I’m still working on getting my head around where R thinks we work and how to tell it where my stuff lives (aka working directories).
On twitter yesterday Alison Hill, Adam Gruer, Zoe Meers and Irene Steves helped me sort out my issues with here
.
hi #rstats friends, how do YOU use the `here` package? I thought I had my head around it but I'm doing something wrong. Here my markdown lives within the "markdown" folder, so I set here to the "data" folder, call read_csv(here("datafile.csv") and it doesn't work... help pic.twitter.com/ZGgxhmxegb
— Dr Jenny Richmond (@JenRichmondPhD) October 18, 2018
But it was THIS slide from Irene that REALLY fixed my problem.
knitr::include_graphics("paths.jpg")
I do love me a .Rmd file but did you know that most of what makes file paths stems from in R difficult is that when you are working in a .Rmd, R makes your working directory the folder that markdown lives in, but if you are working in a script (.R) the default working directory is the top level of the project file?
MIND BLOWN.
So, if you are working in a markdown file, the here
package is helpful in overcoming that not so useful default behaviour and makes it easy to define file paths relative to the top level of your project file.
Let me summarise my understanding so that we are all clear.
The best way to make sure you and R are working in the same place is to use Projects and to always open your analysis via a .Rproj file. That way you will always be working in the same directory as your .Rproj file.
You can check where you are by calling getwd
. RStudio also tells you the working directory right below the Console tab. If you are disagree with R about where you are working you can choose Session–Set Working Directory from the pull down menu to change it.
Up until recently, I have been guaranteeing that R can always find my files just keeping everything (data, scripts, markdown, output) in that working directory folder. If you data is sitting with your analysis script, then you can just call…
datafile <- read_csv("data.csv")
… and R will find your data. It works, but it is not best practice.
here
packageIdeally you want to be a bit more organised than that and it is better practice to have your data live in a folder the is separate from your analysis scripts, which are in a folder separate from your output files.
I am starting a new project and trying to set up my folder organisation as I mean to continue. I have a folder that contains an .Rproj file, and subfiles for data, markdowns, and output.
knitr::include_graphics("folder.png")
My analysis scripts (.Rmd files) live in a folder called markdown. So when you ask R what the working directory is, it defaults to that folder. This makes it difficult to tell R where your data files live.
getwd()
[1] “/Users/jenny/Desktop/project/markdown”
here
to tell R where your data isThe here
package allows you to set the top level of your project folder as “here” and to specify where things live relative to that location. I was under the misconception that here
set the directory, but it simply builds a path to the top level of your project file everytime you use it.
here::here()
[1] “/Users/jenny/Desktop/project”
You can use here when reading data that live within a “data” folder.
data <- read_csv(here("datafolder", "datafile.csv"))
If your data lives in the depths of several folders, you just string the folder references together.
data <- read_csv(here("datafolder", "subfolder", "datafile.csv"))
I like this “folder”, “subfolder”, “datafile.csv” method to call the path, because I am still fuzzy on how many . and / are needed in filepaths, but alternatively you can combine a more traditional file path with here.
data <- read_csv(here("./datafolder/datafile.csv"))
You can also use here
to make a filepath, and then use that file path to load lots of .csvs at once using map(read_csv). Check out my post about that use case here
Note: most of yesterday’s problem stemmed from a clash between lubridate
and here
. If you have used lubridate it is best to be specific that you want here::here() [with 2 colons].