what I want to do is to modify all selected columns of an R data table according to the rows conditions i.e
for all 4 columns selected in cols variable, if the value is greater (or equal) than 1.5, i would like to put them to 1 else 0
I tried something like that : iris[(cols) > 1.5 , (cols) := 1, .SDcols = cols]
Thx
One data.table approach:
iris <- as.data.table(iris)
cols <- names(iris)[1:4]
cols
# [1] "Sepal.Length" "Sepal.Width" "Petal.Length" "Petal.Width"
iris[, (cols) := lapply(.SD, function(z) fifelse(z > 1.5, 1, z)), .SDcols = cols]
iris
# Sepal.Length Sepal.Width Petal.Length Petal.Width Species
# <num> <num> <num> <num> <fctr>
# 1: 1 1 1.4 0.2 setosa
# 2: 1 1 1.4 0.2 setosa
# 3: 1 1 1.3 0.2 setosa
# 4: 1 1 1.5 0.2 setosa
# 5: 1 1 1.4 0.2 setosa
# 6: 1 1 1.0 0.4 setosa
# 7: 1 1 1.4 0.3 setosa
# 8: 1 1 1.5 0.2 setosa
# 9: 1 1 1.4 0.2 setosa
# 10: 1 1 1.5 0.1 setosa
# ---
# 141: 1 1 1.0 1.0 virginica
# 142: 1 1 1.0 1.0 virginica
# 143: 1 1 1.0 1.0 virginica
# 144: 1 1 1.0 1.0 virginica
# 145: 1 1 1.0 1.0 virginica
# 146: 1 1 1.0 1.0 virginica
# 147: 1 1 1.0 1.0 virginica
# 148: 1 1 1.0 1.0 virginica
# 149: 1 1 1.0 1.0 virginica
# 150: 1 1 1.0 1.0 virginica
An alternative using set:
for (nm in cols) set(iris, which(iris[[nm]] > 1.5), nm, 1)
Another solution:
library(dplyr)
library(data.table)
iris[,1:4] %>% data.table() %>% mutate_all(~ ifelse(.x>=1.5,1,0))
If you just need to check for numeric columns across can be a good fit, it also works with more specific choices like positions and names
library(tidyverse)
iris |>
as_tibble() |>
mutate(across(.cols = where(is.numeric),.fns = ~ if_else(.x > 1.5,1,.x)))
#> # A tibble: 150 x 5
#> Sepal.Length Sepal.Width Petal.Length Petal.Width Species
#> <dbl> <dbl> <dbl> <dbl> <fct>
#> 1 1 1 1.4 0.2 setosa
#> 2 1 1 1.4 0.2 setosa
#> 3 1 1 1.3 0.2 setosa
#> 4 1 1 1.5 0.2 setosa
#> 5 1 1 1.4 0.2 setosa
#> 6 1 1 1 0.4 setosa
#> 7 1 1 1.4 0.3 setosa
#> 8 1 1 1.5 0.2 setosa
#> 9 1 1 1.4 0.2 setosa
#> 10 1 1 1.5 0.1 setosa
#> # ... with 140 more rows
Created on 2021-10-18 by the reprex package (v2.0.1)
Base R option -
data <- iris
cols <- 1:4
data[cols] <- +(data[cols] > 1.5)
# Sepal.Length Sepal.Width Petal.Length Petal.Width Species
#1 1 1 0 0 setosa
#2 1 1 0 0 setosa
#3 1 1 0 0 setosa
#4 1 1 0 0 setosa
#5 1 1 0 0 setosa
#6 1 1 1 0 setosa
#...
#...
The + at the beginning is used to change the logical values (TRUE/FALSE) to integers (1/0).