      if word.lower().strip(string.punctuation) not in stopwords) \\\n",
        "                  if pd.notnull(row['tag title']) else set()\n",
        "    \n",
        "    # Se il titolo è vuoto, restituisci 'N.A.'\n",
        "    if not title_words:\n",
        "        return 'N.A.'\n",
        "\n",
        "    # Trova quali parole chiave mancano nel titolo\n",
        "    missing = keywords - title_words\n",
        "\n",
        "    # Restituisci il risultato appropriato\n",
        "    if not missing:\n",
        "        return 'Ok'\n",
        "    else:\n",
        "        return f\"Missing {len(missing)}: {', '.join(missing)}\"\n",
        "\n",
        "# Applica la funzione a ciascuna riga del DataFrame e crea la colonna 'check'\n",
        "merged_df7['check'] = merged_df7.apply(check_keywords_in_title, axis=1)\n",
        "\n",
        "# Mostra le prime righe per confermare che la colonna 'check' è stata creata correttamente\n",
        "merged_df7.head()\n",
        "\n"
      ]
    },
    {
      "cell_type": "code",
      "execution_count": 259,
      "metadata": {},
      "outputs": [],
      "source": [
        "# riorganizza colonne del foglio \"Check tag title\"\n",
        "# Crea una lista delle colonne nell'ordine desiderato\n",
        "column_order = [\"query\", \"page\", \"clicks\", \"impressions\", \"position\", \"ctr\",\"website_avg_ctr_by_pos\",\"comparison\", \"main_query\",\"top_5_queries\",\"tag title\",\"check\",]\n",
        "merged_df8 = merged_df7.reindex(columns=column_order)"
      ]
    },
    {
      "cell_type": "code",
      "execution_count": 260,
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "l4p0DYQy2_Y4",
        "outputId": "7681f890-e40f-4fd5-bb8f-baf350256f5e"
      },
      "outputs": [
        {
          "data": {
            "text/html": [
              "<div>\n",
              "<style scoped>\n",
              "    .dataframe tbody tr th:only-of-type {\n",
              "        vertical-align: middle;\n",
              "    }\n",
              "\n",
              "    .dataframe tbody tr th {\n",
              "        vertical-align: top;\n",
              "    }\n",
              "\n",
              "    .dataframe thead th {\n",
              "        text-align: right;\n",
              "    }\n",
              "</style>\n",
              "<table border=\"1\" class=\"dataframe\">\n",
              "  <thead>\n",
              "    <tr style=\"text-align: right;\">\n",
              "      <th></th>\n",
              "      <th>query</th>\n",
              "      <th>page</th>\n",
              "      <th>clicks</th>\n",
              "      <th>impressions</th>\n",
              "      <th>position</th>\n",
              "      <th>ctr</th>\n",
              "      <th>website_avg_ctr_by_pos</th>\n",
              "      <th>comparison</th>\n",
              "      <th>main_query</th>\n",
              "      <th>top_5_queries</th>\n",
              "      <th>tag title</th>\n",
              "      <th>tag title len</th>\n",
              "      <th>check</th>\n",
              "    </tr>\n",
              "  </thead>\n",
              "  <tbody>\n",
              "    <tr>\n",
              "      <th>0</th>\n",
              "      <td>web archive</td>\n",
              "      <td>https://www.evemilano.com/web-archive/</td>\n",
              "      <td>200</td>\n",
              "      <td>62371</td>\n",
              "      <td>5</td>\n",
              "      <td>0.32%</td>\n",
              "      <td>0.97%</td>\n",
              "      <td>lower</td>\n",
              "      <td>web</td>\n",
              "      <td>web archive, webarchive, archive web, web.arch...</td>\n",
              "      <td>Cos’è Web Archive? Scopri i suoi utilizzi pratici</td>\n",
              "      <td>49</td>\n",
              "      <td>Missing 3: web.archive, internet, webarchive</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>1</th>\n",
              "      <td>proxy</td>\n",
              "      <td>https://www.evemilano.com/proxy-server/</td>\n",
              "      <td>5</td>\n",
              "      <td>51043</td>\n",
              "      <td>10</td>\n",
              "      <td>0.01%</td>\n",
              "      <td>0.30%</td>\n",
              "      <td>lower</td>\n",
              "      <td>proxy</td>\n",
              "      <td>proxy, proxy server, server proxy, proxy signi...</td>\n",
              "      <td></td>\n",
              "      <td>0</td>\n",
              "      <td>N.A.</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>2</th>\n",
              "      <td>webarchive</td>\n",
              "      <td>https://www.evemilano.com/web-archive/</td>\n",
              "      <td>88</td>\n",
              "      <td>43088</td>\n",
              "      <td>5</td>\n",
              "      <td>0.20%</td>\n",
              "      <td>0.97%</td>\n",
              "      <td>lower</td>\n",
              "      <td>webarchive</td>\n",
              "      <td>web archive, webarchive, archive web, web.arch...</td>\n",
              "      <td>Cos’è Web Archive? Scopri i suoi utilizzi pratici</td>\n",
              "      <td>49</td>\n",
              "      <td>Missing 3: web.archive, internet, webarchive</td>\n",
              "    </tr>\n",
              "  </tbody>\n",
              "</table>\n",
              "</div>"
            ],
            "text/plain": [
              "         query                                     page  clicks  impressions  \\\n",
              "0  web archive   https://www.evemilano.com/web-archive/     200        62371   \n",
              "1        proxy  https://www.evemilano.com/proxy-server/       5        51043   \n",
              "2   webarchive   https://www.evemilano.com/web-archive/      88        43088   \n",
              "\n",
              "   position   ctr  website_avg_ctr_by_pos comparison  main_query  \\\n",
              "0         5 0.32%                   0.97%      lower         web   \n",
              "1        10 0.01%                   0.30%      lower       proxy   \n",
              "2         5 0.20%                   0.97%      lower  webarchive   \n",
              "\n",
              "                                       top_5_queries  \\\n",
              "0  web archive, webarchive, archive web, web.arch...   \n",
              "1  proxy, proxy server, server proxy, proxy signi...   \n",
              "2  web archive, webarchive, archive web, web.arch...   \n",
              "\n",
              "                                           tag title  tag title len  \\\n",
              "0  Cos’è Web Archive? Scopri i suoi utilizzi pratici             49   \n",
              "1                                                                 0   \n",
              "2  Cos’è Web Archive? Scopri i suoi utilizzi pratici             49   \n",
              "\n",
              "                                          check  \n",
              "0  Missing 3: web.archive, internet, webarchive  \n",
              "1                                          N.A.  \n",
              "2  Missing 3: web.archive, internet, webarchive  "
            ]
          },
          "execution_count": 260,
          "metadata": {},
          "output_type": "execute_result"
        }
      ],
      "source": [
        "# conta caratteri\n",
        "# Creare la nuova colonna \"tag title length\" con la lunghezza della stringa in \"tag title\"\n",
        "merged_df8.insert(merged_df8.columns.get_loc(\"tag title\")+1, \"tag title len\", merged_df8[\"tag title\"].apply(lambda x: len(str(x))))\n",
        "merged_df8.head(3)"
      ]
    },
    {
      "cell_type": "code",
      "execution_count": 261,
      "metadata": {},
      "outputs": [],
      "source": [
        "# aggiorna openai\n",
        "if False:\n",
        "    import subprocess\n",
        "    # Comando per aggiornare il pacchetto openai\n",
        "    command = \"pip install --upgrade openai\"\n",
        "    # Esegui il comando\n",
        "    subprocess.run(command, shell=True)"
      ]
    },
    {
      "cell_type": "code",
      "execution_count": 262,
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "yppDziF_3MIP",
        "outputId": "0d438ce8-8157-409f-f7f5-741971bff6d9"
      },
      "outputs": [
        {
          "name": "stdout",
          "output_type": "stream",
          "text": [
            "Processed row 6847/6847 | 2023-12-05 21:54:49 | 269 tokens.\n",
            "Total tokens used: 269\n",
            "Actual API calls made: 1\n"
          ]
        }
      ],
      "source": [
        "# ottieni tag title da gpt\n",
        "#################################\n",
        "\n",
        "#import openai\n",
        "from dotenv import load_dotenv\n",
        "import os\n",
        "load_dotenv()  # Carica le variabili d'ambiente dal file .env\n",
        "\n",
        "from openai import OpenAI\n",
        "client = OpenAI(api_key=os.environ['openai.api_key'])\n",
        "\n",
        "# setup richiesta gtp\n",
        "merged_df8b = merged_df8.copy()\n",
        "\n",
        "# creo dizionario delle risposte di gpt per evitare chiamate doppie\n",
        "gpt_responses = {}\n",
        "# Inizializza un contatore per il numero totale di token\n",
        "total_tokens_used = 0\n",
