Standard and Non-Standard Evaluation in R

Kevin Feasel

2019-04-04

R

John Mount explains Standard Evaluation versus Non-Standard Evaluation in R:

In standard (or value oriented evaluation) code you type in is taken to be variable names, functions, names, operators, and even numeric literal values. String values or literals need extra marks, such as quotes.

John walks us through several examples along the way. At the end, John is a major proponent of Standard Evaluation over Non-Standard Evaluation.

Related Posts

From Excel to R: Three Examples

Abdul Majed Raja has a few examples of things which are easy to do in Excel and how you can do them in R: Create a difference variable between the current value and the next valueThis is also known as lead and lag – especially in a time series dataset this varaible becomes very important in feature engineering. In […]

Read More

Calculating AUC in R

Andrew Treadway shows how you can calculate Area Under the Curve in R: AUC is an important metric in machine learning for classification. It is often used as a measure of a model’s performance. In effect, AUC is a measure between 0 and 1 of a model’s performance that rank-orders predictions from a model. For […]

Read More

Categories

April 2019
MTWTFSS
« Mar May »
1234567
891011121314
15161718192021
22232425262728
2930