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Flashcards for online data science specialization courses
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DataScientistsToolbox 1 - command line interface.Rda
DataScientistsToolbox 1 - command line interface.csv
DataScientistsToolbox 2 - Basic git commands.Rda
DataScientistsToolbox 2 - Basic git commands.csv
DataScientistsToolbox 3 - R.Rda
DataScientistsToolbox 3 - R.csv
Exploratory Data Analysis - Week 1.Rda
Exploratory Data Analysis - Week 1.csv
Exploratory Data Analysis - Week 2.Rda
Exploratory Data Analysis - Week 2.csv
Exploratory Data Analysis - Week 3.Rda
Exploratory Data Analysis - Week 3.csv
Exploratory Data Analysis - Week 4.Rda
Exploratory Data Analysis - Week 4.csv
Getting and Cleaning Data - Week 1.Rda
Getting and Cleaning Data - Week 1.csv
Getting and Cleaning Data - Week 2.Rda
Getting and Cleaning Data - Week 2.csv
Getting and Cleaning Data - Week 3.Rda
Getting and Cleaning Data - Week 3.csv
Getting and Cleaning Data - Week 4.Rda
Getting and Cleaning Data - Week 4.csv
Inferential Statistics - Deck 1.Rda
Inferential Statistics - Deck 1.csv
Inferential Statistics - Deck 2.Rda
Inferential Statistics - Deck 2.csv
IntroDataScience 1 What is big data.Rda
IntroDataScience 1 What is big data.csv
IntroDataScience 2 Types of questions.Rda
IntroDataScience 2 Types of questions.csv
IntroDataScience 3 - Expermimental Design.Rda
IntroDataScience 3 - Expermimental Design.csv
IntroDataScience 1 Intro.Rda
IntroDataScience 1 Intro.csv
R Programming - Week 1.Rda
R Programming - Week 1.csv
R Programming - Week 2.Rda
R Programming - Week 2.csv
R Programming - Week 3.Rda
R Programming - Week 3.csv
R Programming - Week 4.Rda
R Programming - Week 4.csv
Reproducible Research - Week 1.Rda
Reproducible Research - Week 1.csv
Reproducible Research - Week 2.Rda
Reproducible Research - Week 2.csv
Reproducible Research - Week 3.Rda
Reproducible Research - Week 3.csv

Flashcards for the Data Science specialization on Coursera

##What this repository offers:

  • Flashcards for courses of the Data Science specialization on Coursera in CSV and (reformatted) RDA files

  • A script to convert CSV files exported from Studyblue into clean RDA files, which can be loaded into R. (studyblue_csv_to_rda.R)

  • A script to review these flashcards saved in RDA format (studyblue_rda_viewer.R)

###Available soon:

  • An extension of the converter script, to convert it into clean CSV files and other useful formats.

##How to use the converter script:

1 Download the R script form Github

2 Save it in the folder in which your (corrupt) CSV files are located

3 Run it on RStudio

4 The first prompt will ask you to choose among csv files located in your folder.

5 If everything goes fine, the script will prompt "conversion fine" at the end of the process. This means that the script saved a clean(er) RDA file bearing the same name, yet with a different file extension, in your working directory.

##How to use the reviewer script:

1 Download the R script

2 Save it in the folder in which you have your RDA files

3 Run the script in RStudio

4 The first prompt will ask you to choose among the RDA files located in your working directory. And off you go!

##What is the point of converting Studyblue's csv files?

When you export your flashcards from Studyblue, the questions and answers are scattered all over the csv file. Plainly speaking, if you open the CSV file in Excel there is not one cell for the question and one cell for the answer. Neither can the CSV file be read into the R environment by using the read.csv command, no matter which separator is used. The converter script allows to detect the correct structure and convert the corrupt CSV files into a clean data.frame, saved as a RDA file.

In case you wonder about the use of exporting flashcards from Studyblue, bear in mind that these flashcards are user generated. Whereas our good old paper flashcards are rotting in our attics under a ever-increasing dust layer, they can still be used. But what are you going to do when Studyblue disappears or stops being free?


I hope everything works great for you. If not, please bear in mind that the script was designed solely for csv files exported from the Studyblue platform and it is definitely not bullet-proof. I even had to rewrite the script as the structure of the exported CSV files somehow changed over time, from one unclean state to another.

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