        "# Inizializza un contatore per le chiamate API effettive\n",
        "actual_api_calls = 0\n",
        "\n",
        "def improve_tag_title(row, gpt_responses):\n",
        "    global total_tokens_used  , actual_api_calls      \n",
        "    top_5_queries = row['top_5_queries']\n",
        "\n",
        "    # Ottieni il tag title e l'URL dalla riga corrente\n",
        "    tag_title = row[\"tag title\"]\n",
        "    page_url = row[\"page\"]\n",
        "\n",
        "    # Controllo se tag_title è presente e non vuoto\n",
        "    if not tag_title:\n",
        "        return None\n",
        "\n",
        "    # Controllo per saltare la chiamata GPT quando comparison è 'greater' o check è 'Ok'\n",
        "    #if row[\"comparison\"] == \"greater\" or \"Missing\" not in row[\"check\"]:\n",
        "    #    #return row[\"tag title\"]\n",
        "    #    return None\n",
        "\n",
        "    # Verifica se l'URL è già stato processato\n",
        "    if page_url in gpt_responses:\n",
        "        return gpt_responses[page_url]  # Usa il tag title migliorato se disponibile\n",
        "\n",
        "    prompt = (      \n",
        "        f\"Sto cercando di migliorare il tag title per una pagina web. Il tag title attuale è: {tag_title}.\\n\"\n",
        "        f\"Le parole chiave più importanti e pertinenti alla pagina sono: {top_5_queries}.\\n\"\n",
        "        f\"Crea un nuovo tag title in {gpt_language} che incorpori queste parole chiave in modo naturale e coinvolgente. Il tag title dovrebbe:\\n\"\n",
        "        f\"1) avere al massimo 65 caratteri, spazi inclusi. Assicurati che la tua risposta non superi questo limite.\\n\"\n",
        "        f\"2) non includere il nome del brand.\\n\"\n",
        "        f\"3) non utilizzare lettere maiuscole inutili, simboli, apici o virgolette.\\n\"\n",
        "        f\"4) essere presentato da solo, senza alcuna spiegazione o contenuto aggiuntivo.\\n\"\n",
        "        f\"Per favore, segui scrupolosamente tutte queste regole nella tua risposta. Se non sei sicuro, conferma che hai seguito tutte le regole nel tuo messaggio.\"\n",
        "    )\n",
        "\n",
        "    try:\n",
        "        # Modifica la struttura dell'input per utilizzare il formato chat\n",
        "        #response = client.completions.create(\n",
        "        response = client.chat.completions.create(\n",
        "            model=\"gpt-4\",\n",
        "            #model=\"gpt-4-1106-preview\", # gpt4turbo\n",
        "            messages=[\n",
        "                {\"role\": \"system\", \"content\": \"Comportati come se fossi un SEO copywriter professionista.\"},\n",
        "                {\"role\": \"user\", \"content\": prompt}\n",
        "            ],\n",
        "            max_tokens=1000,\n",
        "            temperature=0.4,\n",
        "            top_p=1,\n",
        "            frequency_penalty=0.1,\n",
        "            presence_penalty=0.1\n",
        "        )\n",
        "        #print(response)\n",
        "        response = json.loads(response.model_dump_json())\n",
        "\n",
        "        # Aggiungi il numero di token utilizzati per questa risposta al totale\n",
        "        total_tokens_used += response['usage']['total_tokens'] \n",
        "        actual_api_calls += 1  # Incrementa il contatore per le chiamate API effettive\n",
        "\n",
        "    # eccezioni errori gpt\n",
        "    except Exception as e:\n",
        "        print(f\"Error occured while calling OpenAI API: {e}\")\n",
        "        return None\n",
        "\n",
        "    #improved_tag_title = response.model_dump(exclude_unset=True)\n",
        "    #improved_tag_title = response.choices[0].message.content.strip().lower()\n",
        "    #improved_tag_title = response.choices[0].message.content\n",
        "    #improved_tag_title = response.completion.choices[0].text\n",
        "    improved_tag_title = response['choices'][0]['message']['content']\n",
        "    #improved_tag_title = response.choices[0].message['content'].strip().lower()\n",
        "    \n",
        "    #gpt_responses[tag_title] = improved_tag_title\n",
        "    # modifica per usare come chiave di confronto l'URL\n",
        "    gpt_responses[page_url] = improved_tag_title\n",
        "    # SLEEP\n",
        "    time.sleep(1)\n",
        "    return improved_tag_title\n",
        "\n",
        "# chiamate API gpt\n",
        "# Dopo la definizione della funzione, esegui il loop per migliorare i tag title\n",
        "merged_df8b.reset_index(drop=True, inplace=True)\n",
        "processed_rows = 0\n",
        "\n",
        "for index, row in merged_df8b.iterrows():\n",
        "    # Passa la riga corrente e il dizionario delle risposte a improve_tag_title\n",
        "    new_tag_title = improve_tag_title(row, gpt_responses)\n",
        "\n",
        "    # Assegna il nuovo tag title alla riga corrente\n",
        "    merged_df8b.at[index, \"new tag title\"] = new_tag_title\n",
        "    # Aggiorna il dizionario gpt_responses con la risposta ricevuta\n",
        "    gpt_responses[row[\"page\"]] = new_tag_title\n",
        "    # Stampa il progresso\n",
        "    processed_rows += 1  # Incrementa il contatore di righe processate\n",
        "    print(f\"\\rProcessed row {processed_rows}/{len(merged_df8b)} | {datetime.now().strftime('%Y-%m-%d %H:%M:%S')} | {total_tokens_used} tokens.\", end=\"\", flush=True)\n",
        "\n",
        "# Aggiungi qui il nuovo blocco di codice per assicurarti di aggiornare tutte le righe\n",
        "for index, row in merged_df8b.iterrows():\n",
        "    page_url = row[\"page\"]\n",
        "    if page_url in gpt_responses:\n",
        "        merged_df8b.at[index, \"new tag title\"] = gpt_responses[page_url]\n",
        "\n",
        "# Stampa il totale dei token utilizzati\n",
        "print(f\"\\nTotal tokens used: {total_tokens_used}\")\n",
        "print(f\"Actual API calls made: {actual_api_calls}\")\n",
        "# https://platform.openai.com/account/usage"
      ]
    },
    {
      "cell_type": "code",
      "execution_count": 263,
      "metadata": {},
      "outputs": [
        {
          "name": "stdout",
          "output_type": "stream",
          "text": [
            "Somma totale dei clicks: 24903\n",
            "Somma totale delle impressions: 3763566\n"
          ]
        },
        {
          "data": {
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              "</style>\n",
              "<table border=\"1\" class=\"dataframe\">\n",
              "  <thead>\n",
              "    <tr style=\"text-align: right;\">\n",
              "      <th></th>\n",
              "      <th>query</th>\n",
              "      <th>page</th>\n",
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              "      <th>impressions</th>\n",
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              "      <th>0</th>\n",
              "      <td>web archive</td>\n",
              "      <td>https://www.evemilano.com/web-archive/</td>\n",
              "      <td>200</td>\n",
              "      <td>62371</td>\n",
              "      <td>5</td>\n",
              "      <td>0.32%</td>\n",
              "      <td>0.97%</td>\n",
              "      <td>lower</td>\n",
              "      <td>web</td>\n",
              "      <td>web archive, webarchive, archive web, web.arch...</td>\n",
              "      <td>Cos’è Web Archive? Scopri i suoi utilizzi pratici</td>\n",
              "      <td>49</td>\n",
              "      <td>Missing 3: web.archive, internet, webarchive</td>\n",
              "      <td>\"Web Archive e Webarchive: scopri come archivi...</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>1</th>\n",
              "      <td>proxy</td>\n",
              "      <td>https://www.evemilano.com/proxy-server/</td>\n",
              "      <td>5</td>\n",
              "      <td>51043</td>\n",
              "      <td>10</td>\n",
              "      <td>0.01%</td>\n",
              "      <td>0.30%</td>\n",
              "      <td>lower</td>\n",
              "      <td>proxy</td>\n",
              "      <td>proxy, proxy server, server proxy, proxy signi...</td>\n",
              "      <td></td>\n",
              "      <td>0</td>\n",
              "      <td>N.A.</td>\n",
              "      <td>None</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>2</th>\n",
              "      <td>webarchive</td>\n",
              "      <td>https://www.evemilano.com/web-archive/</td>\n",
              "      <td>88</td>\n",
              "      <td>43088</td>\n",
              "      <td>5</td>\n",
              "      <td>0.20%</td>\n",
              "      <td>0.97%</td>\n",
              "      <td>lower</td>\n",
              "      <td>webarchive</td>\n",
              "      <td>web archive, webarchive, archive web, web.arch...</td>\n",
              "      <td>Cos’è Web Archive? Scopri i suoi utilizzi pratici</td>\n",
              "      <td>49</td>\n",
              "      <td>Missing 3: web.archive, internet, webarchive</td>\n",
              "      <td>\"Web Archive e Webarchive: scopri come archivi...</td>\n",
              "    </tr>\n",
              "  </tbody>\n",
              "</table>\n",
