texthero.ipynb

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  "metadata": {
    "colab": {
      "name": "texthero.ipynb",
      "provenance": [],
      "authorship_tag": "ABX9TyNR/W7cu+mlOCyE36lfkREg",
      "include_colab_link": true
    },
    "kernelspec": {
      "name": "python3",
      "display_name": "Python 3"
    },
    "language_info": {
      "name": "python"
    }
  },
  "cells": [
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "view-in-github",
        "colab_type": "text"
      },
      "source": [
        "<a href=\"https://colab.research.google.com/github/naashonomics/pylib_collab/blob/main/texthero.ipynb\" target=\"_parent\"><img src=\"https://colab.research.google.com/assets/colab-badge.svg\" alt=\"Open In Colab\"/></a>"
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "YJfKJ1KhDp3_",
        "outputId": "718c1e88-7f52-4332-b74d-8f5804493a00"
      },
      "source": [
        "!pip install texthero"
      ],
      "execution_count": 1,
      "outputs": [
        {
          "output_type": "stream",
          "text": [
            "Collecting texthero\n",
            "  Downloading https://files.pythonhosted.org/packages/1f/5a/a9d33b799fe53011de79d140ad6d86c440a2da1ae8a7b24e851ee2f8bde8/texthero-1.0.9-py3-none-any.whl\n",
            "Requirement already satisfied: spacy>=2.2.2 in /usr/local/lib/python3.7/dist-packages (from texthero) (2.2.4)\n",
            "Collecting nltk>=3.3\n",
            "\u001b[?25l  Downloading https://files.pythonhosted.org/packages/5e/37/9532ddd4b1bbb619333d5708aaad9bf1742f051a664c3c6fa6632a105fd8/nltk-3.6.2-py3-none-any.whl (1.5MB)\n",
            "\u001b[K     |████████████████████████████████| 1.5MB 27.5MB/s \n",
            "\u001b[?25hRequirement already satisfied: tqdm>=4.3 in /usr/local/lib/python3.7/dist-packages (from texthero) (4.41.1)\n",
            "Requirement already satisfied: scikit-learn>=0.22 in /usr/local/lib/python3.7/dist-packages (from texthero) (0.22.2.post1)\n",
            "Requirement already satisfied: pandas>=1.0.2 in /usr/local/lib/python3.7/dist-packages (from texthero) (1.1.5)\n",
            "Requirement already satisfied: gensim>=3.6.0 in /usr/local/lib/python3.7/dist-packages (from texthero) (3.6.0)\n",
            "Requirement already satisfied: plotly>=4.2.0 in /usr/local/lib/python3.7/dist-packages (from texthero) (4.4.1)\n",
            "Requirement already satisfied: numpy>=1.17 in /usr/local/lib/python3.7/dist-packages (from texthero) (1.19.5)\n",
            "Requirement already satisfied: matplotlib>=3.1.0 in /usr/local/lib/python3.7/dist-packages (from texthero) (3.2.2)\n",
            "Requirement already satisfied: wordcloud>=1.5.0 in /usr/local/lib/python3.7/dist-packages (from texthero) (1.5.0)\n",
            "Collecting unidecode>=1.1.1\n",
            "\u001b[?25l  Downloading https://files.pythonhosted.org/packages/9e/25/723487ca2a52ebcee88a34d7d1f5a4b80b793f179ee0f62d5371938dfa01/Unidecode-1.2.0-py2.py3-none-any.whl (241kB)\n",
            "\u001b[K     |████████████████████████████████| 245kB 40.5MB/s \n",
            "\u001b[?25hRequirement already satisfied: wasabi<1.1.0,>=0.4.0 in /usr/local/lib/python3.7/dist-packages (from spacy>=2.2.2->texthero) (0.8.2)\n",
            "Requirement already satisfied: murmurhash<1.1.0,>=0.28.0 in /usr/local/lib/python3.7/dist-packages (from spacy>=2.2.2->texthero) (1.0.5)\n",
            "Requirement already satisfied: cymem<2.1.0,>=2.0.2 in /usr/local/lib/python3.7/dist-packages (from spacy>=2.2.2->texthero) (2.0.5)\n",
            "Requirement already satisfied: preshed<3.1.0,>=3.0.2 in /usr/local/lib/python3.7/dist-packages (from spacy>=2.2.2->texthero) (3.0.5)\n",
            "Requirement already satisfied: setuptools in /usr/local/lib/python3.7/dist-packages (from spacy>=2.2.2->texthero) (56.1.0)\n",
            "Requirement already satisfied: plac<1.2.0,>=0.9.6 in /usr/local/lib/python3.7/dist-packages (from spacy>=2.2.2->texthero) (1.1.3)\n",
            "Requirement already satisfied: requests<3.0.0,>=2.13.0 in /usr/local/lib/python3.7/dist-packages (from spacy>=2.2.2->texthero) (2.23.0)\n",
            "Requirement already satisfied: srsly<1.1.0,>=1.0.2 in /usr/local/lib/python3.7/dist-packages (from spacy>=2.2.2->texthero) (1.0.5)\n",
