{"nbformat_minor": 1, "nbformat": 4, "cells": [{"outputs": [], "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."], "execution_count": null, "metadata": {"_uuid": "549311675924f4f4144296b5736ffdeb9a40043e", "_cell_guid": "596d5d65-46fe-4a7c-8d13-fb5ca9227e57"}, "cell_type": "code"}, {"outputs": [], "source": [], "execution_count": null, "metadata": {"_uuid": "fae930c26957d900d3151694d95dcc3935729afc", "_cell_guid": "b47cf448-317f-4007-9317-e4d364f5a02f"}, "cell_type": "code"}], "metadata": {"kernelspec": {"display_name": "Python 3", "language": "python", "name": "python3"}, "language_info": {"nbconvert_exporter": "python", "file_extension": ".py", "name": "python", "mimetype": "text/x-python", "codemirror_mode": {"version": 3, "name": "ipython"}, "pygments_lexer": "ipython3", "version": "3.6.3"}}}