Reproducibility.rmd

---
title: Reproducibility
layout: default
---

# How to write a reproducible example.

You are most likely to get good help with your R problem if you provide a reproducible example. A reproducible example allows someone else to recreate your problem by just copying and pasting R code. 

There are four things you need to include to make your example reproducible: required packages, data, code, and a description of your R environment.

* **Packages** should be loaded at the top of the script, so it's easy to
 see which ones the example needs.

* The easiest way to include **data** in an email is to use dput() to generate
  the R code to recreate it. For example, to recreate the mtcars dataset in R,
  I'd perform the following steps:

   1. Run `dput(mtcars)` in R
   2. Copy the output
   3. In my reproducible script, type `mtcars <- ` then paste.

* Spend a little bit of time ensuring that your **code** is easy for others to
  read:

  * make sure you've used spaces and your variable names are concise, but
    informative

  * use comments to indicate where your problem lies

  * do your best to remove everything that is not related to the problem.  
   The shorter your code is, the easier it is to understand.

* Include the output of sessionInfo() as a comment. This summarises your **R
  environment** and makes it easy to check if you're using an out-of-date
  package.

You can check you have actually made a reproducible example by starting up a fresh R session and pasting your script in.  

Before putting all of your code in an email, consider putting it on http://gist.github.com/.  It will give your code nice syntax highlighting, and you don't have to worry about anything getting mangled by the email system.

## Example

Here's an illustration of how to create a reproducible example. First, have R print out your data in a format that can be copy-pasted:

```R
# For this example, use the built-in BOD data set. Replace this with your data.
dput(BOD)
# structure(list(Time = c(1, 2, 3, 4, 5, 7), demand = c(8.3, 10.3, 
# 19, 16, 15.6, 19.8)), .Names = c("Time", "demand"), row.names = c(NA, 
# -6L), class = "data.frame", reference = "A1.4, p. 270")
```


Then you can use that output to create a reproducible example:

```R
library(ggplot2)

# Save the data structure in variable BOD
BOD <- structure(list(Time = c(1, 2, 3, 4, 5, 7), demand = c(8.3, 10.3, 
19, 16, 15.6, 19.8)), .Names = c("Time", "demand"), row.names = c(NA, 
-6L), class = "data.frame", reference = "A1.4, p. 270")

# Some example code that uses the data
ggplot(BOD, aes(x=Time, y=demand)) + geom_line()
```

Check that others can run this code by simply copying and pasting it in a **new** R sesion.