setup.Rmd

---
title: "Setup for Divvy data analysis"
author: "Peter Carbonetto"
date: 2017-06-29
output: html_document
---

<!-- The file analysis/chunks.R contains chunks that define default settings
shared across the workflowr files. -->
```{r read-chunk, include=FALSE, cache=FALSE}
knitr::read_chunk("chunks.R")
```

<!-- Update knitr chunk options -->
```{r knitr-opts-chunk, include=FALSE}
```

<!-- Insert the date the file was last updated -->
```{r last-updated, echo=FALSE, results='asis'}
```

<!-- Insert the code version (Git commit SHA1) if Git repository exists and R
 package git2r is installed -->
```{r code-version, echo=FALSE, results='asis'}
```

To reproduce the results on your own computer, please follow these
setup instructions.

1. Download or clone the
[git repository](https://github.com/pcarbo/wflow-divvy) on your
computer.

2. Download the Divvy data files and copy the files to the
"data" directory. I have provided a script
`code/retrieve_divvy_data.sh` that can be used to automatically
retrieve and prepare the data files. Alternatively, you can open this
script and follow the steps by hand. After completing this step,
all these files should be in the data directory:

  ```
  Divvy_Stations_2016_Q1Q2.csv
  Divvy_Stations_2016_Q3.csv
  Divvy_Stations_2016_Q4.csv
  Divvy_Trips_2016_04.csv
  Divvy_Trips_2016_05.csv
  Divvy_Trips_2016_06.csv
  Divvy_Trips_2016_Q1.csv
  Divvy_Trips_2016_Q3.csv
  Divvy_Trips_2016_Q4.csv
  ```

3. Install [R](http://cran.r-project.org) and/or
[Rstudio](https://www.rstudio.com/products/rstudio).

4. Install the R packages used for the analyses:

   ```R
   install.packages(c("data.table","ggplot2"))
   ```

Once you have completed these steps, you may run the R code. When
running the code, make sure your working directory is set to the
"analysis" directory:

```{r working-directory}
getwd()
```
<br>

## Session information

This is the version of R and the packages that were used to generate
the results from the R Markdown notebooks.

```{r session-info}
```