Defining tidy (and therefore usable) data
Defining tidy (and therefore usable) data
“Data Scientists spend up to 80% of the time on data cleaning and 20 percent of their time on actual data analysis”. This statement is a popular saying in the data since community. It was originally stated in Dasu and Johnson’s book, Exploratory Data Minning and Data cleaning. As reported in the upcoming resources, one can conclude that in any data science project, tidying your data is crucial and makes the workflow more productive and efficient.
Resource: What is Tidy Data?
Type: Article
Who it’s for: Beginner learner
Why we love it: A simple and straight forward approach to define tidiness and usability of tidy data
Resource: Tidy your data
Type: Tutorial / Quiz
Who it’s for: Someone with previous knowledge in the definition of tidy data.
Why we love it: A method to get learners with some practices in tidy data