README.md

In marcoblume/readcamp: Read 'DataCamp' Group Exports into Tidy Data Frames

readcamp

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.

Installation

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")

Usage

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.

Course Metadata

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.

marcoblume/readcamp documentation built on May 27, 2019, 2:01 a.m.