Calculating frequency for each column and calculating the frequency for the whole matrix

My matrix looks like the following table

v1  v2  v3
M   Z   P
Z   Z   P
P   Z   M
Z   P   Z

I wan to calculate the frequency for each column and then calculate the frequency for the whole data. The desired outcome is:

Factor  V1  V2  V3  Freq  Percentage
M       1   0   1   2     16.66666667
P       1   1   2   4     33.33333333
Z       2   3   1   6     50

I tried sapply(df, table), but it did not work. Any help would be great, especially using tidyverse

Solution

Here is one way with table and addmargins

out <- addmargins(table(unlist(df1), c(col(df1))), 2)
cbind(out, Percentage = 100 *out[,4]/sum(out[, 4]))
#  1 2 3 Sum Percentage
#M 1 0 1   2  16.66667
#P 1 1 2   4  33.33333
#Z 2 3 1   6  50.00000

Or in a more compact way

library(qdapTools)
transform(as.data.frame(addmargins(t(mtabulate(df1)), 2)),
                 Percentage = 100 * Sum/sum(Sum))

Or using tidyverse

library(tidyverse)
gather(df1, key, Factor) %>%
    dplyr::count(key, Factor) %>% 
    spread(key, n, fill = 0) %>% 
    mutate(Freq = rowSums(.[-1]), 
           Percentage = 100 * Freq/sum(Freq))
# A tibble: 3 x 6
#  Factor    v1    v2    v3  Freq Percentage
#  <chr>  <dbl> <dbl> <dbl> <dbl>      <dbl>
#1 M          1     0     1     2       16.7
#2 P          1     1     2     4       33.3
#3 Z          2     3     1     6       50

data

df1 <- structure(list(v1 = c("M", "Z", "P", "Z"), v2 = c("Z", "Z", "Z", 
 "P"), v3 = c("P", "P", "M", "Z")), class = "data.frame",
  row.names = c(NA, -4L))