{"metadata":{"kernelspec":{"name":"python"},"language_info":{"name":"python","version":"3.5.1"}},"nbformat":4,"nbformat_minor":0,"cells":[{"metadata":{"_cell_guid":"e6dfa7b1-f792-bbf7-6f91-0b3ab4ae18ad","_active":false,"collapsed":false},"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)\nimport tensorflow as tf # tensorflow\nimport matplotlib.pyplot\n%matplotlib inline\n\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,"cell_type":"code","outputs":[]},{"metadata":{"_cell_guid":"e6dfa7b1-f792-bbf7-6f91-0b3ab4ae18ad","_active":false,"collapsed":false},"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,"cell_type":"code","outputs":[]}]}