packages-report

Workshop challenge checklist

As you complete tasks, you can cross them out by surrounding with ~~.

• Have a look around the files here. Where are the R scripts? What are the directories data and figs for?
• Notice that this README is an .Rmd file. That means it could contain R code and will need to be rendered to create README.md.
• Open R/01_write-installed-packages.R. Write the script as directed. Run it. Commit and push the current state.
• Open R/02_wrangle-packages.R. Fill in the missing pieces of the script as directed. Run it. Commit and push the current state.
• Open R/03_barchart-packages-built.R. Fill in the missing pieces of the script as directed. Run it. Commit and push the current state.
• Fill in the blanks below in this README, using the results stored elsewhere.
• If you get this far, write an R script to run the whole analysis and, perhaps, another script that does a make clean style reset.

Overview

The goal of packages-report is to do a quick analysis of the packages installed on this machine.

I have 570 add-on packages installed.

Here's how they break down in terms of which version of R they were built under, which is related to how recently they were updated on CRAN.

#> 
#> > read_csv("data/add-on-packages-freqtable.csv") %>% 
#> +     ggplot(aes(x = Built, y = n)) + geom_bar(stat = "identity", 
#> +     aes(fill = Built), show .... [TRUNCATED]
#> Parsed with column specification:
#> cols(
#>   Built = col_character(),
#>   n = col_integer(),
#>   prop = col_double()
#> )
#> Saving 7 x 5 in image

Flow of the analysis

If you have time, document the analysis works, using internal links.