{"nbformat_minor": 0, "cells": [{"execution_count": null, "cell_type": "code", "metadata": {"collapsed": false, "_uuid": "fda14eba9df2cc0f6c1f2fa3f338d003e9540f2a", "_execution_state": "idle"}, "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\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, "cell_type": "code", "metadata": {"collapsed": false, "_uuid": "b83a2dbab8721300de10f1d2784112080b4fe053", "_execution_state": "idle", "trusted": false}, "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\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, "cell_type": "code", "metadata": {"collapsed": false, "_uuid": "53576f3d19c6203af35441405780213a22952267", "_execution_state": "idle"}, "outputs": [], "source": ""}, {"execution_count": null, "cell_type": "code", "metadata": {"collapsed": false, "_uuid": "81e03af4b13f64c6e4f0fa90ad9528aa2ee746a0", "_execution_state": "idle"}, "outputs": [], "source": ""}, {"execution_count": null, "cell_type": "code", "metadata": {"collapsed": false, "_uuid": "f15e5a27b0b3cd627e5606e7754bbfa05c0f9f4f", "_execution_state": "idle"}, "outputs": [], "source": ""}], "metadata": {"kernelspec": {"language": "python", "display_name": "Python 3", "name": "python3"}, "language_info": {"name": "python", "file_extension": ".py", "nbconvert_exporter": "python", "version": "3.6.1", "pygments_lexer": "ipython3", "mimetype": "text/x-python", "codemirror_mode": {"name": "ipython", "version": 3}}}, "nbformat": 4}