            "Requirement already satisfied: catalogue<1.1.0,>=0.0.7 in /usr/local/lib/python3.7/dist-packages (from spacy>=2.2.2->texthero) (1.0.0)\n",
            "Requirement already satisfied: blis<0.5.0,>=0.4.0 in /usr/local/lib/python3.7/dist-packages (from spacy>=2.2.2->texthero) (0.4.1)\n",
            "Requirement already satisfied: thinc==7.4.0 in /usr/local/lib/python3.7/dist-packages (from spacy>=2.2.2->texthero) (7.4.0)\n",
            "Requirement already satisfied: joblib in /usr/local/lib/python3.7/dist-packages (from nltk>=3.3->texthero) (1.0.1)\n",
            "Requirement already satisfied: click in /usr/local/lib/python3.7/dist-packages (from nltk>=3.3->texthero) (7.1.2)\n",
            "Requirement already satisfied: regex in /usr/local/lib/python3.7/dist-packages (from nltk>=3.3->texthero) (2019.12.20)\n",
            "Requirement already satisfied: scipy>=0.17.0 in /usr/local/lib/python3.7/dist-packages (from scikit-learn>=0.22->texthero) (1.4.1)\n",
            "Requirement already satisfied: pytz>=2017.2 in /usr/local/lib/python3.7/dist-packages (from pandas>=1.0.2->texthero) (2018.9)\n",
            "Requirement already satisfied: python-dateutil>=2.7.3 in /usr/local/lib/python3.7/dist-packages (from pandas>=1.0.2->texthero) (2.8.1)\n",
            "Requirement already satisfied: six>=1.5.0 in /usr/local/lib/python3.7/dist-packages (from gensim>=3.6.0->texthero) (1.15.0)\n",
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            "Requirement already satisfied: retrying>=1.3.3 in /usr/local/lib/python3.7/dist-packages (from plotly>=4.2.0->texthero) (1.3.3)\n",
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            "Requirement already satisfied: cycler>=0.10 in /usr/local/lib/python3.7/dist-packages (from matplotlib>=3.1.0->texthero) (0.10.0)\n",
            "Requirement already satisfied: pyparsing!=2.0.4,!=2.1.2,!=2.1.6,>=2.0.1 in /usr/local/lib/python3.7/dist-packages (from matplotlib>=3.1.0->texthero) (2.4.7)\n",
            "Requirement already satisfied: pillow in /usr/local/lib/python3.7/dist-packages (from wordcloud>=1.5.0->texthero) (7.1.2)\n",
            "Requirement already satisfied: certifi>=2017.4.17 in /usr/local/lib/python3.7/dist-packages (from requests<3.0.0,>=2.13.0->spacy>=2.2.2->texthero) (2020.12.5)\n",
            "Requirement already satisfied: chardet<4,>=3.0.2 in /usr/local/lib/python3.7/dist-packages (from requests<3.0.0,>=2.13.0->spacy>=2.2.2->texthero) (3.0.4)\n",
            "Requirement already satisfied: idna<3,>=2.5 in /usr/local/lib/python3.7/dist-packages (from requests<3.0.0,>=2.13.0->spacy>=2.2.2->texthero) (2.10)\n",
            "Requirement already satisfied: urllib3!=1.25.0,!=1.25.1,<1.26,>=1.21.1 in /usr/local/lib/python3.7/dist-packages (from requests<3.0.0,>=2.13.0->spacy>=2.2.2->texthero) (1.24.3)\n",
            "Requirement already satisfied: importlib-metadata>=0.20; python_version < \"3.8\" in /usr/local/lib/python3.7/dist-packages (from catalogue<1.1.0,>=0.0.7->spacy>=2.2.2->texthero) (4.0.1)\n",
            "Requirement already satisfied: typing-extensions>=3.6.4; python_version < \"3.8\" in /usr/local/lib/python3.7/dist-packages (from importlib-metadata>=0.20; python_version < \"3.8\"->catalogue<1.1.0,>=0.0.7->spacy>=2.2.2->texthero) (3.7.4.3)\n",
            "Requirement already satisfied: zipp>=0.5 in /usr/local/lib/python3.7/dist-packages (from importlib-metadata>=0.20; python_version < \"3.8\"->catalogue<1.1.0,>=0.0.7->spacy>=2.2.2->texthero) (3.4.1)\n",
            "Installing collected packages: nltk, unidecode, texthero\n",
            "  Found existing installation: nltk 3.2.5\n",
            "    Uninstalling nltk-3.2.5:\n",
            "      Successfully uninstalled nltk-3.2.5\n",
            "Successfully installed nltk-3.6.2 texthero-1.0.9 unidecode-1.2.0\n"
          ],
          "name": "stdout"
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "Z3sHX4nKDy26",
        "outputId": "cfa4fc64-553b-49e8-e71b-de1bf99abb8b"
      },
      "source": [
        "import texthero\n",
        "help(texthero)"
      ],
      "execution_count": 2,
      "outputs": [
        {
          "output_type": "stream",
