R won't compute means correctly with aggregate function

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Not sure why R won't calculate the means of my data correctly. I do have a lot of NA values but R keeps telling me that the mean is NA. Here's an example:

data1=read_excel"pepper.xlsx"

data1$cultivar = as.factor(data1$cultivar)

mean = aggregate(data1[,3:4], list(data1$cultivar), mean)
cultivar replication width height
BOF 1 12 14
BOF 2 10 NA
BOF 3 NA 15
BOF 4 NA NA

Instead of computing the mean width of BOF being 11 and the mean height being 14.5, it computes the means of the height and width as NA. This is an over-simplification of my data. I have several cultivars in my study and calculated the means of each variable of each cultivar using the aggregate function.

mean aggregate r
2 Answers

Update: There is no need for anonymous function (Credits to Gregor Thomas, see comments). We could use:

summarise(across(where(is.numeric), mean, na.rm = TRUE))

First answer: Thanks to Gregor Thomas colMeanswon't work here. We could use dplyr package summarise and across

library(dplyr)

df %>% 
  group_by(cultivar) %>% 
  summarise(across(where(is.numeric),~ mean(., na.rm = TRUE)))

Output:

  cultivar replication width height
  <chr>          <dbl> <dbl>  <dbl>
1 BOF              2.5    11   14.5
user_133216470

Try this:

mean = aggregate(data1[,3:4], list(data1$cultivar), mean, na.rm = TRUE, na.action = na.pass)
user_81047770
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