Somehow I only get means of a few columns then the rest come back as NAs. I tried to use is.na=T and omit.na = T but I am getting the same wrong results. I tried these codes;
library(dplyr)
Test1162019 <- try1 %>%
filter(DateT == "11/6/2019") %>%
summarise(across(where(is.numeric), ~ mean(.x, na.omit = TRUE)))`
IDs DateT A B C D E F G H I J K L M N O P Q R S
A1 7/5/2019 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1
A2 7/5/2019 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1
A3 7/5/2019 5 5 5 6 7 7 8 9 10 10 11 12 12 13 14 15 15 15 15
A4 7/5/2019 33 34 34 35 35 36 37 37 38 38 38 38 38 38 38 38 38 38 38
A5 7/5/2019 3 3 3 NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA
A6 7/5/2019 21 21 21 21 21 21 21 21 21 21 21 21 21 21 21 21 21 21 21
A7 7/5/2019 34 35 35 36 36 36 36 36 37 37 38 38 38 39 39 39 40 40 41
B1 8/5/2019 65 65 65 66 66 67 67 67 67 67 67 68 68 69 69 70 71 71 72
B2 8/5/2019 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1
B3 8/5/2019 9 9 9 9 9 9 9 9 9 9 9 9 9 9 10 10 11 12 13
B3 8/5/2019 11 11 11 NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA
B5 8/5/2019 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2
B6 8/5/2019 21 22 23 24 24 25 26 27 28 28 29 30 31 32 32 33 33 33 33
B7 8/5/2019 8 8 9 10 11 11 12 13 13 14 15 15 16 17 17 18 18 19 19
B8 8/5/2019 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1
B9 8/5/2019 47 47 47 47 47 47 47 47 47 47 48 49 49 50 51 51 52 53 53
B10 8/5/2019 67 67 68 68 69 69 70 71 72 72 73 73 73 73 73 73 73 73 73
B11 8/5/2019 38 38 38 38 38 38 38 39 39 39 39 40 40 40 40 40 41 41 41
C1 11/6/2019 71 71 71 71 71 71 71 71 71 71 71 71 71 71 71 71 71 71 71
C2 11/6/2019 38 39 40 41 42 43 43 44 44 44 45 45 NA NA NA NA NA NA NA
C3 11/6/2019 40 40 40 40 40 40 40 40 40 40 40 40 40 40 40 40 40 40 40
C4 11/6/2019 2 2 2 2 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3
C5 15/5/2020 42 42 43 44 45 45 46 46 46 46 46 46 NA NA NA NA NA NA NA
D1 15/5/2020 41 41 42 43 43 44 44 45 45 46 47 47 48 49 50 51 51 51 52
D2 15/5/2020 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2
D3 15/5/2020 46 46 46 46 47 47 47 47 47 47 48 48 49 50 50 51 51 51 51
D4 15/5/2020 37 37 37 37 37 37 37 37 37 37 37 37 37 37 37 37 37 37 37
D5 15/5/2020 31 31 31 31 31 31 32 32 33 34 34 34 34 34 34 34 35 35 35
D6 15/5/2020 37 37 38 39 40 40 41 42 43 44 44 45 46 47 48 48 48 49 49
How do I solve this problem?
CodePudding user response：
I'm not a dplyr expert but the base R way to signal to mean to remove (ignore)NAs is na.rm = TRUE.
CodePudding user response：
You may use colMeans on a subset s.
s <- c("D", "E", "F") ## selected columns
colMeans(dat[s], na.rm=TRUE)
# D E F
# 28.22222 28.51852 28.70370
Or, use the pipe.
dat[s] |>
colMeans(na.rm=TRUE)
# D E F
# 28.22222 28.51852 28.70370