{"cells":[{"cell_type":"markdown","metadata":{"_cell_guid":"db61ffb1-3f61-2cf9-1d61-83de379ea1a6"},"source":""},{"cell_type":"code","execution_count":null,"metadata":{"_cell_guid":"ae097169-504d-a543-b56f-a54f948a27b2"},"outputs":[],"source":""},{"cell_type":"code","execution_count":null,"metadata":{"_cell_guid":"00bb0d07-00c6-1e8b-1d71-06c823e088d4"},"outputs":[],"source":"# This R environment comes with all of CRAN preinstalled, as well as many other helpful packages\n# The environment is defined by the kaggle/rstats docker image: https://github.com/kaggle/docker-rstats\n# For example, here's several helpful packages to load in \n\nlibrary(ggplot2) # Data visualization\nlibrary(readr) # CSV file I/O, e.g. the read_csv function\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\nsystem(\"ls ../input\")\n\n# Any results you write to the current directory are saved as output."},{"cell_type":"code","execution_count":null,"metadata":{"_cell_guid":"07a3d647-0c33-b348-69b7-85cb117ab98a"},"outputs":[],"source":""}],"metadata":{"_change_revision":0,"_is_fork":false,"kernelspec":{"display_name":"R","language":"R","name":"ir"},"language_info":{"codemirror_mode":"r","file_extension":".r","mimetype":"text/x-r-source","name":"R","pygments_lexer":"r","version":"3.3.3"}},"nbformat":4,"nbformat_minor":0}