          "text": [
            "[nltk_data] Downloading package stopwords to /root/nltk_data...\n",
            "[nltk_data]   Unzipping corpora/stopwords.zip.\n"
          ],
          "name": "stderr"
        },
        {
          "output_type": "stream",
          "text": [
            "Help on package texthero:\n",
            "\n",
            "NAME\n",
            "    texthero - Texthero: python toolkit for text preprocessing, representation and visualization.\n",
            "\n",
            "PACKAGE CONTENTS\n",
            "    extend_pandas\n",
            "    nlp\n",
            "    preprocessing\n",
            "    representation\n",
            "    stop_words\n",
            "    stopwords\n",
            "    visualization\n",
            "\n",
            "DATA\n",
            "    Callable = typing.Callable\n",
            "    List = typing.List\n",
            "    Optional = typing.Optional\n",
            "    Set = typing.Set\n",
            "\n",
            "FILE\n",
            "    /usr/local/lib/python3.7/dist-packages/texthero/__init__.py\n",
            "\n",
            "\n"
          ],
          "name": "stdout"
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "kXDaIyaJD4B6"
      },
      "source": [
        "import pandas as pd \n",
        "text=\"It's a pleasant  night at Sunnyvale; at / (10:30) am\"\n",
        "series=pd.Series(text)"
      ],
      "execution_count": 4,
      "outputs": []
    },
    {
      "cell_type": "code",
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "y7lwoDEvEJTY",
        "outputId": "5a70c07a-23ed-4aee-87b0-c71f2af976ad"
      },
      "source": [
        "\n",
        "series"
      ],
      "execution_count": 5,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "0    It's a pleasant  night at Sunnyvale; at / (10:...\n",
              "dtype: object"
            ]
          },
          "metadata": {
            "tags": []
          },
          "execution_count": 5
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "0IE8ssDPEMid",
        "outputId": "e8805a84-5f18-4384-9fc7-384a0bf1c9e6"
      },
      "source": [
        "\n",
        "import texthero as hero\n",
        "\n",
        "hero.remove_digits(series)"
      ],
      "execution_count": 6,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "0    It's a pleasant  night at Sunnyvale; at / ( : ...\n",
              "dtype: object"
            ]
          },
          "metadata": {
            "tags": []
          },
          "execution_count": 6
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "_0agC8pgEUPY",
        "outputId": "33a6c550-d295-4a2a-ff78-1f9ae7e6fca0"
      },
      "source": [
        "hero.remove_punctuation(series)"
      ],
      "execution_count": 7,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "0    It s a pleasant  night at Sunnyvale  at    10 ...\n",
              "dtype: object"
            ]
          },
          "metadata": {
            "tags": []
          },
          "execution_count": 7
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "kQZQJFFPEVRw",
        "outputId": "438df9a4-f1ee-46b9-d967-128150bc38be"
      },
      "source": [
        "hero.remove_brackets(series)"
      ],
      "execution_count": 8,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "0    It's a pleasant  night at Sunnyvale; at /  am\n",
              "dtype: object"
            ]
          },
          "metadata": {
            "tags": []
          },
          "execution_count": 8
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "2gMn0A5KEY-I",
        "outputId": "a6ca694a-ae48-4bc7-db54-897bfa466cec"
      },
      "source": [
        "hero.remove_diacritics(series)"
      ],
      "execution_count": 9,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "0    It's a pleasant  night at Sunnyvale; at / (10:...\n",
              "dtype: object"
            ]
          },
          "metadata": {
            "tags": []
          },
          "execution_count": 9
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "7HKj28I7EduD",
        "outputId": "fccc94eb-802e-4729-dfe4-71cb23803d61"
      },
      "source": [
        "\n",
        "hero.remove_whitespace(series)"
      ],