              "</div>"
            ],
            "text/plain": [
              "         query                                     page  clicks  impressions  \\\n",
              "0  web archive   https://www.evemilano.com/web-archive/     200        62371   \n",
              "1        proxy  https://www.evemilano.com/proxy-server/       5        51043   \n",
              "2   webarchive   https://www.evemilano.com/web-archive/      88        43088   \n",
              "\n",
              "   position   ctr  website_avg_ctr_by_pos comparison  main_query  \\\n",
              "0         5 0.32%                   0.97%      lower         web   \n",
              "1        10 0.01%                   0.30%      lower       proxy   \n",
              "2         5 0.20%                   0.97%      lower  webarchive   \n",
              "\n",
              "                                       top_5_queries  \\\n",
              "0  web archive, webarchive, archive web, web.arch...   \n",
              "1  proxy, proxy server, server proxy, proxy signi...   \n",
              "2  web archive, webarchive, archive web, web.arch...   \n",
              "\n",
              "                                           tag title  tag title len  \\\n",
              "0  Cos’è Web Archive? Scopri i suoi utilizzi pratici             49   \n",
              "1                                                                 0   \n",
              "2  Cos’è Web Archive? Scopri i suoi utilizzi pratici             49   \n",
              "\n",
              "                                          check  \\\n",
              "0  Missing 3: web.archive, internet, webarchive   \n",
              "1                                          N.A.   \n",
              "2  Missing 3: web.archive, internet, webarchive   \n",
              "\n",
              "                                       new tag title  \n",
              "0  \"Web Archive e Webarchive: scopri come archivi...  \n",
              "1                                               None  \n",
              "2  \"Web Archive e Webarchive: scopri come archivi...  "
            ]
          },
          "execution_count": 263,
          "metadata": {},
          "output_type": "execute_result"
        }
      ],
      "source": [
        "# ordina le colonne del foglio check tag title\n",
        "column_order3 = [\n",
        "    \"query\",\n",
        "    \"page\",\n",
        "    \"clicks\",\n",
        "    \"impressions\",\n",
        "    \"position\",\n",
        "    \"ctr\",\n",
        "    \"website_avg_ctr_by_pos\",\n",
        "    \"comparison\",\n",
        "    \"main_query\",\n",
        "    \"top_5_queries\",\n",
        "    \"tag title\",\n",
        "    \"tag title len\",\n",
        "    \"check\",\n",
        "    \"new tag title\"\n",
        "]\n",
        "# reindex\n",
        "merged_df9 = merged_df8b.reindex(columns=column_order3)\n",
        "\n",
        "# Stampa la somma totale dei clicks e delle impressions\n",
        "total_clicks = merged_df9['clicks'].sum()\n",
        "total_impressions = merged_df9['impressions'].sum()\n",
        "\n",
        "print(\"Somma totale dei clicks:\", total_clicks)\n",
        "print(\"Somma totale delle impressions:\", total_impressions)\n",
        "merged_df9.head(3)"
      ]
    },
    {
      "cell_type": "code",
      "execution_count": 264,
      "metadata": {},
      "outputs": [],
      "source": [
        "# Pulizia new tag title\n",
        "def clean_and_capitalize(x):\n",
        "    if pd.isna(x) or x is None:\n",
        "        return None\n",
        "    else:\n",
        "        # Rimuovi eventuali virgolette singole e doppie e converti la prima lettera di ogni parola in maiuscolo\n",
        "        x = x.replace('\"', '').replace(\"'\", '').capitalize()\n",
        "        # Rimuovi eventuali segni di punteggiatura alla fine della stringa (compresi i punti)\n",
        "        x = x.rstrip(string.punctuation.replace('.', ''))\n",
        "        return x\n",
        "\n",
        "merged_df9['new tag title'] = merged_df9['new tag title'].apply(clean_and_capitalize)\n",
        "#display(merged_df9)"
      ]
    },
    {
      "cell_type": "code",
      "execution_count": 265,
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "1lzLXAgX4OVt",
        "outputId": "0ee30891-2fca-455b-db85-a1fd65d79c1b"
      },
      "outputs": [],
      "source": [
        "# Conta caratteri new tag title\n",
        "# Creare la nuova colonna \"tag title length\" con la lunghezza della stringa in \"tag title\"\n",
        "merged_df9b=merged_df9.copy()\n",
        "merged_df9b.insert(merged_df9b.columns.get_loc(\"new tag title\")+1, \"new tag title len\", merged_df9b[\"new tag title\"].apply(lambda x: len(str(x))))\n",
        "#merged_df9b.head(5)"
      ]
    },
    {
      "cell_type": "code",
      "execution_count": 266,
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "7qjtrcUY5WDQ",
        "outputId": "123dffe0-72c6-4005-c3ea-9bb81d4a9049"
      },
      "outputs": [
        {
          "name": "stdout",
          "output_type": "stream",
          "text": [
            "Somma totale dei clicks: 24903\n",
            "Somma totale delle impressions: 3763566\n"
          ]
        },
        {
          "data": {
            "text/html": [
              "<div>\n",
              "<style scoped>\n",
              "    .dataframe tbody tr th:only-of-type {\n",
              "        vertical-align: middle;\n",
              "    }\n",
              "\n",
              "    .dataframe tbody tr th {\n",
              "        vertical-align: top;\n",
              "    }\n",
              "\n",
              "    .dataframe thead th {\n",
              "        text-align: right;\n",
              "    }\n",
              "</style>\n",
              "<table border=\"1\" class=\"dataframe\">\n",
              "  <thead>\n",
              "    <tr style=\"text-align: right;\">\n",
              "      <th></th>\n",
              "      <th>query</th>\n",
              "      <th>page</th>\n",
              "      <th>clicks</th>\n",
              "      <th>impressions</th>\n",
              "      <th>position</th>\n",
              "      <th>ctr</th>\n",
              "      <th>website_avg_ctr_by_pos</th>\n",
              "      <th>comparison</th>\n",
              "      <th>main_query</th>\n",
              "      <th>top_5_queries</th>\n",
              "      <th>tag title</th>\n",
              "      <th>tag title len</th>\n",
              "      <th>check</th>\n",
              "      <th>new tag title</th>\n",
              "      <th>new tag title len</th>\n",
              "      <th>diff</th>\n",
              "      <th>diff_check</th>\n",
              "    </tr>\n",
              "  </thead>\n",
              "  <tbody>\n",
              "    <tr>\n",
              "      <th>0</th>\n",
              "      <td>web archive</td>\n",
              "      <td>https://www.evemilano.com/web-archive/</td>\n",
              "      <td>200</td>\n",
              "      <td>62371</td>\n",
              "      <td>5</td>\n",
              "      <td>0.32%</td>\n",
              "      <td>0.97%</td>\n",
              "      <td>lower</td>\n",
              "      <td>web</td>\n",
              "      <td>web archive, webarchive, archive web, web.arch...</td>\n",
              "      <td>Cos’è Web Archive? Scopri i suoi utilizzi pratici</td>\n",
              "      <td>49</td>\n",
              "      <td>Missing 3: web.archive, internet, webarchive</td>\n",
              "      <td>Web archive e webarchive: scopri come archivia...</td>\n",
              "      <td>55</td>\n",
              "      <td>6</td>\n",
              "      <td>From Opt to Opt</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>1</th>\n",
              "      <td>proxy</td>\n",
              "      <td>https://www.evemilano.com/proxy-server/</td>\n",
              "      <td>5</td>\n",
              "      <td>51043</td>\n",
              "      <td>10</td>\n",
              "      <td>0.01%</td>\n",
              "      <td>0.30%</td>\n",
              "      <td>lower</td>\n",
              "      <td>proxy</td>\n",
              "      <td>proxy, proxy server, server proxy, proxy signi...</td>\n",
              "      <td></td>\n",
              "      <td>0</td>\n",
              "      <td>N.A.</td>\n",
              "      <td>None</td>\n",
              "      <td>4</td>\n",
              "      <td>4</td>\n",
              "      <td>N.A.</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>2</th>\n",
              "      <td>webarchive</td>\n",
              "      <td>https://www.evemilano.com/web-archive/</td>\n",
              "      <td>88</td>\n",
              "      <td>43088</td>\n",
              "      <td>5</td>\n",
              "      <td>0.20%</td>\n",
              "      <td>0.97%</td>\n",
              "      <td>lower</td>\n",
              "      <td>webarchive</td>\n",
              "      <td>web archive, webarchive, archive web, web.arch...</td>\n",
              "      <td>Cos’è Web Archive? Scopri i suoi utilizzi pratici</td>\n",
              "      <td>49</td>\n",
              "      <td>Missing 3: web.archive, internet, webarchive</td>\n",
