---
title: "HW 4"
author: "Name here"
date: "Due February 6, 2018 at 12:15 PM"
output: html_document
---

Please use D2L to turn in both the HTML output and your R Markdown file in.

## Q1. Data Wrangling (4 pts)
Define data wrangling and discuss why it is an important element in the data analysis or data visualization process.

## Q2. dplyr (5 pts)
Implement one function from the dplyr package on a dataset we have used in class (such as [http://math.montana.edu/ahoegh/teaching/stat408/datasets/SeattleHousing.csv](http://math.montana.edu/ahoegh/teaching/stat408/datasets/SeattleHousing.csv) or [http://math.montana.edu/ahoegh/teaching/stat408/datasets/HousingSales.csv](http://math.montana.edu/ahoegh/teaching/stat408/datasets/HousingSales.csv) ) and describe what this procedure is doing.

## Q3.

### a (4 pts)
Describe the difference between `substr()` and `strsplit()`.

### b (6 pts)
Use one of these function to create a new variable for the hour an Uber ride began using [http://math.montana.edu/ahoegh/teaching/stat408/datasets/UberMay2014.csv](http://math.montana.edu/ahoegh/teaching/stat408/datasets/UberMay2014.csv).

Then apply the `count()` function from dplyr to compute the number of rides starting at each hour

