From e6c91c2f9cdceae44c3ff78dba91225cca743152 Mon Sep 17 00:00:00 2001 From: Natalia Laban Date: Sat, 27 May 2023 16:17:47 +0100 Subject: [PATCH] [Lab | Feature engineering] Natalia --- Feature engineering.ipynb | 581 ++++++++++++++++++++++++++++++++++++++ 1 file changed, 581 insertions(+) create mode 100644 Feature engineering.ipynb diff --git a/Feature engineering.ipynb b/Feature engineering.ipynb new file mode 100644 index 0000000..7cdf78d --- /dev/null +++ b/Feature engineering.ipynb @@ -0,0 +1,581 @@ +{ + "cells": [ + { + "cell_type": "code", + "execution_count": null, + "id": "73fa5df2-74ce-4106-969c-433562f60dfc", + "metadata": {}, + "outputs": [], + "source": [ + "#Lab | Feature engineering" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "id": "636a6540-ac88-453e-a8fc-d9236211deb4", + "metadata": {}, + "outputs": [], + "source": [ + "#Instructions\n", + "#Here we will work on cleaning some of the other columns in the dataset using the techniques that we used before in the lessons.\n", + "\n", + "#Check for null values in the numerical columns.\n", + "#Use appropriate methods to clean the columns GEOCODE2, WEALTH1, ADI, DMA,and MSA.\n", + "#Use appropriate EDA technique where ever necessary." + ] + }, + { + "cell_type": "code", + "execution_count": 1, + "id": "5564da15-a0ee-44ca-b991-36749f9cadf6", + "metadata": {}, + "outputs": [], + "source": [ + "import pandas as pd\n", + "import numpy as np\n", + "import matplotlib.pyplot as plt\n", + "import seaborn as sns" + ] + }, + { + "cell_type": "code", + "execution_count": 2, + "id": "bc26fff4-b853-4ebc-ab9e-068da8c56fc5", + "metadata": {}, + "outputs": [], + "source": [ + "categorical = pd.read_csv('categorical.csv')\n", + "numerical2 = pd.read_csv('numerical2.csv')\n", + "targets = pd.read_csv('targets.csv')" + ] + }, + { + "cell_type": "code", + "execution_count": 3, + "id": "4bd5ee32-31f9-4269-af20-5df0f7b5dfa7", + "metadata": {}, + "outputs": [ + { + "data": { + "text/html": [ + "
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column_namenulls
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136ADI0.001383
137DMA0.001383
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" + ], + "text/plain": [ + " column_name nulls\n", + "5 WEALTH1 0.468830\n", + "315 NEXTDATE 0.104526\n", + "135 MSA 0.001383\n", + "136 ADI 0.001383\n", + "137 DMA 0.001383" + ] + }, + "execution_count": 3, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "df = pd.DataFrame(numerical2.isna().sum()/len(numerical2)).reset_index()\n", + "df.columns = ['column_name','nulls']\n", + "df[df['nulls']>0].sort_values(by='nulls',ascending=False)" + ] + }, + { + "cell_type": "code", + "execution_count": 9, + "id": "8e152d6a-84e2-4a84-b22e-49ad29bdfa73", + "metadata": {}, + "outputs": [ + { + "data": { + "text/plain": [ + "9.0 7585\n", + "8.0 6793\n", + "7.0 6198\n", + "6.0 5825\n", + "5.0 5280\n", + "4.0 4810\n", + "3.0 4237\n", + "2.0 4085\n", + "1.0 3454\n", + "0.0 2413\n", + "Name: WEALTH1, dtype: int64" + ] + }, + "execution_count": 9, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "numerical2['WEALTH1'].value_counts()" + ] + }, + { + "cell_type": "code", + "execution_count": 35, + "id": "8ecc71f7-3c07-4ad1-b9fe-4a4010051a04", + "metadata": {}, + "outputs": [], + "source": [ + "numerical2['WEALTH1'] = numerical2['WEALTH1'].fillna(round(numerical2['WEALTH1'].mode().values[0]))" + ] + }, + { + "cell_type": "code", + "execution_count": 36, + "id": "40dd92ea-4b8c-482f-b9c8-49188716b530", + "metadata": {}, + "outputs": [ + { + "data": { + "text/plain": [ + "" + ] + }, + "execution_count": 36, + "metadata": {}, + "output_type": "execute_result" + }, + { + "data": { + "image/png": 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\n", + "text/plain": [ + "
