{ "cells": [ { "cell_type": "markdown", "metadata": {}, "source": [ "# Visualizing Chipotle's Data" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "This time we are going to pull data directly from the internet.\n", "Special thanks to: https://github.com/justmarkham for sharing the dataset and materials.\n", "\n", "### Step 1. Import the necessary libraries" ] }, { "cell_type": "code", "execution_count": 1, "metadata": { "collapsed": false }, "outputs": [], "source": [ "import pandas as pd\n", "import collections\n", "import matplotlib.pyplot as plt \n", "\n", "# set this so the graphs open internally\n", "%matplotlib inline" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "### Step 2. Import the dataset from this [address](https://raw.githubusercontent.com/justmarkham/DAT8/master/data/chipotle.tsv). " ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "### Step 3. Assign it to a variable called chipo." ] }, { "cell_type": "code", "execution_count": null, "metadata": { "collapsed": false }, "outputs": [], "source": [] }, { "cell_type": "markdown", "metadata": {}, "source": [ "### Step 4. See the first 10 entries" ] }, { "cell_type": "code", "execution_count": null, "metadata": { "collapsed": false, "scrolled": false }, "outputs": [], "source": [] }, { "cell_type": "markdown", "metadata": {}, "source": [ "### Step 5. Create a histogram of the top 5 items bought" ] }, { "cell_type": "code", "execution_count": null, "metadata": { "collapsed": false }, "outputs": [], "source": [] }, { "cell_type": "markdown", "metadata": {}, "source": [ "### Step 6. Create a scatterplot with the number of items orderered per order price\n", "#### Hint: Price should be in the X-axis and Items ordered in the Y-axis" ] }, { "cell_type": "code", "execution_count": null, "metadata": { "collapsed": false }, "outputs": [], "source": [] }, { "cell_type": "markdown", "metadata": {}, "source": [ "### Step 7. BONUS: Create a question and a graph to answer your own question." ] }, { "cell_type": "code", "execution_count": null, "metadata": { "collapsed": false }, "outputs": [], "source": [] } ], "metadata": { "kernelspec": { "display_name": "Python 2", "language": "python", "name": "python2" }, "language_info": { "codemirror_mode": { "name": "ipython", "version": 2 }, "file_extension": ".py", "mimetype": "text/x-python", "name": "python", "nbconvert_exporter": "python", "pygments_lexer": "ipython2", "version": "2.7.11" } }, "nbformat": 4, "nbformat_minor": 0 }