              "      <td>Web archive e webarchive: scopri come archivia...</td>\n",
              "      <td>55</td>\n",
              "      <td>6</td>\n",
              "      <td>From Opt to Opt</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>3</th>\n",
              "      <td>indirizzo ip</td>\n",
              "      <td>https://www.evemilano.com/come-trovare-indiriz...</td>\n",
              "      <td>28</td>\n",
              "      <td>41172</td>\n",
              "      <td>3</td>\n",
              "      <td>0.07%</td>\n",
              "      <td>4.12%</td>\n",
              "      <td>lower</td>\n",
              "      <td>ip</td>\n",
              "      <td>indirizzo ip, l'indirizzo di un sito, trova in...</td>\n",
              "      <td></td>\n",
              "      <td>0</td>\n",
              "      <td>N.A.</td>\n",
              "      <td>None</td>\n",
              "      <td>4</td>\n",
              "      <td>4</td>\n",
              "      <td>N.A.</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>4</th>\n",
              "      <td>gdpr acronimo</td>\n",
              "      <td>https://www.evemilano.com/gdpr/</td>\n",
              "      <td>26</td>\n",
              "      <td>32356</td>\n",
              "      <td>8</td>\n",
              "      <td>0.08%</td>\n",
              "      <td>0.27%</td>\n",
              "      <td>lower</td>\n",
              "      <td>gdpr</td>\n",
              "      <td>gdpr acronimo, gdpr significato, gdpr, acronim...</td>\n",
              "      <td></td>\n",
              "      <td>0</td>\n",
              "      <td>N.A.</td>\n",
              "      <td>None</td>\n",
              "      <td>4</td>\n",
              "      <td>4</td>\n",
              "      <td>N.A.</td>\n",
              "    </tr>\n",
              "  </tbody>\n",
              "</table>\n",
              "</div>"
            ],
            "text/plain": [
              "           query                                               page  clicks  \\\n",
              "0    web archive             https://www.evemilano.com/web-archive/     200   \n",
              "1          proxy            https://www.evemilano.com/proxy-server/       5   \n",
              "2     webarchive             https://www.evemilano.com/web-archive/      88   \n",
              "3   indirizzo ip  https://www.evemilano.com/come-trovare-indiriz...      28   \n",
              "4  gdpr acronimo                    https://www.evemilano.com/gdpr/      26   \n",
              "\n",
              "   impressions  position   ctr  website_avg_ctr_by_pos comparison  main_query  \\\n",
              "0        62371         5 0.32%                   0.97%      lower         web   \n",
              "1        51043        10 0.01%                   0.30%      lower       proxy   \n",
              "2        43088         5 0.20%                   0.97%      lower  webarchive   \n",
              "3        41172         3 0.07%                   4.12%      lower          ip   \n",
              "4        32356         8 0.08%                   0.27%      lower        gdpr   \n",
              "\n",
              "                                       top_5_queries  \\\n",
              "0  web archive, webarchive, archive web, web.arch...   \n",
              "1  proxy, proxy server, server proxy, proxy signi...   \n",
              "2  web archive, webarchive, archive web, web.arch...   \n",
              "3  indirizzo ip, l'indirizzo di un sito, trova in...   \n",
              "4  gdpr acronimo, gdpr significato, gdpr, acronim...   \n",
              "\n",
              "                                           tag title  tag title len  \\\n",
              "0  Cos’è Web Archive? Scopri i suoi utilizzi pratici             49   \n",
              "1                                                                 0   \n",
              "2  Cos’è Web Archive? Scopri i suoi utilizzi pratici             49   \n",
              "3                                                                 0   \n",
              "4                                                                 0   \n",
              "\n",
              "                                          check  \\\n",
              "0  Missing 3: web.archive, internet, webarchive   \n",
              "1                                          N.A.   \n",
              "2  Missing 3: web.archive, internet, webarchive   \n",
              "3                                          N.A.   \n",
              "4                                          N.A.   \n",
              "\n",
              "                                       new tag title  new tag title len  diff  \\\n",
              "0  Web archive e webarchive: scopri come archivia...                 55     6   \n",
              "1                                               None                  4     4   \n",
              "2  Web archive e webarchive: scopri come archivia...                 55     6   \n",
              "3                                               None                  4     4   \n",
              "4                                               None                  4     4   \n",
              "\n",
              "        diff_check  \n",
              "0  From Opt to Opt  \n",
              "1             N.A.  \n",
              "2  From Opt to Opt  \n",
              "3             N.A.  \n",
              "4             N.A.  "
            ]
          },
          "execution_count": 266,
          "metadata": {},
          "output_type": "execute_result"
        }
      ],
      "source": [
        "# Calcolo differenza tag title\n",
        "merged_df10 = merged_df9b.copy()\n",
        "merged_df10.insert(merged_df10.columns.get_loc(\"new tag title len\") + 1, \"diff\", merged_df10[\"new tag title len\"] - merged_df10[\"tag title len\"])\n",
        "\n",
        "# aggiungi colonna diff_check shorter longer\n",
        "\n",
        "# analisi dei nuovi tag title e creazione etichetta diff_check\n",
        "def apply_label(row):\n",
        "    # Aggiungere il controllo per verificare che entrambi i titoli siano stringhe non vuote.\n",
        "    if pd.notnull(row['tag title']) and row['tag title'].strip() and \\\n",
        "       pd.notnull(row['new tag title']) and row['new tag title'].strip():\n",
        "        tag_title_len = row['tag title len']\n",
        "        new_tag_title_len = row['new tag title len']\n",
        "\n",
        "        if tag_title_len > 70 and 45 <= new_tag_title_len <= 70:\n",
        "            return \"From Long to Opt\"\n",
        "        elif tag_title_len < 45 and 45 <= new_tag_title_len <= 70:\n",
        "            return \"From Short to Opt\"\n",
        "        elif 45 <= tag_title_len <= 70 and 45 <= new_tag_title_len <= 70:\n",
        "            return \"From Opt to Opt\"\n",
        "        elif tag_title_len > 70 and new_tag_title_len > 70:\n",
        "            return \"From Long to Long\"\n",
        "        elif tag_title_len < 45 and new_tag_title_len > 70:\n",
        "            return \"From Short to Long\"\n",
        "        elif 45 <= tag_title_len <= 70 and new_tag_title_len > 70:\n",
        "            return \"From Opt to Long\"\n",
        "        elif tag_title_len > 70 and new_tag_title_len < 45:\n",
        "            return \"From Long to Short\"\n",
        "        elif tag_title_len < 45 and new_tag_title_len < 45:\n",
        "            return \"From Short to Short\"\n",
        "        elif 45 <= tag_title_len <= 70 and new_tag_title_len < 45:\n",
        "            return \"From Opt to Short\"\n",
        "    # Se una delle colonne è vuota, restituisci \"Unlabeled\" o un altro valore appropriato.\n",
        "    return \"N.A.\"\n",
        "\n",
        "# Applica la funzione solo alle righe con valori non vuoti per le colonne specificate\n",
        "merged_df10['diff_check'] = merged_df10.apply(apply_label, axis=1)\n",
        "\n",
        "# Stampa la somma totale dei clicks e delle impressions\n",
        "total_clicks = merged_df10['clicks'].sum()\n",
        "total_impressions = merged_df10['impressions'].sum()\n",
        "\n",
        "print(\"Somma totale dei clicks:\", total_clicks)\n",
        "print(\"Somma totale delle impressions:\", total_impressions)\n",
        "merged_df10.head(5)\n"
      ]
    },
    {
      "cell_type": "code",
      "execution_count": 267,
      "metadata": {},
      "outputs": [
        {
          "name": "stdout",
          "output_type": "stream",
          "text": [
            "preparazione dei dati\n",
            "normalizzazione dei dati\n",
            "addestramento\n",
            "Model loaded successfully\n",
            "Epoch: 10, Training Loss: 0.0805, Validation Loss: 0.0708\n",
            "Epoch: 20, Training Loss: 0.0229, Validation Loss: 0.0460\n",
            "Epoch: 30, Training Loss: 0.0349, Validation Loss: 0.0493\n",
            "Epoch: 40, Training Loss: 0.0104, Validation Loss: 0.0574\n",
            "Epoch: 50, Training Loss: 0.0208, Validation Loss: 0.0599\n",
            "Epoch: 60, Training Loss: 0.0071, Validation Loss: 0.0453\n",
            "Epoch: 70, Training Loss: 0.1293, Validation Loss: 0.0520\n",
