{"cells": [{"source": ["## EDA on Grocery Sales Forecasting\n", "\n", "* Data Exploration\n", "* Feature Engineering"], "cell_type": "markdown", "metadata": {}}, {"source": ["import numpy as np # linear algebra\n", "import pandas as pd # data processing, CSV file I/O (e.g. pd.read_csv)\n", "\n", "from subprocess import check_output\n", "print(check_output([\"ls\", \"../input\"]).decode(\"utf8\"))"], "cell_type": "code", "outputs": [], "execution_count": null, "metadata": {"_cell_guid": "03310d0d-f20a-4431-a90b-c329dba03b27", "_uuid": "2afbefca27aa8a428283ee5201d69f1bf558d8a3"}}, {"source": ["train = pd.read_csv('../input/train.csv')\n", "test = pd.read_csv('../input/test.csv')"], "cell_type": "code", "outputs": [], "execution_count": null, "metadata": {"_cell_guid": "3e87df5d-ea23-41ba-88d2-e081f04ed420", "_uuid": "cd1c54796bbbd38e8f22995774850787f14ae294"}}, {"source": ["## Exploring Data"], "cell_type": "markdown", "metadata": {}}, {"source": ["print(train.shape)\n", "train.head()"], "cell_type": "code", "outputs": [], "execution_count": null, "metadata": {"_cell_guid": "1d296a7a-6862-46c4-ba84-50aace304a20", "_uuid": "dfdab5c67fe5f067359f6e0ff00dbe53765a317c"}}, {"source": ["print(test.shape)\n", "test.head()"], "cell_type": "code", "outputs": [], "execution_count": null, "metadata": {"_cell_guid": "9c0ec14e-5c8b-49dc-9136-8ce9750eec3f", "_uuid": "c0668f507cef668d2d94f6140941bd9116fb3bcf"}}, {"source": ["stores = pd.read_csv('./../input/stores.csv')\n", "print(stores.shape)\n", "stores.head()"], "cell_type": "code", "outputs": [], "execution_count": null, "metadata": {"_cell_guid": "01bd50b2-914e-44f5-87f3-e028109ca4e8", "_uuid": "8e3827a110dfe66f1232db9e0e7cba1015c3ab8f"}}, {"source": ["items = pd.read_csv('./../input/items.csv')\n", "print(items.shape)\n", "items.head()"], "cell_type": "code", "outputs": [], "execution_count": null, "metadata": {}}, {"source": ["oil = pd.read_csv('./../input/oil.csv')\n", "print(oil.shape)\n", "oil.head()"], "cell_type": "code", "outputs": [], "execution_count": null, "metadata": {}}, {"source": ["transactions = pd.read_csv('./../input/transactions.csv')\n", "print(transactions.shape)\n", "transactions.head()"], "cell_type": "code", "outputs": [], "execution_count": null, "metadata": {}}], "nbformat": 4, "nbformat_minor": 1, "metadata": {"language_info": {"codemirror_mode": {"version": 3, "name": "ipython"}, "name": "python", "mimetype": "text/x-python", "nbconvert_exporter": "python", "pygments_lexer": "ipython3", "version": "3.6.3", "file_extension": ".py"}, "kernelspec": {"display_name": "Python 3", "name": "python3", "language": "python"}}}