Have a look around the files here. Where are the R scripts? What are the directories data and figs for? Do the names and structure help you find things?
Open each R script, finish it, and run it. Remember to restart R as you go, so you are certain each file is complete, i.e. data flows through explicit write/read, not the global workspace.
Combine your work analyzing your R packages and what we’ve learned re: GitHub and R Markdown
This Quarto document gives a scaffold for using the work you did earlier to make a little report.
Given our previous work, I’m using pre-computed results and including a pre-made figure, leaving the R code down in scripts below R/. But know that, in other contexts, you could inline all that code in chunks here. Depends on downstream usage and the project context.
Overview
The goal of packages-report is to FINISH THIS SENTENCE.
# load data/add-on-packages-freqtable.csv here in this chunkapt <- here::here("ae/ae-15-project-workflow-A/data/add-on-packages-freqtable.csv") |>read_csv()
Rows: 3 Columns: 3
── Column specification ────────────────────────────────────────────────────────
Delimiter: ","
chr (1): Built
dbl (2): n, prop
ℹ Use `spec()` to retrieve the full column specification for this data.
ℹ Specify the column types or set `show_col_types = FALSE` to quiet this message.
I have 3 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.