            "Epoch: 80, Training Loss: 0.0219, Validation Loss: 0.0484\n",
            "Epoch: 90, Training Loss: 0.0588, Validation Loss: 0.0499\n",
            "Epoch: 100, Training Loss: 0.0347, Validation Loss: 0.0464\n",
            "salvataggio modello\n",
            "previsione\n"
          ]
        }
      ],
      "source": [
        "# test 1 pytorch\n",
        "df_torch = merged_df10.copy()\n",
        "\n",
        "if previsioni == 'y':\n",
        "    import torch\n",
        "    import torch.nn as nn\n",
        "    import torch.optim as optim\n",
        "    from torch.utils.data import Dataset, DataLoader\n",
        "    from sklearn.model_selection import train_test_split\n",
        "    from sklearn.preprocessing import StandardScaler\n",
        "\n",
        "    # Preparazione dei dati\n",
        "    # Estrae le colonne 'impressions', 'position', 'ctr' come input e 'clicks' come target\n",
        "    print('preparazione dei dati')\n",
        "    data = df_torch[['impressions','position','ctr']].values\n",
        "    target = df_torch['clicks'].values\n",
        "\n",
        "    # Normalizzazione dei dati e del target\n",
        "    print('normalizzazione dei dati')\n",
        "    # È importante normalizzare i dati per migliorare le prestazioni e la stabilità dell'addestramento del modello\n",
        "    scaler_x = StandardScaler()\n",
        "    scaler_y = StandardScaler()\n",
        "    # Applicazione della normalizzazione\n",
        "    data = scaler_x.fit_transform(data)\n",
        "    target = scaler_y.fit_transform(target.reshape(-1, 1))\n",
        "\n",
        "    # Divisione dei dati in set di addestramento e di test\n",
        "    # Il 70% dei dati viene utilizzato per l'addestramento, il 30% per il test\n",
        "    data_train, data_test, target_train, target_test = train_test_split(data, target, test_size=0.3, random_state=42)\n",
        "\n",
        "    # Questa classe consente di gestire facilmente i dati durante l'addestramento e il test\n",
        "    class ClickPredictionDataset(Dataset):\n",
        "        def __init__(self, data, target):\n",
        "            self.data = torch.FloatTensor(data)\n",
        "            self.target = torch.FloatTensor(target)\n",
        "\n",
        "        def __len__(self):\n",
        "            return len(self.data)\n",
        "\n",
        "        def __getitem__(self, idx):\n",
        "            return self.data[idx], self.target[idx]\n",
        "\n",
        "    # Creazione di istanze del dataset per addestramento e test\n",
        "    print('addestramento')\n",
        "    train_dataset = ClickPredictionDataset(data_train, target_train)\n",
        "    test_dataset = ClickPredictionDataset(data_test, target_test)\n",
        "    # Creazione dei DataLoader per gestire i batch di dati durante l'addestramento\n",
        "    train_dataloader = DataLoader(train_dataset, batch_size=100, shuffle=True)\n",
        "    test_dataloader = DataLoader(test_dataset, batch_size=100)\n",
        "\n",
        "    # Creazione del modello\n",
        "    # Definizione del modello di rete neurale\n",
        "    class ClickPredictionModel(nn.Module):\n",
        "        def __init__(self, input_size, hidden_size, output_size):\n",
        "            super(ClickPredictionModel, self).__init__()\n",
        "            self.fc1 = nn.Linear(input_size, hidden_size)  # 1 strato lineare\n",
        "            self.fc2 = nn.Linear(hidden_size, output_size)  # 2 strato lineare\n",
        "\n",
        "        def forward(self, x):\n",
        "            x = torch.relu(self.fc1(x)) # applicazione della funzione di attivazione ReLU\n",
        "            x = self.fc2(x) # output dal secondo strato\n",
        "            return x\n",
        "\n",
        "    # Impostazione delle dimensioni del modello\n",
        "    input_size = data.shape[1]\n",
        "    # \n",
        "    # hidden size 64, 128, 256, 512\n",
        "    hidden_size = 512\n",
        "    output_size = 1\n",
        "    model = ClickPredictionModel(input_size, hidden_size, output_size)\n",
        "\n",
        "    # Verifica se esiste un modello salvato da caricare\n",
        "    try:\n",
        "        model.load_state_dict(torch.load('model.pth'))\n",
        "        print(\"Model loaded successfully\")\n",
        "    except FileNotFoundError:\n",
        "        print(\"No previous model found, starting training from scratch\")\n",
        "    # Imposta il modello in modalità addestramento\n",
        "    model.train()  # Set the model to training mode\n",
        "\n",
        "    # Definizione della funzione di perdita e dell'ottimizzatore\n",
        "    criterion = nn.MSELoss() # Funzione di perdita Mean Squared Error\n",
        "    optimizer = optim.Adam(model.parameters(), lr=0.005) # Addestramento del modello\n",
        "    num_epochs = 100\n",
        "\n",
        "    for epoch in range(num_epochs):\n",
        "        # Fase di addestramento\n",
        "        # Training\n",
        "        model.train()\n",
        "        train_losses = []\n",
        "        for inputs, targets in train_dataloader:\n",
        "            # Forward pass\n",
        "            outputs = model(inputs)\n",
        "            loss = criterion(outputs, targets)\n",
        "\n",
        "            # Backward pass e ottimizzazione\n",
        "            optimizer.zero_grad()\n",
        "            loss.backward()\n",
        "            optimizer.step()\n",
        "\n",
        "            train_losses.append(loss.item())\n",
        "            \n",
        "        # Validation\n",
        "        # Fase di validazione\n",
        "        model.eval()\n",
        "        val_losses = []\n",
        "        with torch.no_grad():\n",
        "            for inputs, targets in test_dataloader:\n",
        "                outputs = model(inputs)\n",
        "                loss = criterion(outputs, targets)\n",
        "                val_losses.append(loss.item())\n",
        "            \n",
        "        if (epoch + 1) % 10 == 0:\n",
        "            print(f'Epoch: {epoch+1}, Training Loss: {np.mean(train_losses):.4f}, Validation Loss: {np.mean(val_losses):.4f}')\n",
        "\n",
        "    # Save the model\n",
        "    torch.save(model.state_dict(), 'model.pth')\n",
        "    print('salvataggio modello')\n",
        "    model.eval()\n",
        "\n",
        "    # Creazione del set di dati per la posizione 1\n",
        "    data_pos1 = df_torch[['impressions','position','ctr']].copy()\n",
        "    data_pos1['position'] = 1\n",
        "    data_pos1 = scaler_x.transform(data_pos1.values)  # usa lo scaler già addestrato\n",
        "\n",
        "    # Previsione dei click per posizione 1\n",
        "    print('previsione')\n",
        "    with torch.no_grad():\n",
        "        inputs = torch.FloatTensor(data_pos1)\n",
        "        predicted_clicks_pos1 = model(inputs).numpy()\n",
        "\n",
        "    # Aggiunta della colonna con la stima dei click per posizione 1 al dataframe\n",
        "    df_torch['estimated_clicks_pos1'] = scaler_y.inverse_transform(predicted_clicks_pos1)\n",
        "    df_torch['estimated_clicks_pos1'] = df_torch['estimated_clicks_pos1'].round().astype(int)\n",
        "    df_torch.head(10)"
      ]
    },
    {
      "cell_type": "code",
      "execution_count": 268,
      "metadata": {},
      "outputs": [
        {
          "data": {
            "text/html": [
              "<div>\n",
              "<style scoped>\n",
              "    .dataframe tbody tr th:only-of-type {\n",
              "        vertical-align: middle;\n",
              "    }\n",
              "\n",
              "    .dataframe tbody tr th {\n",
              "        vertical-align: top;\n",
              "    }\n",
              "\n",
              "    .dataframe thead th {\n",
              "        text-align: right;\n",
              "    }\n",
              "</style>\n",
              "<table border=\"1\" class=\"dataframe\">\n",
              "  <thead>\n",
              "    <tr style=\"text-align: right;\">\n",
              "      <th></th>\n",
              "      <th>query</th>\n",
              "      <th>page</th>\n",
              "      <th>clicks</th>\n",
              "      <th>impressions</th>\n",
              "      <th>position</th>\n",
              "      <th>ctr</th>\n",
              "      <th>website_avg_ctr_by_pos</th>\n",
              "      <th>comparison</th>\n",
              "      <th>main_query</th>\n",
              "      <th>top_5_queries</th>\n",
              "      <th>tag title</th>\n",
              "      <th>tag title len</th>\n",
              "      <th>check</th>\n",
              "      <th>new tag title</th>\n",
              "      <th>new tag title len</th>\n",
              "      <th>diff</th>\n",
              "      <th>diff_check</th>\n",
              "      <th>estimated_clicks_pos1</th>\n",
              "    </tr>\n",
              "  </thead>\n",
              "  <tbody>\n",
              "    <tr>\n",
              "      <th>0</th>\n",
              "      <td>web archive</td>\n",
              "      <td>https://www.evemilano.com/web-archive/</td>\n",
