Install packages from Mastering Software Development in R

I'm currently reading a really nice book "Mastering Software Development in R" — but also a complete book — about R language. It was written by Roger D. Peng, Sean Kross and Brooke Anderson

Mastering Software Development in R

In the introduction of this book, authors give you an insight for all the packages they will use — and also invite you to install them — If you familiar with R, it will be no big deal ;-) And maybe a lot of theses packages are already installed on you R environement — ... but familiar or not I will give you some advice to be more efficient, because that's 45 packages.

Because time is what we are looking for with software like R: automation of data analyses to get more time of "real consulting" !

Installing packages with R

If you know just a little of R you could try :

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1install.packages("package_name")

But really 45 times, are you insane ? ;-)

If you just have to install a few packages, you could try to install several — dependents — packages in one :

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1install.packages("package_name")

One-liner to install packages with R

But what I recommend you to do is to install all packages at once, with this line (example) :

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1install.packages(c("package_one", "package_two", "...", "package_n"))

Note: it could take time ... time that you could use to comment this article and take a coffee/a tea!

All the packages

And with all the packages :

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1install.packages(c("choroplethr", "choroplethrMaps", "data.table", "datasets", "devtools", "dlnm", "dplyr", "faraway", "forcats", "GGally", "ggmap", "ggplot2", "ggthemes", "ghit", "GISTools", "grid", "gridExtra", "httr", "knitr", "leaflet", "lubridate", "magrittr", "methods", "microbenchmark", "package", "pander", "plotly", "profvis", "pryr", "purrr", "rappdirs", "raster", "RColorBrewer", "readr", "rmarkdown", "sp", "stats", "stringr", "testthat", "tidyr", "tidyverse", "tigris", "titanic", "viridis"))

With a variable

You could also create a variable including all packages, like that :

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1packages <- c("choroplethr", "choroplethrMaps", "data.table", "datasets", "devtools", "dlnm", "dplyr", "faraway", "forcats", "GGally", "ggmap", "ggplot2", "ggthemes", "ghit", "GISTools", "grid", "gridExtra", "httr", "knitr", "leaflet", "lubridate", "magrittr", "methods", "microbenchmark", "package", "pander", "plotly", "profvis", "pryr", "purrr", "rappdirs", "raster", "RColorBrewer", "readr", "rmarkdown", "sp", "stats", "stringr", "testthat", "tidyr", "tidyverse", "tigris", "titanic", "viridis")

And then call them directly on a variable ;-)

Listing all the packages from "Mastering Software Development in R"

The list of all the packages are :

• choroplethr
• choroplethr
• Maps
• data.table
• datasets
• devtools
• dlnm
• dplyr
• faraway
• forcats
• GGally
• ggmap
• ggplot2
• ggthemes
• ghit
• GISTools
• grid
• gridExtra
• httr
• knitr
• leaflet
• lubridate
• magrittr
• methods
• microbenchmark
• package
• pander
• plotly
• profvis
• pryr
• purrr
• rappdirs
• raster
• RColorBrewer
• readr
• rmarkdown
• sp
• stats
• stringr
• testthat
• tidyr
• tidyverse
• tigris
• titanic
• viridis

If you've understand how it works, it would be the same to call several libraries :

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1library(c("choroplethr", "choroplethrMaps", "data.table", "datasets", "devtools", "dlnm", "dplyr", "faraway", "forcats", "GGally", "ggmap", "ggplot2", "ggthemes", "ghit", "GISTools", "grid", "gridExtra", "httr", "knitr", "leaflet", "lubridate", "magrittr", "methods", "microbenchmark", "package", "pander", "plotly", "profvis", "pryr", "purrr", "rappdirs", "raster", "RColorBrewer", "readr", "rmarkdown", "sp", "stats", "stringr", "testthat", "tidyr", "tidyverse", "tigris", "titanic", "viridis"))

Hope this article helped you or interesed you, if it's the case you can share it and give a thumb up!

Thanks!