---
title: "Lab 4: Data Cleaning"
author: 'Group Member Names - here'
date: "February 6, 2018"
output: html_document
---
Turn in one copy for each group, both HTML and R Markdown files. If group members are not present in class they will be required to complete their own lab to receive credit. Please turn in **both an HTML file and your R Markdown script**.  This is due Sunday, February 11. 

## Lab Overview


The entire lab will be worth 100 points. Clarity of code, including comments and interpretable variables names, along with thoughtful writing with an emphasis on concise interpretations will be considered when grading. 

## Questions
Answer the following questions in this R Markdown document. Please include code where necessary.

### 1. Capital BikeShare Data
This data set contains single bike trips from January - March of 2017 for the Capital BikeShare system in Washington, D.C.

#### a. (5 points)
Download the file [http://math.montana.edu/ahoegh/teaching/stat408/datasets/biketrips2017.csv](http://math.montana.edu/ahoegh/teaching/stat408/datasets/biketrips2017.csv). 

#### b. (15 points)
Summarize the data set. What does each column represent? What about each row? 

#### c. (40 points)
Using commands from the dplyr packaged, compute how many trips were made each day of the month. (I have filtered out cases that started and ended on different days.) Note this will require an intermediate step to extract the day of the month.

#### d. (40 points)

Use the piping structure from dplyr to compute the average trip length by member type. As a hint, the end date and start date have time stamps that you'll need to extract to compute the trip time for each bike rental.