              "      <td>200</td>\n",
              "      <td>62371</td>\n",
              "      <td>5</td>\n",
              "      <td>0.32%</td>\n",
              "      <td>0.97%</td>\n",
              "      <td>lower</td>\n",
              "      <td>web</td>\n",
              "      <td>web archive, webarchive, archive web, web.arch...</td>\n",
              "      <td>Cos’è Web Archive? Scopri i suoi utilizzi pratici</td>\n",
              "      <td>49</td>\n",
              "      <td>Missing 3: web.archive, internet, webarchive</td>\n",
              "      <td>Web archive e webarchive: scopri come archivia...</td>\n",
              "      <td>55</td>\n",
              "      <td>6</td>\n",
              "      <td>From Opt to Opt</td>\n",
              "      <td>311</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>1</th>\n",
              "      <td>proxy</td>\n",
              "      <td>https://www.evemilano.com/proxy-server/</td>\n",
              "      <td>5</td>\n",
              "      <td>51043</td>\n",
              "      <td>10</td>\n",
              "      <td>0.01%</td>\n",
              "      <td>0.30%</td>\n",
              "      <td>lower</td>\n",
              "      <td>proxy</td>\n",
              "      <td>proxy, proxy server, server proxy, proxy signi...</td>\n",
              "      <td></td>\n",
              "      <td>0</td>\n",
              "      <td>N.A.</td>\n",
              "      <td>None</td>\n",
              "      <td>4</td>\n",
              "      <td>4</td>\n",
              "      <td>N.A.</td>\n",
              "      <td>170</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>2</th>\n",
              "      <td>webarchive</td>\n",
              "      <td>https://www.evemilano.com/web-archive/</td>\n",
              "      <td>88</td>\n",
              "      <td>43088</td>\n",
              "      <td>5</td>\n",
              "      <td>0.20%</td>\n",
              "      <td>0.97%</td>\n",
              "      <td>lower</td>\n",
              "      <td>webarchive</td>\n",
              "      <td>web archive, webarchive, archive web, web.arch...</td>\n",
              "      <td>Cos’è Web Archive? Scopri i suoi utilizzi pratici</td>\n",
              "      <td>49</td>\n",
              "      <td>Missing 3: web.archive, internet, webarchive</td>\n",
              "      <td>Web archive e webarchive: scopri come archivia...</td>\n",
              "      <td>55</td>\n",
              "      <td>6</td>\n",
              "      <td>From Opt to Opt</td>\n",
              "      <td>153</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>3</th>\n",
              "      <td>indirizzo ip</td>\n",
              "      <td>https://www.evemilano.com/come-trovare-indiriz...</td>\n",
              "      <td>28</td>\n",
              "      <td>41172</td>\n",
              "      <td>3</td>\n",
              "      <td>0.07%</td>\n",
              "      <td>4.12%</td>\n",
              "      <td>lower</td>\n",
              "      <td>ip</td>\n",
              "      <td>indirizzo ip, l'indirizzo di un sito, trova in...</td>\n",
              "      <td></td>\n",
              "      <td>0</td>\n",
              "      <td>N.A.</td>\n",
              "      <td>None</td>\n",
              "      <td>4</td>\n",
              "      <td>4</td>\n",
              "      <td>N.A.</td>\n",
              "      <td>113</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>4</th>\n",
              "      <td>gdpr acronimo</td>\n",
              "      <td>https://www.evemilano.com/gdpr/</td>\n",
              "      <td>26</td>\n",
              "      <td>32356</td>\n",
              "      <td>8</td>\n",
              "      <td>0.08%</td>\n",
              "      <td>0.27%</td>\n",
              "      <td>lower</td>\n",
              "      <td>gdpr</td>\n",
              "      <td>gdpr acronimo, gdpr significato, gdpr, acronim...</td>\n",
              "      <td></td>\n",
              "      <td>0</td>\n",
              "      <td>N.A.</td>\n",
              "      <td>None</td>\n",
              "      <td>4</td>\n",
              "      <td>4</td>\n",
              "      <td>N.A.</td>\n",
              "      <td>84</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>5</th>\n",
              "      <td>consulenza seo</td>\n",
              "      <td>https://www.evemilano.com/</td>\n",
              "      <td>0</td>\n",
              "      <td>27454</td>\n",
              "      <td>30</td>\n",
              "      <td>0.00%</td>\n",
              "      <td>0.08%</td>\n",
              "      <td>lower</td>\n",
              "      <td>seo</td>\n",
              "      <td>consulenza seo, consulente seo, agenzia seo, c...</td>\n",
              "      <td></td>\n",
              "      <td>0</td>\n",
              "      <td>N.A.</td>\n",
              "      <td>None</td>\n",
              "      <td>4</td>\n",
              "      <td>4</td>\n",
              "      <td>N.A.</td>\n",
              "      <td>51</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>6</th>\n",
              "      <td>agenzia seo</td>\n",
              "      <td>https://www.evemilano.com/servizi-seo/agenzia/</td>\n",
              "      <td>2</td>\n",
              "      <td>27130</td>\n",
              "      <td>71</td>\n",
              "      <td>0.01%</td>\n",
              "      <td>0.10%</td>\n",
              "      <td>lower</td>\n",
              "      <td>seo</td>\n",
              "      <td>agenzia seo, agenzia seo milano, agenzie seo m...</td>\n",
              "      <td></td>\n",
              "      <td>0</td>\n",
              "      <td>N.A.</td>\n",
              "      <td>None</td>\n",
              "      <td>4</td>\n",
              "      <td>4</td>\n",
              "      <td>N.A.</td>\n",
              "      <td>52</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>7</th>\n",
              "      <td>gdpr significato</td>\n",
              "      <td>https://www.evemilano.com/gdpr/</td>\n",
              "      <td>11</td>\n",
              "      <td>26666</td>\n",
              "      <td>8</td>\n",
              "      <td>0.04%</td>\n",
              "      <td>0.27%</td>\n",
              "      <td>lower</td>\n",
              "      <td>significato</td>\n",
              "      <td>gdpr acronimo, gdpr significato, gdpr, acronim...</td>\n",
              "      <td></td>\n",
              "      <td>0</td>\n",
              "      <td>N.A.</td>\n",
              "      <td>None</td>\n",
              "      <td>4</td>\n",
              "      <td>4</td>\n",
              "      <td>N.A.</td>\n",
              "      <td>56</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>8</th>\n",
              "      <td>regex</td>\n",
              "      <td>https://www.evemilano.com/come-funzionano-le-e...</td>\n",
              "      <td>92</td>\n",
              "      <td>22931</td>\n",
              "      <td>9</td>\n",
              "      <td>0.40%</td>\n",
              "      <td>0.51%</td>\n",
              "      <td>lower</td>\n",
              "      <td>regex</td>\n",
              "      <td>regex, regular expression, espressioni regolar...</td>\n",
              "      <td></td>\n",
              "      <td>0</td>\n",
              "      <td>N.A.</td>\n",
              "      <td>None</td>\n",
              "      <td>4</td>\n",
              "      <td>4</td>\n",
              "      <td>N.A.</td>\n",
              "      <td>108</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>9</th>\n",
              "      <td>posizionamento siti web</td>\n",
              "      <td>https://www.evemilano.com/servizi-seo/posizion...</td>\n",
              "      <td>1</td>\n",
              "      <td>19860</td>\n",
              "      <td>34</td>\n",
              "      <td>0.01%</td>\n",
              "      <td>0.09%</td>\n",
              "      <td>lower</td>\n",
              "      <td>web</td>\n",
              "      <td>posizionamento siti web, posizionamento siti, ...</td>\n",
              "      <td></td>\n",
              "      <td>0</td>\n",
              "      <td>N.A.</td>\n",
              "      <td>None</td>\n",
              "      <td>4</td>\n",
              "      <td>4</td>\n",
              "      <td>N.A.</td>\n",
              "      <td>32</td>\n",
              "    </tr>\n",
              "  </tbody>\n",
              "</table>\n",
              "</div>"
            ],
            "text/plain": [
              "                     query                                               page  \\\n",
              "0              web archive             https://www.evemilano.com/web-archive/   \n",
              "1                    proxy            https://www.evemilano.com/proxy-server/   \n",
              "2               webarchive             https://www.evemilano.com/web-archive/   \n",
              "3             indirizzo ip  https://www.evemilano.com/come-trovare-indiriz...   \n",
              "4            gdpr acronimo                    https://www.evemilano.com/gdpr/   \n",
              "5           consulenza seo                         https://www.evemilano.com/   \n",
              "6              agenzia seo     https://www.evemilano.com/servizi-seo/agenzia/   \n",
