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Reproducibility
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.
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Packages should be loaded at the top of the script, so it's easy to see which ones the example needs.
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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:
- Run
dput(mtcars)
in R - Copy the output
- In my reproducible script, type
mtcars <-
then paste.
- Run
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Spend a little bit of time ensuring that your code is easy for others to read:
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make sure you've used spaces and your variable names are concise, but informative
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use comments to indicate where your problem lies
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do your best to remove everything that is not related to the problem.
The shorter your code is, the easier it is to understand.
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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 This summarises your R environment and makes it easy to check if you're using an out-of-date package.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.
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:
# 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:
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.