The Theory Behind cdata

Kevin Feasel



John Mount has a video explaining the concepts behind cdata:

We also have two really nifty articles on the theory and methods:

Please give it a try!

Click through for the video, which I found very helpful in tying together a number of data transformation operations (pivoting, unpivoting, one-hot encoding, etc.).

Related Posts

Principal Component Analysis With Stack Overflow Data

Julia Silge explains Principal Component Analysis and shows us an example using Stack Overflow data: We have tidy data, both because that’s what I get when querying our databases and because it is useful for exploratory data analysis when preparing for a machine learning algorithm like PCA. To implement PCA, we need a matrix, and […]

Read More

Using xplain To Interpret Model Results

Joachim Zuckarelli walks us through the xplain package in R: The above XML produces the following output (don’t worry too much about the call of xplain(), we will discuss later on in more detail how to work with the xplain() function): library(car) library(xplain) xplain(call="lm(education ~ young + income + urban, data=Anscombe)", xml="") ## ## Call: ## lm(formula = education […]

Read More


January 2018
« Dec Feb »