SweetVIZDEMO.ipynb

{
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  "metadata": {
    "colab": {
      "name": "SweetVIZDEMO.ipynb",
      "provenance": [],
      "collapsed_sections": [],
      "toc_visible": true,
      "include_colab_link": true
    },
    "kernelspec": {
      "name": "python3",
      "display_name": "Python 3"
    }
  },
  "cells": [
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "view-in-github",
        "colab_type": "text"
      },
      "source": [
        "<a href=\"https://colab.research.google.com/github/datamongerbonny/analyzing-census-data/blob/master/SweetVIZDEMO.ipynb\" target=\"_parent\"><img src=\"https://colab.research.google.com/assets/colab-badge.svg\" alt=\"Open In Colab\"/></a>"
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "W7R0i5yKCjgU",
        "colab_type": "code",
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 294
        },
        "outputId": "4f788f98-e9bf-4f52-8f0c-e6f0f5fb258d"
      },
      "source": [
        "!pip install sweetviz"
      ],
      "execution_count": null,
      "outputs": [
        {
          "output_type": "stream",
          "text": [
            "Requirement already satisfied: sweetviz in /usr/local/lib/python3.6/dist-packages (1.0b5)\n",
            "Requirement already satisfied: importlib-resources>=1.2.0 in /usr/local/lib/python3.6/dist-packages (from sweetviz) (3.0.0)\n",
            "Requirement already satisfied: numpy>=1.16.0 in /usr/local/lib/python3.6/dist-packages (from sweetviz) (1.18.5)\n",
            "Requirement already satisfied: scipy>=1.3.2 in /usr/local/lib/python3.6/dist-packages (from sweetviz) (1.4.1)\n",
            "Requirement already satisfied: pandas!=1.0.0,!=1.0.1,!=1.0.2,>=0.25.3 in /usr/local/lib/python3.6/dist-packages (from sweetviz) (1.0.5)\n",
            "Requirement already satisfied: matplotlib>=3.1.3 in /usr/local/lib/python3.6/dist-packages (from sweetviz) (3.2.2)\n",
            "Requirement already satisfied: tqdm>=4.43.0 in /usr/local/lib/python3.6/dist-packages (from sweetviz) (4.48.0)\n",
            "Requirement already satisfied: jinja2>=2.11.1 in /usr/local/lib/python3.6/dist-packages (from sweetviz) (2.11.2)\n",
            "Requirement already satisfied: zipp>=0.4; python_version < \"3.8\" in /usr/local/lib/python3.6/dist-packages (from importlib-resources>=1.2.0->sweetviz) (3.1.0)\n",
            "Requirement already satisfied: pytz>=2017.2 in /usr/local/lib/python3.6/dist-packages (from pandas!=1.0.0,!=1.0.1,!=1.0.2,>=0.25.3->sweetviz) (2018.9)\n",
            "Requirement already satisfied: python-dateutil>=2.6.1 in /usr/local/lib/python3.6/dist-packages (from pandas!=1.0.0,!=1.0.1,!=1.0.2,>=0.25.3->sweetviz) (2.8.1)\n",
            "Requirement already satisfied: cycler>=0.10 in /usr/local/lib/python3.6/dist-packages (from matplotlib>=3.1.3->sweetviz) (0.10.0)\n",
            "Requirement already satisfied: pyparsing!=2.0.4,!=2.1.2,!=2.1.6,>=2.0.1 in /usr/local/lib/python3.6/dist-packages (from matplotlib>=3.1.3->sweetviz) (2.4.7)\n",
            "Requirement already satisfied: kiwisolver>=1.0.1 in /usr/local/lib/python3.6/dist-packages (from matplotlib>=3.1.3->sweetviz) (1.2.0)\n",
            "Requirement already satisfied: MarkupSafe>=0.23 in /usr/local/lib/python3.6/dist-packages (from jinja2>=2.11.1->sweetviz) (1.1.1)\n",
            "Requirement already satisfied: six>=1.5 in /usr/local/lib/python3.6/dist-packages (from python-dateutil>=2.6.1->pandas!=1.0.0,!=1.0.1,!=1.0.2,>=0.25.3->sweetviz) (1.15.0)\n"
          ],
          "name": "stdout"
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "AR4P_XS3C4bp",
        "colab_type": "code",
        "colab": {}
      },
      "source": [
        "import pandas as pd"
      ],
      "execution_count": null,
      "outputs": []
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "N6Heqk3rDBQr",
        "colab_type": "code",
        "colab": {}
      },
      "source": [
        "df = pd.read_csv('/content/compas-scores-raw.csv')"
      ],
      "execution_count": null,
      "outputs": []
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "WvjA71r3GP13",
        "colab_type": "code",
        "colab": {}
      },
      "source": [
        "df = pd.read_csv('CENSUSTESTDATA.csv')"
      ],
      "execution_count": null,
      "outputs": []
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "DuOkneGsaRQ1",
        "colab_type": "code",
        "colab": {}
      },
      "source": [
        "df = pd.read_csv('/content/nc_greensboro_2020_04_01.csv')"
      ],
      "execution_count": null,
      "outputs": []
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "ZQPN63w6ZDrH",
        "colab_type": "code",
        "colab": {}
      },
      "source": [
        "df = pd.read_csv('MEPSTFFNA.csv')"
      ],
      "execution_count": null,
      "outputs": []
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "Z-tcurNjxp5y",
        "colab_type": "text"
      },
      "source": [
        "# New Section"
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "1InIqJbcxvz0",
        "colab_type": "code",
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 34
        },
        "outputId": "35af367c-a7d0-4140-f1f6-21bcf070be8f"
      },
      "source": [
        "from google.colab import drive\n",
        "drive.mount('/content/drive')"
      ],
      "execution_count": null,
      "outputs": [
        {
          "output_type": "stream",
          "text": [
            "Drive already mounted at /content/drive; to attempt to forcibly remount, call drive.mount(\"/content/drive\", force_remount=True).\n"
          ],
          "name": "stdout"
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "6XwcQoh0DH5Q",
        "colab_type": "code",
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 1000
        },
        "outputId": "93e3f160-5930-49b4-86ea-ddcf19b7e2bb"
      },
      "source": [
        "import sweetviz as sv\n",
        "df = sv.analyze(df)\n",
        "df.show_html('CENSUSTESTDATA.html')"
      ],
      "execution_count": null,
      "outputs": [
        {
          "output_type": "stream",
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            ":FEATURES DONE:                    |█████████████████████| [100%]   00:24  -> (00:00 left)\n",
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            ":PAIRWISE DONE:                    |█████████████████████| [100%]   09:58  -> (00:00 left)\n"
          ],
          "name": "stderr"
        },
        {
          "output_type": "stream",
          "text": [
            "Creating Associations graph... DONE!\n",
            "Report CENSUSTESTDATA.html was generated! NOTEBOOK/COLAB USERS: no browser will pop up, the report is saved in your notebook/colab files.\n"
          ],
          "name": "stdout"
        }
      ]
    }
  ]
}