{"metadata":{"language_info":{"version":"3","name":"python"},"kernelspec":{"language":"python","name":"python3","display_name":"Python 3"}},"cells":[{"metadata":{"_cell_guid":"9248c84f-d988-407d-bd9b-02a6002f5751","_uuid":"0c0c966487178ad13662c7784a926d2c880e30c8"},"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":[]}],"nbformat":4,"nbformat_minor":0}