{"cells":[{"cell_type":"code","execution_count":null,"metadata":{"_cell_guid":"96cd225e-11f3-5760-ce8a-bc995f7b4c47"},"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\nimport numpy as np # linear algebra\nimport 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\nfrom subprocess import check_output\nprint(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":"437ec07e-e519-b3a4-d9e8-6f85001c89c3"},"outputs":[],"source":"clicks_test_df = pd.read_csv(r'../input/clicks_test.csv',nrows=10000)\nclicks_train_df = pd.read_csv(r'../input/clicks_train.csv',nrows=10000)\ndocuments_categories_df = pd.read_csv(r'../input/documents_categories.csv',nrows=10000)\ndocuments_entities_df = pd.read_csv(r'../input/documents_entities.csv',nrows=10000)\ndocuments_meta_df = pd.read_csv(r'../input/documents_meta.csv',nrows=10000)\ndocuments_topics_df = pd.read_csv(r'../input/documents_topics.csv',nrows=10000)\nevents_df = pd.read_csv(r'../input/events.csv',nrows=10000)\npage_views_sample_df = pd.read_csv(r'../input/page_views_sample.csv',nrows=10000)\npromoted_content_df = pd.read_csv(r'../input/promoted_content.csv',nrows=10000)"},{"cell_type":"code","execution_count":null,"metadata":{"_cell_guid":"4d88740f-fb11-8d7c-2e5d-1461d40b004c"},"outputs":[],"source":"print(\"clicks_test_df:          {}\".format(list(clicks_test_df.columns)))\nprint(\"clicks_train_df:         {}\".format(list(clicks_train_df.columns)))\nprint(\"documents_categories_df: {}\".format(list(documents_categories_df.columns)))\nprint(\"documents_entities_df:   {}\".format(list(documents_entities_df.columns)))\nprint(\"documents_meta_df:       {}\".format(list(documents_meta_df.columns)))\nprint(\"documents_topics_df:     {}\".format(list(documents_topics_df.columns)))\nprint(\"events_df:               {}\".format(list(events_df.columns)))\nprint(\"page_views_sample_df:    {}\".format(list(page_views_sample_df.columns)))\nprint(\"promoted_content_df:     {}\".format(list(promoted_content_df.columns)))"},{"cell_type":"code","execution_count":null,"metadata":{"_cell_guid":"01b8056a-5b1f-bac5-5065-f38dc5fb0278"},"outputs":[],"source":"clicks_train_df.head()"},{"cell_type":"code","execution_count":null,"metadata":{"_cell_guid":"2f7a91f6-1765-1b6b-48a3-afa0b0576504"},"outputs":[],"source":"events_df.head()"},{"cell_type":"code","execution_count":null,"metadata":{"_cell_guid":"46a3193a-57d7-f378-e6d0-48f60ce8f580"},"outputs":[],"source":"page_views_sample_df"}],"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","version":"3.5.2"}},"nbformat":4,"nbformat_minor":0}