" + ] + }, + "metadata": {}, + "output_type": "display_data" + } + ], + "source": [ + "sns.histplot(numerical2['WEALTH1'])" + ] + }, + { + "cell_type": "code", + "execution_count": 10, + "id": "17d5476f-caab-48c9-a70e-5baced012745", + "metadata": {}, + "outputs": [ + { + "data": { + "text/plain": [ + "9504.0 2253\n", + "9412.0 1970\n", + "8703.0 1959\n", + "9512.0 1870\n", + "8612.0 1688\n", + " ... \n", + "7711.0 1\n", + "8407.0 1\n", + "7211.0 1\n", + "7810.0 1\n", + "8412.0 1\n", + "Name: NEXTDATE, Length: 188, dtype: int64" + ] + }, + "execution_count": 10, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "numerical2['NEXTDATE'].value_counts()" + ] + }, + { + "cell_type": "code", + "execution_count": 20, + "id": "1a157280-007e-4c61-9dbf-fa4819c871f6", + "metadata": {}, + "outputs": [], + "source": [ + "numerical2['NEXTDATE'] = numerical2['NEXTDATE'].fillna(round(numerical2['NEXTDATE'].mean()))" + ] + }, + { + "cell_type": "code", + "execution_count": 21, + "id": "df68b62f-01f5-4f7e-a09c-31548a5e130b", + "metadata": {}, + "outputs": [ + { + "data": { + "text/plain": [ + "" + ] + }, + "execution_count": 21, + "metadata": {}, + "output_type": "execute_result" + }, + { + "data": { + "image/png": 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\n", 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"b2623e7d-f191-48fb-993c-9036b6f68a57", + "metadata": {}, + "outputs": [ + { + "data": { + "text/plain": [ + "" + ] + }, + "execution_count": 31, + "metadata": {}, + "output_type": "execute_result" + }, + { + "data": { + "image/png": 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\n", + "text/plain": [ + "
" + ] + }, + "metadata": {}, + "output_type": "display_data" + } + ], + "source": [ + "sns.histplot(numerical2['MSA'])" + ] + }, + { + "cell_type": "code", + "execution_count": 13, + "id": "a9c4a3c2-76d1-4067-ac70-7b6561f6bfaa", + "metadata": {}, + "outputs": [ + { + "data": { + "text/plain": [ + "13.0 7296\n", + "51.0 4622\n", + "65.0 3765\n", + "57.0 2836\n", + "105.0 2617\n", + " ... \n", + "651.0 1\n", + "103.0 1\n", + "601.0 1\n", + "161.0 1\n", + "147.0 1\n", + "Name: ADI, Length: 204, dtype: int64" + ] + }, + "execution_count": 13, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "numerical2['ADI'].value_counts() " + ] + }, + { + "cell_type": "code", + "execution_count": 32, + "id": "162ac881-2fe8-4877-bc88-7c2bd7fb7750", + "metadata": {}, + "outputs": [], + "source": [ + "numerical2['ADI'] = numerical2['ADI'].fillna(round(numerical2['ADI'].mean()))" + ] + }, + { + "cell_type": "code", + "execution_count": 33, + "id": "24aabfaa-0e1c-466f-b0a8-76ab357ff3c8", + "metadata": {}, + "outputs": [ + { + "data": { + "text/plain": [ + "" + ] + }, + "execution_count": 33, + "metadata": {}, + "output_type": "execute_result" + }, + { + "data": { + "image/png": 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\n", + "text/plain": [ + "
" + ] + }, + "metadata": {}, + "output_type": "display_data" + } + ], + "source": [ + "sns.histplot(numerical2['ADI'])" + ] + }, + { + "cell_type": "code", + "execution_count": 14, + "id": "e4a7d6d3-3162-45d6-b159-cdadcfeee3ab", + "metadata": {}, + "outputs": [ + { + "data": { + "text/plain": [ + "803.0 7296\n", + "602.0 4632\n", + "807.0 3765\n", + "505.0 2839\n", + "819.0 2588\n", + " ... \n", + "569.0 1\n", + "554.0 1\n", + "584.0 1\n", + "552.0 1\n", + "516.0 1\n", + "Name: DMA, Length: 206, dtype: int64" + ] + }, + "execution_count": 14, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "numerical2['DMA'].value_counts() " + ] + }, + { + "cell_type": "code", + "execution_count": 37, + "id": "8e3f901e-3a70-49e7-b64d-7ac534c3b1c2", + "metadata": {}, + "outputs": [], + "source": [ + "numerical2['DMA'] = numerical2['DMA'].fillna(round(numerical2['DMA'].mean()))" + ] + }, + { + "cell_type": "code", + "execution_count": 38, + "id": "e48c2159-5f45-42ca-ab0a-3c08ddf5641c", + "metadata": {}, + "outputs": [ + { + "data": { + "text/plain": [ + "" + ] + }, + "execution_count": 38, + "metadata": {}, + "output_type": "execute_result" + }, + { + "data": { + "image/png": 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