{"cells":[{"metadata":{"_cell_guid":"b1076dfc-b9ad-4769-8c92-a6c4dae69d19","_kg_hide-input":true,"_uuid":"8f2839f25d086af736a60e9eeb907d3b93b6e0e5"},"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\nimport os\nprint(os.listdir(\"../input\"))\ndata = pd.read_csv(\"../input/train_sample.csv\")\ndata.head()\n\n# Any results you write to the current directory are saved as output.","execution_count":null,"outputs":[]},{"metadata":{"_cell_guid":"79c7e3d0-c299-4dcb-8224-4455121ee9b0","collapsed":true,"_uuid":"d629ff2d2480ee46fbb7e2d37f6b5fab8052498a"},"cell_type":"code","source":"","execution_count":null,"outputs":[]}],"metadata":{"language_info":{"pygments_lexer":"ipython3","mimetype":"text/x-python","name":"python","codemirror_mode":{"version":3,"name":"ipython"},"version":"3.6.4","file_extension":".py","nbconvert_exporter":"python"},"kernelspec":{"display_name":"Python 3","language":"python","name":"python3"}},"nbformat_minor":1,"nbformat":4}