              "7         gdpr significato                    https://www.evemilano.com/gdpr/   \n",
              "8                    regex  https://www.evemilano.com/come-funzionano-le-e...   \n",
              "9  posizionamento siti web  https://www.evemilano.com/servizi-seo/posizion...   \n",
              "\n",
              "   clicks  impressions  position   ctr  website_avg_ctr_by_pos comparison  \\\n",
              "0     200        62371         5 0.32%                   0.97%      lower   \n",
              "1       5        51043        10 0.01%                   0.30%      lower   \n",
              "2      88        43088         5 0.20%                   0.97%      lower   \n",
              "3      28        41172         3 0.07%                   4.12%      lower   \n",
              "4      26        32356         8 0.08%                   0.27%      lower   \n",
              "5       0        27454        30 0.00%                   0.08%      lower   \n",
              "6       2        27130        71 0.01%                   0.10%      lower   \n",
              "7      11        26666         8 0.04%                   0.27%      lower   \n",
              "8      92        22931         9 0.40%                   0.51%      lower   \n",
              "9       1        19860        34 0.01%                   0.09%      lower   \n",
              "\n",
              "    main_query                                      top_5_queries  \\\n",
              "0          web  web archive, webarchive, archive web, web.arch...   \n",
              "1        proxy  proxy, proxy server, server proxy, proxy signi...   \n",
              "2   webarchive  web archive, webarchive, archive web, web.arch...   \n",
              "3           ip  indirizzo ip, l'indirizzo di un sito, trova in...   \n",
              "4         gdpr  gdpr acronimo, gdpr significato, gdpr, acronim...   \n",
              "5          seo  consulenza seo, consulente seo, agenzia seo, c...   \n",
              "6          seo  agenzia seo, agenzia seo milano, agenzie seo m...   \n",
              "7  significato  gdpr acronimo, gdpr significato, gdpr, acronim...   \n",
              "8        regex  regex, regular expression, espressioni regolar...   \n",
              "9          web  posizionamento siti web, posizionamento siti, ...   \n",
              "\n",
              "                                           tag title  tag title len  \\\n",
              "0  Cos’è Web Archive? Scopri i suoi utilizzi pratici             49   \n",
              "1                                                                 0   \n",
              "2  Cos’è Web Archive? Scopri i suoi utilizzi pratici             49   \n",
              "3                                                                 0   \n",
              "4                                                                 0   \n",
              "5                                                                 0   \n",
              "6                                                                 0   \n",
              "7                                                                 0   \n",
              "8                                                                 0   \n",
              "9                                                                 0   \n",
              "\n",
              "                                          check  \\\n",
              "0  Missing 3: web.archive, internet, webarchive   \n",
              "1                                          N.A.   \n",
              "2  Missing 3: web.archive, internet, webarchive   \n",
              "3                                          N.A.   \n",
              "4                                          N.A.   \n",
              "5                                          N.A.   \n",
              "6                                          N.A.   \n",
              "7                                          N.A.   \n",
              "8                                          N.A.   \n",
              "9                                          N.A.   \n",
              "\n",
              "                                       new tag title  new tag title len  diff  \\\n",
              "0  Web archive e webarchive: scopri come archivia...                 55     6   \n",
              "1                                               None                  4     4   \n",
              "2  Web archive e webarchive: scopri come archivia...                 55     6   \n",
              "3                                               None                  4     4   \n",
              "4                                               None                  4     4   \n",
              "5                                               None                  4     4   \n",
              "6                                               None                  4     4   \n",
              "7                                               None                  4     4   \n",
              "8                                               None                  4     4   \n",
              "9                                               None                  4     4   \n",
              "\n",
              "        diff_check  estimated_clicks_pos1  \n",
              "0  From Opt to Opt                    311  \n",
              "1             N.A.                    170  \n",
              "2  From Opt to Opt                    153  \n",
              "3             N.A.                    113  \n",
              "4             N.A.                     84  \n",
              "5             N.A.                     51  \n",
              "6             N.A.                     52  \n",
              "7             N.A.                     56  \n",
              "8             N.A.                    108  \n",
              "9             N.A.                     32  "
            ]
          },
          "execution_count": 268,
          "metadata": {},
          "output_type": "execute_result"
        }
      ],
      "source": [
        "df_torch.head(10)"
      ]
    },
    {
      "cell_type": "code",
      "execution_count": 269,
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "okE0TzM3SYYw",
        "outputId": "5fe8de9c-4d5d-4ff6-f50d-0ffb95906a7c"
      },
      "outputs": [
        {
          "name": "stdout",
          "output_type": "stream",
          "text": [
            "Saving pvt_spacy...\n",
            "Questo df pvt_spacy ha 0 URLs\n",
            "Saving pvt_lemmy...\n",
            "Questo df pvt_lemmy ha 0 URLs\n",
            "Saving pvt_stem...\n",
            "Questo df pvt_stem ha 0 URLs\n",
            "Saving trending_folders...\n",
            "Questo df trending_folders ha 0 URLs\n",
            "Saving raw_df...\n",
            "Questo df raw_df ha 94498 URLs\n",
            "Exporting to CSV due to high URL count...\n",
            "DataFrame raw_df with high URL count saved as CSV in output/evemilano.com\\GSC_EXT_evemilano.com_365days_1crawls_20231205_2121.xlsx_Raw data.csv\n",
            "Saving query_pivot_tableP...\n",
            "Questo df query_pivot_tableP ha 0 URLs\n",
            "Saving raw_dfP...\n",
            "Questo df raw_dfP ha 1363 URLs\n",
            "Saving brand_count_df...\n",
            "Questo df brand_count_df ha 0 URLs\n",
            "Saving df_brand...\n",
            "Questo df df_brand ha 258 URLs\n",
            "Saving sorted_pivot...\n",
            "Questo df sorted_pivot ha 0 URLs\n",
            "Saving final_df...\n",
            "Questo df final_df ha 6847 URLs\n",
            "Saving cann_filtered_table...\n",
            "Questo df cann_filtered_table ha 0 URLs\n",
            "Saving df_top_improve...\n",
            "Questo df df_top_improve ha 1321 URLs\n",
            "Saving df_improve...\n",
            "Questo df df_improve ha 6274 URLs\n",
            "Saving df_torch...\n",
            "Questo df df_torch ha 6847 URLs\n",
            "Building exported csv index\n",
            "File output_file_name salvato in output/evemilano.com\\GSC_EXT_evemilano.com_365days_1crawls_20231205_2121.xlsx\n"
          ]
        }
      ],
      "source": [
        "# Salvataggio Export\n",
        "######################################################\n",
        "# Specifica il percorso completo del file di output\n",
        "filepath = os.path.join(new_output_dir, filename)\n",
        "# colleziona dataframe da esportare\n",
        "dataframes = {\n",
        "  'pvt_spacy' : 'Trending Topics',\n",
        "  'pvt_lemmy' : 'Trending Lemmas',\n",
        "  'pvt_stem' : 'Trending Stems',\n",
        "  'trending_folders':'Trending Folders',  \n",
        "  'raw_df': 'Raw data',\n",
        "  'query_pivot_tableP':'Query data',\n",
        "  'raw_dfP': 'URL data',\n",
        "  'brand_count_df': 'Brand table',\n",
        "  'df_brand': 'Brand queries',\n",
        "  'sorted_pivot': 'Pvt brand',\n",
        "  #'query_analysis': 'CTR by pos',\n",
        "  'final_df': 'Main output',\n",
        "  'cann_filtered_table': 'Cannibal',\n",
        "  'df_top_improve':'Improve 2<pos<11',\n",
        "  'df_improve': 'Improve pos>5',\n",
        "  'df_torch': 'Check title'\n",
