{"nbformat_minor": 0, "cells": [{"outputs": [], "metadata": {"_uuid": "332561433e417dc7e7a7fdac37bf516475266b44", "_cell_guid": "28fc7df5-4b35-4bd1-aaef-8f03f71fef49"}, "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\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}], "metadata": {"language_info": {"name": "python", "version": "3"}, "kernelspec": {"language": "python", "name": "python3", "display_name": "Python 3"}}, "nbformat": 4}