{"cells":[{"cell_type":"code","execution_count":null,"metadata":{"_cell_guid":"cb71131f-bd10-8890-ad64-b26a1a794576"},"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":"f6d20d12-ddee-8296-af34-aa1ceb84d229"},"outputs":[],"source":"test = pd.read_csv('../input/clicks_test.csv')\ntrain = pd.read_csv('../input/clicks_train.csv')\nsubmission = pd.read_csv('../input/sample_submission.csv')\n\ntrain_ad = set(train['display_id'].unique())\ntest_ad = set(test['display_id'].unique())\nsub_ad = set(submission['display_id'].unique())\n\nprint(len(test_ad))\nprint(len(sub_ad))\nprint(len(test_ad.intersection(sub_ad)))\n"},{"cell_type":"code","execution_count":null,"metadata":{"_cell_guid":"0f784c14-74eb-cbaf-bd90-4c41f1fc05c8"},"outputs":[],"source":"print(test.loc[test['ad_id'].isnull(),:])"},{"cell_type":"code","execution_count":null,"metadata":{"_cell_guid":"82e34056-90c0-983e-11e3-a506e9da0088"},"outputs":[],"source":"print(test['display_id'].value_counts())"}],"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}