      "execution_count": 10,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "0    It's a pleasant night at Sunnyvale; at / (10:3...\n",
              "dtype: object"
            ]
          },
          "metadata": {
            "tags": []
          },
          "execution_count": 10
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "Cp72gaMFEdxa",
        "outputId": "22353209-f32c-44d9-e061-4defef5ee4b4"
      },
      "source": [
        "hero.remove_stopwords(series)"
      ],
      "execution_count": 11,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "0    It'  pleasant  night  Sunnyvale;  / (10:30) \n",
              "dtype: object"
            ]
          },
          "metadata": {
            "tags": []
          },
          "execution_count": 11
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "Kbua-BkDEhzw",
        "outputId": "b380f5a6-32df-4ca0-8eef-7507efc75852"
      },
      "source": [
        "hero.clean(series)"
      ],
      "execution_count": 12,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "0    pleasant night sunnyvale\n",
              "dtype: object"
            ]
          },
          "metadata": {
            "tags": []
          },
          "execution_count": 12
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 195
        },
        "id": "dBVrP4a8Eh3A",
        "outputId": "45fd08ff-a681-4781-f556-b51d6e18baa8"
      },
      "source": [
        "df = pd.read_csv(\n",
        "   \"https://github.com/jbesomi/texthero/raw/master/dataset/bbcsport.csv\"\n",
        ")\n",
        "df.head()"
      ],
      "execution_count": 13,
      "outputs": [
        {
          "output_type": "execute_result",
          "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>text</th>\n",
              "      <th>topic</th>\n",
              "    </tr>\n",
              "  </thead>\n",
              "  <tbody>\n",
              "    <tr>\n",
              "      <th>0</th>\n",
              "      <td>Claxton hunting first major medal\\n\\nBritish h...</td>\n",
              "      <td>athletics</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>1</th>\n",
              "      <td>O'Sullivan could run in Worlds\\n\\nSonia O'Sull...</td>\n",
              "      <td>athletics</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>2</th>\n",
              "      <td>Greene sets sights on world title\\n\\nMaurice G...</td>\n",
              "      <td>athletics</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>3</th>\n",
              "      <td>IAAF launches fight against drugs\\n\\nThe IAAF ...</td>\n",
              "      <td>athletics</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>4</th>\n",
              "      <td>Dibaba breaks 5,000m world record\\n\\nEthiopia'...</td>\n",
              "      <td>athletics</td>\n",
              "    </tr>\n",
              "  </tbody>\n",
              "</table>\n",
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            ],
            "text/plain": [
              "                                                text      topic\n",
              "0  Claxton hunting first major medal\\n\\nBritish h...  athletics\n",
              "1  O'Sullivan could run in Worlds\\n\\nSonia O'Sull...  athletics\n",
              "2  Greene sets sights on world title\\n\\nMaurice G...  athletics\n",
              "3  IAAF launches fight against drugs\\n\\nThe IAAF ...  athletics\n",
              "4  Dibaba breaks 5,000m world record\\n\\nEthiopia'...  athletics"
            ]
          },
          "metadata": {
            "tags": []
          },
          "execution_count": 13
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 542
        },
        "id": "HfrpuqNSEh7R",
        "outputId": "34e7ff4b-92a0-4545-ac28-97fb93e45f4f"
      },
      "source": [
        "\n",
        "###PCA\n",
        "import texthero as hero\n",
        "import pandas as pd\n",
        "\n",
        "df = pd.read_csv(\n",
        "   \"https://github.com/jbesomi/texthero/raw/master/dataset/bbcsport.csv\"\n",
        ")\n",
        "\n",
        "df['pca'] = (\n",
        "   df['text']\n",
        "   .pipe(hero.clean)\n",
        "   .pipe(hero.tfidf)###vectorizing\n",
