readcamp is a simple R package to munge DataCamp's group exports into a tidy format. It is useful for group administrators who wish to understand how their students are doing, and prefer to perform this analysis in R.
This package is not yet available on CRAN. You can install the development version from GitHub with:
# install.packages("devtools")
devtools::install_github("atheriel/readcamp")readcamp exposes one main function that reads all course & chapter grades
and completion information from the .zip archive downloaded from the DataCamp
website. For example:
x <- readcamp::read_group_export("group_export_XXXX.zip")
x
#> A DataCamp Group Export containing the following course dataset:
#> # A tibble: ?? x 10
#> user_id course course_id chapter
#> <chr> <chr> <int> <chr>
#> 1 93ea1f54 introduction to r 58 Overview
#> 2 93ea1f54 data visualization with ggplot2 (part 1) 774 Overview
#> 3 93ea1f54 intermediate r 672 Overview
#> 4 93ea1f54 data manipulation in r with dplyr 625 Overview
#> 5 93ea1f54 importing data in r (part 1) 1477 Overview
#> 6 93ea1f54 intermediate r - practice 753 Overview
#> 7 93ea1f54 importing data in r (part 2) 1478 Overview
#> 8 93ea1f54 introduction to data 1800 Overview
#> 9 93ea1f54 data visualization in r 1498 Overview
#> 10 93ea1f54 data visualization in r with ggvis 638 Overview
#> # ... with ?? more rows, and 6 more variables: free <lgl>,
#> # status <fctr>, start_date <chr>, completed_date <chr>, grade <dbl>,
#> # completion <dbl>As you can see, this will return an object containing course- and chapter-level
start and end dates, grades, and completion, in a tidy data format. To extract
the course data frame itself, use the readcamp::courses() method:
readcamp::courses(x)
#> # A tibble: ?? x 10
#> user_id course course_id chapter
#> <chr> <chr> <int> <chr>
#> 1 93ea1f54 introduction to r 58 Overview
#> 2 93ea1f54 data visualization with ggplot2 (part 1) 774 Overview
#> 3 93ea1f54 intermediate r 672 Overview
#> 4 93ea1f54 data manipulation in r with dplyr 625 Overview
#> 5 93ea1f54 importing data in r (part 1) 1477 Overview
#> 6 93ea1f54 intermediate r - practice 753 Overview
#> 7 93ea1f54 importing data in r (part 2) 1478 Overview
#> 8 93ea1f54 introduction to data 1800 Overview
#> 9 93ea1f54 data visualization in r 1498 Overview
#> 10 93ea1f54 data visualization in r with ggvis 638 Overview
#> # ... with ?? more rows, and 6 more variables: free <lgl>,
#> # status <fctr>, start_date <chr>, completed_date <chr>, grade <dbl>,
#> # completion <dbl>By default, user names and emails are hashed into the user_id column, but
should you wish to retrieve the underlying account information, use the
readcamp::users() method to view the data frame mapping users to their ids.
Since the package uses a metadata file (see inst/course_metadata.csv) to map
course names to IDs and to identify free courses, it is possible that this file
will become out-of-date. The read_group_export() function will warn you if
there are courses with no IDs or names, and you can diagnose these with the
missing_courses() method.
If you do find errors or needed updates in the course metadata, please contact me on Slack, or submit a PR making the change directly.
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