CODEWITHSUNDEEP
rdataframe
user11418708
user11418708

Reputation: 902

Calculating the means with NAs

I would like to calculate the below data frame mean. Due to the NA's, I receive the following message: Warning message:In mean.default(df_new) : argument is not numeric or logical: returning NA. Is there a way to bypass this error?

Data structure:

enter image description here

Desire output rule =AVERAGE(B2:P7)

enter image description here

Sample data:

structure(list(X1 = c(1, 2, 3, 4, 5, 6), `10` = c(10, 10, 10, 
10, NA, NA), `20` = c(20, 20, 20, NA, NA, NA), `30` = c(30, 30, 
30, 30, NA, NA), `40` = c(40, 40, 40, 40, NA, NA), `50` = c(50, 
50, 50, 50, 50, 50), `60` = c(60, 60, NA, NA, NA, NA), `70` = c(70, 
70, NA, NA, NA, NA), `80` = c(80, 80, NA, NA, NA, NA), `90` = c(90, 
90, NA, NA, NA, NA), `100` = c(NA, NA, NA, NA, NA, NA), `110` = c(110, 
110, 110, NA, NA, NA), `120` = c(120, 120, NA, NA, NA, NA), `130` = c(NA, 
NA, NA, NA, NA, NA), `140` = c(NA, NA, NA, NA, NA, NA), `150` = c(150, 
NA, NA, NA, NA, NA), X17 = c(NA, NA, NA, NA, "average", "57.14285714"
)), class = c("spec_tbl_df", "tbl_df", "tbl", "data.frame"), row.names = c(NA, 
-6L), spec = structure(list(cols = list(X1 = structure(list(), class = c("collector_double", 
"collector")), `10` = structure(list(), class = c("collector_double", 
"collector")), `20` = structure(list(), class = c("collector_double", 
"collector")), `30` = structure(list(), class = c("collector_double", 
"collector")), `40` = structure(list(), class = c("collector_double", 
"collector")), `50` = structure(list(), class = c("collector_double", 
"collector")), `60` = structure(list(), class = c("collector_double", 
"collector")), `70` = structure(list(), class = c("collector_double", 
"collector")), `80` = structure(list(), class = c("collector_double", 
"collector")), `90` = structure(list(), class = c("collector_double", 
"collector")), `100` = structure(list(), class = c("collector_logical", 
"collector")), `110` = structure(list(), class = c("collector_double", 
"collector")), `120` = structure(list(), class = c("collector_double", 
"collector")), `130` = structure(list(), class = c("collector_logical", 
"collector")), `140` = structure(list(), class = c("collector_logical", 
"collector")), `150` = structure(list(), class = c("collector_double", 
"collector")), X17 = structure(list(), class = c("collector_character", 
"collector"))), default = structure(list(), class = c("collector_guess", 
"collector")), skip = 1L), class = "col_spec"))

Upvotes: 1

Views: 56

Answers (1)

akrun
akrun

Reputation: 887223

We may need rowMeans

rowMeans(df_new[grep("^\\d+$", names(df_new))], na.rm = TRUE)

Or if it is for the whole dataset, unlist the data.frame by selecting only the columns of interest to create a vector

mean(unlist(df_new[grep("^\\d+$", names(df_new))]), na.rm = TRUE)
[1] 57.14286

Or in a tidy way

library(dplyr)
df_new %>% 
    select(matches('^\\d+$')) %>% 
    as.matrix %>% 
    mean(na.rm = TRUE)
#[1] 57.14286

Upvotes: 1

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