{"metadata":{"kernelspec":{"name":"python3","display_name":"Python 3","language":"python"},"language_info":{"pygments_lexer":"ipython3","version":"3.6.0","name":"python","mimetype":"text/x-python","codemirror_mode":{"version":3,"name":"ipython"},"nbconvert_exporter":"python","file_extension":".py"}},"nbformat":4,"nbformat_minor":0,"cells":[{"cell_type":"code","metadata":{"_uuid":"a96454e2f871c6bb762cf69d1b3244fbd7f34a5c","_execution_state":"busy"},"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.","outputs":[],"execution_count":null},{"metadata":{"collapsed":false,"_uuid":"b22d3197b49b6532ecf724cdc440648ef252dbdb","_execution_state":"idle"},"source":"","outputs":[],"cell_type":"code","execution_count":null}]}