28
votes

I'm try to calculate minimum across multiple columns (row-wise min) in a data frame, but the min function automatically returns the minimum across the whole of each column rather than for each row separately. I'm sure I'm missing something really simple here? Any ideas much appreciated.

x <- c(1,2,7)
y <- c(1,5,4)
minIwant <- c(1,2,4)
df <- data.frame(x, y, minIwant)
df$minIget <- min(df$x,df$y)
df
  x y minIwant minIget
1 1 1        1       1
2 2 5        2       1
3 7 4        4       1
4
@RichScriven's is less intuitive (to me) but much faster, for anyone who's in optimization mode.Jason

4 Answers

42
votes

You can use apply to go through each row

apply(df, 1, FUN = min)

Where 1 means to apply FUN to each row of df, 2 would mean to apply FUN to columns.

To remove missing values, use:

apply(df, 1, FUN = min, na.rm = TRUE)
15
votes

We could use pmin, which finds the parallel minima of sets of values. Since our df is technically a list, we will need to run it via do.call.

df$min <- do.call(pmin, df)

which gives

df
#   x y min
# 1 1 1   1
# 2 2 5   2
# 3 7 4   4

Data:

df <- data.frame(x = c(1, 2, 7), y = c(1, 5, 4))

Furthermore, if na.rm = TRUE is needed, you can do

df$min <- do.call(pmin, c(df, na.rm = TRUE))
4
votes

We could also use rowMins from library(matrixStats)

library(matrixStats)
df$minIwant <- rowMins(as.matrix(df))
4
votes

Just want to add on how you can also do this with dplyr.

library(dplyr)

x<-c(1,2,7)
y<-c(1,5,4)
df <- data.frame(x,y)

df %>% rowwise() %>% mutate(minIget = min(x, y))
# A tibble: 3 x 3
    x     y   minIget
  <dbl> <dbl>   <dbl>
1    1.    1.      1.
2    2.    5.      2.
3    7.    4.      4.