R 中数据框每一列的第 25 个分位数

Question

I am trying to iterate over a data frame in R. For each column I would like to print the 25th quantile.

Using data from the nycflights13 package I am trying the following:

abt <- select(flights, sched_dep_time)

for(i in names(abt)) {
  qrt_1 <- quantile(abt[i], c(.25))
  print(qrt_1)
}

However this gives me the error: Error: Must use a vector in [ , not an object of class matrix.

Where am I taking a wrong turn here?

Answer 1

This might not bring you a solution to your question why it does not work, but i want to present you an alternative with lapply()

lapply(mtcars, function (x) quantile(x, 0.25))

This also returns you the 25% quantile of every column in your dataframe. But every column must be numeric (which you assume in your example).

Also you can use sapply instead of lapply if you want a vectorised output

Answer 2

In your example you are using select to choose a single column from the "flights" data frame, which returns a tibble with a single column giving scheduled departure times. You are not iterating over the data frame.

If you want to iterate over the flights data frame you need to do something like this:

cat("25th Quantiles:\n===============\n")

for(i in names(flights)) 
{ 
  if(is.numeric(flights[[i]])) 
  {
    qrt_1 <- quantile(flights[[i]], c(.25), na.rm = TRUE)
    cat(i, ":", qrt_1, "\n")
  }
}

Which prints the following to the console:

#> 25th Quantiles:
#> ===============
#> year : 2013 
#> month : 4 
#> day : 8 
#> dep_time : 907 
#> sched_dep_time : 906 
#> dep_delay : -5 
#> arr_time : 1104 
#> sched_arr_time : 1124 
#> arr_delay : -17 
#> flight : 553 
#> air_time : 82 
#> distance : 502 
#> hour : 9 
#> minute : 8 

Answer 3

You can pipe with dplyr's summarise_if (@emilliman5's comment):

library(tidyverse)

flights %>% 
  summarise_if(is.numeric, quantile, 0.25) 

As you dindn't provide any reproducible example, you can check with iris data:

---

using summarise_if

iris %>% 
   summarise_if(is.numeric, quantile, 0.25)

#  Sepal.Length Sepal.Width Petal.Length Petal.Width
#1          5.1         2.8          1.6         0.3     

---

or using sapply and select_if (original answer):

iris %>% 
  select_if(is.numeric) %>% 
  sapply(quantile, 0.25)

#Sepal.Length.25%  Sepal.Width.25% Petal.Length.25%  Petal.Width.25% 
#             5.1              2.8              1.6              0.3