Add a column with count of NAs and Mean

You can try this:

#Find the row mean and add it to a new column in the dataframe
df1$Mean <- rowMeans(df1, na.rm = TRUE)

#Find the count of NA and add it to a new column in the dataframe
df1$CountNa <- rowSums(apply(is.na(df1), 2, as.numeric))

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'))))))