{
  "cells": [
    {
      "cell_type": "code",
      "execution_count": null,
      "metadata": {
        "_cell_guid": "2a5bb5ba-de68-7276-7dda-52c392c8dc7f"
      },
      "outputs": [],
      "source": [
        "# This Python 3 environment comes with many helpful analytics libraries installed\n",
        "# It is defined by the kaggle/python docker image: https://github.com/kaggle/docker-python\n",
        "# For example, here's several helpful packages to load in \n",
        "\n",
        "import numpy as np # linear algebra\n",
        "import pandas as pd # data processing, CSV file I/O (e.g. pd.read_csv)\n",
        "\n",
        "# Input data files are available in the \"../input/\" directory.\n",
        "# For example, running this (by clicking run or pressing Shift+Enter) will list the files in the input directory\n",
        "\n",
        "from subprocess import check_output\n",
        "print(check_output([\"ls\", \"../input\"]).decode(\"utf8\"))\n",
        "\n",
        "# Any results you write to the current directory are saved as output."
      ]
    },
    {
      "cell_type": "code",
      "execution_count": null,
      "metadata": {
        "_cell_guid": "3d65ffee-08f2-31ec-7c56-e6fafabe3c97"
      },
      "outputs": [],
      "source": [
        "pd.read_csv('../input/clicks_train.csv').head()"
      ]
    },
    {
      "cell_type": "code",
      "execution_count": null,
      "metadata": {
        "_cell_guid": "b1c0761e-86b4-d470-79d6-c2bd16bdd776"
      },
      "outputs": [],
      "source": [
        "print (pd.read_csv('../input/clicks_train.csv').columns)\n",
        "print (pd.read_csv('../input/documents_categories.csv').columns)\n",
        "print (pd.read_csv('../input/documents_entities.csv').columns)\n",
        "print (pd.read_csv('../input/documents_meta.csv').columns)\n",
        "print (pd.read_csv('../input/documents_topics.csv').columns)\n",
        "print (pd.read_csv('../input/events.csv').columns)\n",
        "print (pd.read_csv('../input/page_views_sample.csv').columns)\n",
        "print (pd.read_csv('../input/promoted_content.csv').columns)\n",
        "print (pd.read_csv('../input/sample_submission.csv').columns)"
      ]
    },
    {
      "cell_type": "code",
      "execution_count": null,
      "metadata": {
        "_cell_guid": "c7cddd1f-e321-df7b-3b7b-219e2d427091"
      },
      "outputs": [],
      "source": [
        "df = pd.read_csv('../input/clicks_train.csv')"
      ]
    },
    {
      "cell_type": "code",
      "execution_count": null,
      "metadata": {
        "_cell_guid": "b37a38a9-fcbd-16dc-48c7-7e8075d46d01"
      },
      "outputs": [],
      "source": [
        "pd.summary(df)"
      ]
    },
    {
      "cell_type": "code",
      "execution_count": null,
      "metadata": {
        "_cell_guid": "ae9256dd-8248-bfe1-21ca-5f29d8599374"
      },
      "outputs": [],
      "source": ""
    }
  ],
  "metadata": {
    "_change_revision": 0,
    "_is_fork": false,
    "kernelspec": {
      "display_name": "Python 3",
      "language": "python",
      "name": "python3"
    },
    "language_info": {
      "codemirror_mode": {
        "name": "ipython",
        "version": 3
      },
      "file_extension": ".py",
      "mimetype": "text/x-python",
      "name": "python",
      "nbconvert_exporter": "python",
      "pygments_lexer": "ipython3",
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