{"cells":[{"metadata":{"_cell_guid":"74c46061-c516-4c91-8a6e-a16d59d7bfa9","_execution_state":"idle","_uuid":"a601727a7e19a7f5c8d2f0dfdc30d459c718beb0","trusted":true},"cell_type":"code","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.","execution_count":null,"outputs":[]}],"metadata":{"language_info":{"version":"3.6.1","nbconvert_exporter":"python","name":"python","file_extension":".py","mimetype":"text/x-python","pygments_lexer":"ipython3","codemirror_mode":{"version":3,"name":"ipython"}},"kernelspec":{"language":"python","display_name":"Python 3","name":"python3"}},"nbformat":4,"nbformat_minor":1}