{"cells":[{"cell_type":"code","execution_count":null,"metadata":{"_cell_guid":"a986bcb1-3a98-21cd-e6af-4bfd3eb1bfb4"},"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":"28ea682c-93d5-d055-aa85-bb9177a5b54a"},"outputs":[],"source":"train = pd.read_csv('../input/train.csv', nrows=1000)"},{"cell_type":"code","execution_count":null,"metadata":{"_cell_guid":"d4e5950b-b4dd-4a73-adb3-c93ff739ed1c"},"outputs":[],"source":"train"},{"cell_type":"code","execution_count":null,"metadata":{"_cell_guid":"e0cef179-f1a8-5e1b-342e-d8976eb3eb00"},"outputs":[],"source":"product = pd.read_csv('../input/producto_tabla.csv')"},{"cell_type":"code","execution_count":null,"metadata":{"_cell_guid":"8f9272a2-7258-7691-bf26-f006a04045fb"},"outputs":[],"source":"product"},{"cell_type":"code","execution_count":null,"metadata":{"_cell_guid":"216e2937-7821-9012-5367-623e6b5c2c7d"},"outputs":[],"source":"town_state = pd.read_csv('../input/town_state.csv')"},{"cell_type":"code","execution_count":null,"metadata":{"_cell_guid":"208f5b2b-36ea-1a83-5a2f-cc50bc72a876"},"outputs":[],"source":"town_state"},{"cell_type":"code","execution_count":null,"metadata":{"_cell_guid":"f871613d-d886-99ed-d9e8-607df7d668b2"},"outputs":[],"source":"client = pd.read_csv('../input/cliente_tabla.csv')"},{"cell_type":"code","execution_count":null,"metadata":{"_cell_guid":"0e1ce416-3c95-23da-f46e-d2dc12a4c6ed"},"outputs":[],"source":"client"},{"cell_type":"code","execution_count":null,"metadata":{"_cell_guid":"7a079f45-2bd1-654a-0a1e-2ef65862bd83"},"outputs":[],"source":"test = pd.read_csv('../input/test.csv', nrows=20)"},{"cell_type":"code","execution_count":null,"metadata":{"_cell_guid":"0f8142ad-1e24-c7fa-302f-2a371ef37e11"},"outputs":[],"source":"test"},{"cell_type":"code","execution_count":null,"metadata":{"_cell_guid":"b2251330-042e-6fb6-0ea9-4b33fd32a564"},"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":"3.6.0"}},"nbformat":4,"nbformat_minor":0}