{"nbformat_minor": 1, "metadata": {"kernelspec": {"display_name": "Python 3", "language": "python", "name": "python3"}, "language_info": {"mimetype": "text/x-python", "nbconvert_exporter": "python", "pygments_lexer": "ipython3", "name": "python", "file_extension": ".py", "version": "3.6.3", "codemirror_mode": {"name": "ipython", "version": 3}}}, "cells": [{"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", "\n", "import numpy as np # linear algebra\n", "import 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", "\n", "from subprocess import check_output\n", "print(check_output([\"ls\", \"../input\"]).decode(\"utf8\"))\n", "\n", "# Any results you write to the current directory are saved as output."], "outputs": [], "metadata": {"_cell_guid": "eba7fbb2-0faa-4e24-b2d4-bc1304b95a5f", "_uuid": "e9d667a08568d1e8a5c4e6292f8ecd22e25abfa4", "collapsed": true}, "execution_count": null, "cell_type": "code"}], "nbformat": 4}