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student_performance's Issues

Peer Review

CC: @moahmed @msimar

Rubric

Topic Rating
Coding style Excellent. Besides satisfying the general guidelines of script organization (proper headers, etc). The code is spaced out well and is easy to read. Tabs are used properly and show compartmentalized segments of code and brief comments allow one to skip over reading code.
Coding strategy Satisfactory. While there are no logical errors, it would be nice to see some consistency and modularization in the handling of data frames across scripts. For instance, in the grades_report.rmd, the average grades are calculated under the tidyverse package. But this calculation is also done in calculate_grades.R using base R's $ to reference column names.
Presentation: graphs Excellent. Simple and easy to understand at a glance.
Presentation: tables Satisfactory. In the final report, a lot of rows of the data is shown. It would be great to limit the number of rows if you simply want the reader to get a sense for the contents of the data frame.
Achievement, creativity Excellent. Unique data set and compelling topic.
Ease of access Excellent. I was able to generate the report in less than two minutes of reading the README and probing the scripts. There was an error in the first run of the run_this.sh file because there was no results directory originally. Consider adding a line to the script to create the folders necessary.

Remarks:

The overall project is well done with a good topic of choice and appropriate data set. It is good to see the instructions for building the report in the README as well as an option to run a bash script that builds the report. There are some areas that could be improved. Some were listed above. I would also recommend a list of dependencies in the README such as programs and libraries that need to be installed/added to their PATH variable. Also, you seem to be adding to the PATH directories which are specific to your computer in some of your R scripts. See for example,

# in src/calculate_grades.R

R_LIBS_USER=c("C:/Users/Toniloba/Documents/R/win-library/3.4")
.libPaths("C:/Users/Toniloba/Documents/R/win-library/3.4")

It might be wiser to instruct the user to do this themselves in the README since they might have their libraries stored elsewhere.

A copy of this peer evaluation appears as an issue on https://github.ubc.ca/ubc-mds-2017/DSCI_522_milestone2_tedd

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