Add a column with count of NAs and Mean

I have a data frame and I need to add another column to it which shows the count of NAs in all the other columns for that row and also the mean of the non-NA values. I think it can be done in dplyr.

> df1 <- data.frame(a = 1:5, b = c(1,2,NA,4,NA), c = c(NA,2,3,NA,NA))
> df1
  a  b  c
1 1  1 NA
2 2  2  2
3 3 NA  3
4 4  4 NA
5 5 NA NA

I want to mutate another column which counts the number of NAs in that row and another column which shows the mean of all the NON-NA values in that row.

library(dplyr)

count_na <- function(x) sum(is.na(x))    

df1 %>%
  mutate(means = rowMeans(., na.rm = T),
         count_na = apply(., 1, count_na))

#### ANSWER FOR RADEK ####
elected_cols <- c('b', 'c')

df1 %>%
  mutate(means = rowMeans(.[elected_cols], na.rm = T),
         count_na = apply(.[elected_cols], 1, count_na))

As mentioned here https://stackoverflow.com/a/37732069/2292993

df1 <- data.frame(a = 1:5, b = c(1,2,NA,4,NA), c = c(NA,2,3,NA,NA))

df1 %>%
  mutate(means = rowMeans(., na.rm = T),
         count_na = rowSums(is.na(.)))

to work on selected cols (the example here is for col a and col c):

df1 %>%
  mutate(means = rowMeans(., na.rm = T),
       count_na = rowSums(is.na(select(.,one_of(c('a','c'))))))