{"cells":[{"cell_type":"code","execution_count":null,"metadata":{"collapsed":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)\nprint('Loading data ...')\ndf_train = pd.read_csv('../input/train.csv',\n                       usecols=['row_id','x','y','time','place_id','accuracy'], \n                       index_col = 0)\ndf_test = pd.read_csv('../input/test.csv',\n                      usecols=['row_id','x','y','time','accuracy'],\n                      index_col = 0)\n"},{"cell_type":"code","execution_count":null,"metadata":{"collapsed":false},"outputs":[],"source":""}],"metadata":{"kernelspec":{"display_name":"Python 3","language":"python","name":"python3"}},"nbformat":4,"nbformat_minor":0}