knitr::opts_chunk$set( collapse = TRUE, comment = "#>" )
The egen
function is used to convert a continuous variable into groups by discretizing it into intervals. It is a deprecated function that has been replaced by the cut
function from the mStats
package. The main difference between egen
and cut
is the input they accept.
egen
works with data frames or tibbles, allowing variable grouping within the context of the entire dataset.cut
operates on a vector, performing grouping directly on that vector.The egen
function is deprecated and serves as a wrapper around the cut function. It issues a deprecation warning indicating that the recommended approach is to use cut directly.
library(mStats) data <- data.frame(x = 1:10) egen(data, x, at = c(3, 7), label = c("low", "medium", "high"))
egen
versus mutate
+ cut
library(dplyr) # Example 1: Using egen() function data <- data.frame(x = 1:10) data <- egen(data, var = x, at = c(3, 7), label = c("low", "medium", "high")) # Example 2: Using mutate() and cut() functions data2 <- data.frame(x = 1:10) data2 <- mutate(data2, x = cut(x, at = c(-Inf, 3, 7, Inf), label = c("low", "medium", "high"))) # Check if the results are the same identical(data, data2) # Should be TRUE
In both examples, a data frame data
and data2
with a single variable x
is created. The goal is to group the values of x
into three categories: "low", "medium", and "high", based on the specified breakpoints.
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