{"cells":[{"cell_type":"code","execution_count":null,"metadata":{"_cell_guid":"9b895da4-b05c-a6a0-04ba-0319482498df"},"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."},{"cell_type":"code","execution_count":null,"metadata":{"_cell_guid":"71f915fa-9b5d-bf74-4fba-361708c44dba"},"outputs":[],"source":"cd ../input"},{"cell_type":"code","execution_count":null,"metadata":{"_cell_guid":"e31a8c0a-5107-1448-c2d6-3ae7e653d025"},"outputs":[],"source":"ll -h"},{"cell_type":"code","execution_count":null,"metadata":{"_cell_guid":"07cdb55b-d911-5c4a-baaa-5c6461f1f34e"},"outputs":[],"source":"sample = open(\"sample_submission.csv\", \"r\").readlines()\nsample[:5]"},{"cell_type":"code","execution_count":null,"metadata":{"_cell_guid":"b646db41-6eef-cebe-760b-a9abc806ff1b"},"outputs":[],"source":"import os\nos.listdir()\ndata = dict()\nfor name in os.listdir():\n    true_name = name[:-4]\n    data[true_name] = []\n    f = open(name, 'r')\n    for i in range(50):\n        data[true_name].append(f.readline())\n    f.close()"},{"cell_type":"code","execution_count":null,"metadata":{"_cell_guid":"5cee8dd8-1e75-7950-3497-b85dac9e0e0e"},"outputs":[],"source":"data['train_categorical'][0]"},{"cell_type":"code","execution_count":null,"metadata":{"_cell_guid":"d73b34d2-d0ce-9997-042d-74176d8ab2b6"},"outputs":[],"source":"data['train_numeric'][0]"},{"cell_type":"code","execution_count":null,"metadata":{"_cell_guid":"b8237595-4822-51e0-01bc-9695afc9d1e5"},"outputs":[],"source":"data['train_date'][0]"},{"cell_type":"code","execution_count":null,"metadata":{"_cell_guid":"d8abf33b-609b-ac10-f2cb-bfd9423e86ce"},"outputs":[],"source":"import xgboost"},{"cell_type":"code","execution_count":null,"metadata":{"_cell_guid":"9c1c7841-f615-82f6-d608-8f9971eccd4b"},"outputs":[],"source":"help(xgboost)"},{"cell_type":"code","execution_count":null,"metadata":{"_cell_guid":"d86c9058-cf6b-c5a5-1e8e-9d59803a9d65"},"outputs":[],"source":"df = pd.read_csv(\"train_numeric.csv\")"},{"cell_type":"code","execution_count":null,"metadata":{"_cell_guid":"bf64af16-506b-dbbe-2703-85157987681f"},"outputs":[],"source":""}],"metadata":{"_change_revision":0,"_is_fork":false,"kernelspec":{"display_name":"Python 3","language":"python","name":"python3"},"language_info":{"codemirror_mode":{"name":"ipython","version":3},"file_extension":".py","mimetype":"text/x-python","name":"python","nbconvert_exporter":"python","pygments_lexer":"ipython3","version":"3.5.2"}},"nbformat":4,"nbformat_minor":0}