        "}\n",
        "\n",
        "# Limite massimo di righe ed URL di Excel\n",
        "max_urls_in_sheets = 65530\n",
        "max_rows = 1048575\n",
        "\n",
        "csv_exported = []\n",
        "\n",
        "# Esporta il DataFrame in un file Excel nella cartella di output\n",
        "with pd.ExcelWriter(filepath) as writer:\n",
        "    for df_name, sheet_name in dataframes.items():\n",
        "        print(f\"Saving {df_name}...\")\n",
        "        if df_name in locals():\n",
        "            df = locals()[df_name]\n",
        "            lunghezzatot = len(df)\n",
        "\n",
        "            # Verifica il numero di URL nella colonna page\n",
        "            #url_count = df['page'].nunique() if 'page' in df.columns else 0\n",
        "            url_count = len(df['page']) if 'page' in df.columns else 0\n",
        "\n",
        "            print(f'Questo df {df_name} ha {url_count} URLs')\n",
        "            # Esporta in CSV se il numero di URL supera il limite\n",
        "            if url_count > max_urls_in_sheets:\n",
        "                print('Exporting to CSV due to high URL count...')\n",
        "                csv_filename = f\"{filename}_{sheet_name}.csv\"\n",
        "                csv_filepath = os.path.join(new_output_dir, csv_filename)\n",
        "                #df.to_csv(csv_filepath, index=False)\n",
        "                df.to_csv(csv_filepath, encoding='utf-8', index=False)\n",
        "                print(f\"DataFrame {df_name} with high URL count saved as CSV in {csv_filepath}\")\n",
        "                csv_exported.append((df_name, sheet_name))  # Aggiungi il DataFrame all'elenco dei CSV esportati\n",
        "                continue  # Salta l'esportazione in Excel per questo DataFrame\n",
        "            \n",
        "            # Converti gli URL in stringhe nel DataFrame\n",
        "            if 'page' in df.columns:  \n",
        "                #df['page'] = df['page'].astype(str)\n",
        "                df.loc[:, 'page'] = df['page'].astype(str)\n",
        "\n",
        "            \n",
        "            # Se il DataFrame ha più righe del limite massimo, troncalo al limite massimo\n",
        "            if len(df) > max_rows:\n",
        "                # esporta in csv i df troppo grandi\n",
        "                print('Exporting to CSV due to high ROW count...')\n",
        "                csv_filename = f\"{filename}_{sheet_name}.csv\"  # Nome del file CSV\n",
        "                csv_filepath = os.path.join(new_output_dir, csv_filename)  # Percorso del file CSV\n",
        "                df.to_csv(csv_filepath, index=False)  # Esporta in CSV\n",
        "                print(f\"Full DataFrame {df_name} saved as CSV in {csv_filepath}\")\n",
        "                # formattazine migliaia\n",
        "                print(f\"Truncating {df_name} to the first {max_rows:,} rows on total {lunghezzatot:,}.\")\n",
        "                df = df.iloc[:max_rows]\n",
        "            \n",
        "            index_option = True  # Imposta a True per i fogli con indice, False altrimenti\n",
        "            if sheet_name in ['Raw data', 'URL data', 'Brand queries', 'Main output', 'Improve 2<pos<11', 'Improve pos>5', 'Check title',]:\n",
        "                index_option = False\n",
        "            df.to_excel(writer, sheet_name=sheet_name, index=index_option)\n",
        "            \n",
        "        # Se ci sono DataFrame esportati in CSV, scrivili in un nuovo foglio Excel\n",
        "    if csv_exported:\n",
        "        print('Building exported csv index')\n",
        "        df_csv_exported = pd.DataFrame(csv_exported, columns=['DataFrame Name', 'Sheet Name'])\n",
        "        df_csv_exported.to_excel(writer, sheet_name='CSV Exported', index=False)\n",
        "\n",
        "# Stampa un messaggio di conferma\n",
        "print(f'File {file_name} salvato in {filepath}')"
      ]
    },
    {
      "cell_type": "code",
      "execution_count": 270,
      "metadata": {},
      "outputs": [
        {
          "name": "stdout",
          "output_type": "stream",
          "text": [
            "loading workbook\n",
            "workbook loaded\n",
            "formatting\n",
            "DONE!\n"
          ]
        }
      ],
      "source": [
        "if formattazione == 'y':\n",
        "    from openpyxl import load_workbook\n",
        "    from openpyxl.styles import NamedStyle\n",
        "    from openpyxl.formatting.rule import ColorScaleRule\n",
        "    from openpyxl.styles import Color\n",
        "\n",
        "    # Definisci gli stili\n",
        "    thousands_style = NamedStyle(name='thousands', number_format='#,##0')\n",
        "    percent_style = NamedStyle(name='percent', number_format='0.00%')\n",
        "    integer_style = NamedStyle(name='integer', number_format='0')\n",
        "\n",
        "    # Carica il workbook esistente\n",
        "    print('loading workbook')\n",
        "    workbook = load_workbook(filepath)\n",
        "    print('workbook loaded')\n",
        "    # Definisci la mappatura della colonna al suo stile e alla formattazione condizionale\n",
        "    column_formats = {\n",
        "        # FF0000 rosso - FFFFFF bianco - 00FF00 verde\n",
        "        'clicks': (thousands_style, 'FF0000', 'FFFFFF', '00FF00'),\n",
        "        'query': (thousands_style, 'FF0000', 'FFFFFF', '00FF00'),\n",
        "        'url_count': (thousands_style, 'FF0000', 'FFFFFF', '00FF00'),\n",
        "        'impressions': (thousands_style, 'FF0000', 'FFFFFF', '00FF00'),\n",
        "        'ctr': (percent_style, 'FF0000', 'FFFFFF', '00FF00'),\n",
        "        'website_avg_ctr_by_pos': (percent_style, 'FF0000', 'FFFFFF', '00FF00'),\n",
        "        'avg position': (integer_style, '00FF00', 'FFFFFF', 'FF0000'),\n",
        "        'position': (integer_style, '00FF00', 'FFFFFF', 'FF0000'),  # Inverti per 'avg position'\n",
        "        'weighted avg position': (integer_style, '00FF00', 'FFFFFF', 'FF0000'),\n",
        "        'tag title len': (thousands_style, 'FF0000', 'FFFFFF', 'FF0000'),\n",
        "        'new tag title': (thousands_style, 'FF0000', 'FFFFFF', 'FF0000'),\n",
        "        'diff': (thousands_style, 'FF0000', 'FFFFFF', 'FF0000'),\n",
        "\n",
        "    }\n",
        "    print('formatting')\n",
        "    # Applica la formattazione specifica a tutte le colonne desiderate in tutti i fogli\n",
        "    for sheet_name in workbook.sheetnames:\n",
        "        sheet = workbook[sheet_name]\n",
        "        \n",
        "        # Aggiungi gli stili al workbook se non sono già stati aggiunti\n",
        "        if thousands_style.name not in workbook.named_styles:\n",
        "            workbook.add_named_style(thousands_style)\n",
        "        if percent_style.name not in workbook.named_styles:\n",
        "            workbook.add_named_style(percent_style)\n",
        "        if integer_style.name not in workbook.named_styles:\n",
        "            workbook.add_named_style(integer_style)\n",
        "        \n",
        "        for col_info in sheet.iter_cols(min_row=1, max_row=sheet.max_row):\n",
        "            #print(f'Formatting {col_info} in {sheet}')\n",
        "            col_name = sheet.cell(row=1, column=col_info[0].column).value\n",
        "            if col_name and col_name.lower() in column_formats:\n",
        "                col_values = [cell.value for cell in col_info if isinstance(cell.value, (int, float))]\n",
        "                if col_values:  # Assicurati che ci siano valori numerici nella colonna\n",
        "                    min_val = min(col_values)\n",
        "                    max_val = max(col_values)\n",
        "                    mid_val = (min_val + max_val) / 2  # Calcolo del valore medio per il bianco\n",
        "\n",
        "                    # Formattazione condizionale con tre colori\n",
        "                    # Ottieni lo stile e i colori dalla mappatura\n",
        "                    style, start_color, mid_color, end_color = column_formats[col_name.lower()]\n",
        "\n",
        "                    # Formattazione condizionale con tre colori\n",
        "                    color_scale_rule = ColorScaleRule(start_type='num', start_value=min_val, start_color=start_color,\n",
        "                                                    mid_type='num', mid_value=mid_val, mid_color=mid_color,\n",
        "                                                    end_type='num', end_value=max_val, end_color=end_color)\n",
        "                    col_letter = col_info[0].column_letter\n",
        "                    sheet.conditional_formatting.add(f\"{col_letter}2:{col_letter}{sheet.max_row}\", color_scale_rule)\n",
        "\n",
        "                    # Applica lo stile di formattazione numerica\n",
        "                    for cell in col_info[1:]:  # Saltare l'intestazione\n",
        "                        cell.style = style\n",
        "\n",
        "    # Salva le modifiche al workbook\n",
        "    workbook.save(filepath)\n",
        "    print('DONE!')\n"
      ]
    }
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