使用 cut() 和 quantile() 在 R 中存储连续列

Question

I have the following generated df with ages and weights

df = data.frame(
    Age = sample(18:98, 1000, replace = TRUE),
    Weight = sample(80:250, 10000, replace = TRUE)
)

I want to alter the continuous columns by creating buckets based on the quantiles (25%, 50%, 75%. This can be done like so:

> quantile(df$Age, probs = c(0.25,0.5,0.75))
25% 50% 75% 
 39  58  78

However, I want to use the cut function using these quantiles (25%, 50%, 75%)

How can I do this? I want the output to transform to something like this, where any continuous variable is converted to buckets based on the quantile (25%, 50%, 75%)

Age          Weight
(17.9,44.7]  (137,193]
(44.7,71.3]  (137,193]
(71.3,98.1]  (79.8,137]
(44.7,71.3]  (193,250]
(17.9,44.7]  (79.8,137]

Answer 1

Just pass your quantiles as the second argument to cut , though add a 0 and 1 quantile so that your cuts have lower and upper bounds. (ie c(0, 0.25, 0.5, 0.75, 1) , which can be concisely written as 0:4 / 4 )

Tidyverse version

library(dplyr)

as_tibble(df) %>% 
   mutate(across(everything(), .fn = function(x) cut(x, quantile(x, 0:4/4))))
#> # A tibble: 10,000 x 2
#>    Age     Weight   
#>    <fct>   <fct>    
#>  1 (18,38] (80,121] 
#>  2 (78,98] (121,165]
#>  3 (18,38] (121,165]
#>  4 (58,78] (208,250]
#>  5 (58,78] (165,208]
#>  6 (78,98] (80,121] 
#>  7 (38,58] (165,208]
#>  8 (58,78] (80,121] 
#>  9 (38,58] (165,208]
#> 10 (58,78] (121,165]
#> # ... with 9,990 more rows

---

Base R version

df$Age <- cut(df$Age, quantile(df$Age, 0:4/4))
df$Weight <- cut(df$Weight, quantile(df$Weight, 0:4/4))

Answer 2

My santoku package has chop_quantiles() :

library(santoku)
df[] <- apply(df, 2, chop_quantiles, 0:4/4)

or even simpler:

df[] <- apply(df, 2, chop_equally, 4)

The empty brackets are a trick which keeps df as a data.frame.

If you want the raw values in your labels, you can do:

df[] <- apply(df, 2, chop_equally, 4, labels = lbl_intervals(raw = TRUE))