{"cells":[{"metadata":{"_uuid":"8f2839f25d086af736a60e9eeb907d3b93b6e0e5","_cell_guid":"b1076dfc-b9ad-4769-8c92-a6c4dae69d19","trusted":true},"cell_type":"code","source":"#https://www.kaggle.com/c/flavours-of-physics/data\n\n# 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 \nimport math\nimport seaborn as sns\nsns.set(style=\"whitegrid\", color_codes=True)\n\n\nfrom wordcloud import WordCloud, STOPWORDS\n\nimport pandas as pd # data processing, CSV file I/O (e.g. pd.read_csv)\nimport numpy as np # linear algebra\nimport matplotlib \nimport matplotlib.pyplot as plt\nimport sklearn\n%matplotlib inline\nimport matplotlib.pyplot as plt \nplt.rcParams[\"figure.figsize\"] = [16, 12]\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.\nfilenames = check_output([\"ls\", \"../input/\"]).decode(\"utf8\").strip()\n# helpful character encoding module\nimport chardet\n\n# set seed for reproducibility\nnp.random.seed(0)","execution_count":1,"outputs":[]},{"metadata":{"_uuid":"d629ff2d2480ee46fbb7e2d37f6b5fab8052498a","_cell_guid":"79c7e3d0-c299-4dcb-8224-4455121ee9b0","collapsed":true,"trusted":false},"cell_type":"code","source":"","execution_count":null,"outputs":[]}],"metadata":{"kernelspec":{"display_name":"Python 3","language":"python","name":"python3"},"language_info":{"name":"python","version":"3.6.5","mimetype":"text/x-python","codemirror_mode":{"name":"ipython","version":3},"pygments_lexer":"ipython3","nbconvert_exporter":"python","file_extension":".py"}},"nbformat":4,"nbformat_minor":1}