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{
"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"
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"nbformat_minor": 0
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