        "   .pipe(hero.pca)\n",
        ")\n",
        "hero.scatterplot(df, 'pca', color='topic', title=\"PCA BBC Sport news\")"
      ],
      "execution_count": 14,
      "outputs": [
        {
          "output_type": "display_data",
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              "      <td>[-0.04801445322810521, 0.05286443585256461]</td>\n",
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              "    <tr>\n",
              "      <th>734</th>\n",
              "      <td>Federer wins title in Rotterdam\\n\\nWorld numbe...</td>\n",
              "      <td>tennis</td>\n",
              "      <td>[-0.04944529011024591, 0.060125054133552555]</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>735</th>\n",
              "      <td>GB players warned over security\\n\\nBritain's D...</td>\n",
              "      <td>tennis</td>\n",
              "      <td>[-0.048706692935028155, 0.013770089409489556]</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>736</th>\n",
              "      <td>Sharapova overcomes tough Molik\\n\\nWimbledon c...</td>\n",
              "      <td>tennis</td>\n",
              "      <td>[-0.029087748594066893, 0.07146335755067912]</td>\n",
              "    </tr>\n",
              "  </tbody>\n",
              "</table>\n",
              "<p>737 rows × 3 columns</p>\n",
              "</div>"
            ],
            "text/plain": [
              "                                                  text  ...                                            pca\n",
              "0    Claxton hunting first major medal\\n\\nBritish h...  ...    [-0.09099189408291171, 0.10357781418366688]\n",
              "1    O'Sullivan could run in Worlds\\n\\nSonia O'Sull...  ...  [-0.0004729498887925908, 0.02489658125442612]\n",
              "2    Greene sets sights on world title\\n\\nMaurice G...  ...     [-0.11749722644630145, 0.1284739515178323]\n",
              "3    IAAF launches fight against drugs\\n\\nThe IAAF ...  ...    [-0.09137056111597706, 0.15407538222623324]\n",
              "4    Dibaba breaks 5,000m world record\\n\\nEthiopia'...  ...    [-0.09119627341587415, 0.13503644869489076]\n",
              "..                                                 ...  ...                                            ...\n",
              "732  Agassi into second round in Dubai\\n\\nFourth se...  ...     [-0.06654203407492167, 0.1088630711777171]\n",
              "733  Mauresmo fights back to win title\\n\\nWorld num...  ...    [-0.04801445322810521, 0.05286443585256461]\n",
              "734  Federer wins title in Rotterdam\\n\\nWorld numbe...  ...   [-0.04944529011024591, 0.060125054133552555]\n",
              "735  GB players warned over security\\n\\nBritain's D...  ...  [-0.048706692935028155, 0.013770089409489556]\n",
              "736  Sharapova overcomes tough Molik\\n\\nWimbledon c...  ...   [-0.029087748594066893, 0.07146335755067912]\n",
              "\n",
              "[737 rows x 3 columns]"
            ]
          },
          "metadata": {
            "tags": []
          },
          "execution_count": 15
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 542
        },
        "id": "NHuoNcO9E5BI",
        "outputId": "38e993c4-e8a2-4a7b-e324-617f05474858"
      },
      "source": [
        "import texthero as hero\n",
        "import pandas as pd\n",
        "\n",
        "df = pd.read_csv(\n",
        "    \"https://github.com/jbesomi/texthero/raw/master/dataset/bbcsport.csv\"\n",
        ")\n",
        "\n",
        "df['tfidf'] = (\n",
        "    df['text']\n",
        "    .pipe(hero.clean)\n",
        "    .pipe(hero.tfidf)\n",
        ")\n",
        "### Kmeans\n",
        "\n",
        "df['kmeans_labels'] = (\n",
        "    df['tfidf']\n",
        "    .pipe(hero.kmeans, n_clusters=5)\n",
        "    .astype(str)\n",
        ")\n",
        "\n",
        "df['pca'] = df['tfidf'].pipe(hero.pca)\n",
        "\n",
        "hero.scatterplot(df, 'pca', color='kmeans_labels', title=\"K-means BBC Sport news\")"
      ],
      "execution_count": 16,
      "outputs": [
        {
          "output_type": "display_data",
          "data": {
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