How to prevent R from rounding in frequency function? - r

Question

I used the freq function of frequency package to get frequency percent on my dataset$MoriskyAdherence, then R gives me percent values with rounding. I need more decimal places.
MoriskyAdherence=dataset$MoriskyAdherence
freq(MoriskyAdherence)
The result is:
The Percent values are 35.5, 41.3,23.8. The sum of them is 100.1.
The exact amounts should be 35.5, 41.25, 23.75.
What should I do?
I used sprintf, as.data.frame,formatC, and some other function to deal with it.But...

Answer 1

The function freq returns a character data frame, and has no option to adjust the number of decimal places. However, it is easy to recreate the table however you want it. For example, I have written this function, which will give you the same result but with two decimal places instead of one:
freq2 <- function(data_frame)
{
df <- frequency::freq(data_frame)
lapply(df, function(x)
{
n <- suppressWarnings(as.numeric(x$Freq))
sum_all <- as.numeric(x$Freq[nrow(x)])
raw_percent <- suppressWarnings(100 * n / sum_all)
t_row <- grep("Total", x[,2])[1]
valid_percent <- suppressWarnings(100*n / as.numeric(x$Freq[t_row]))
x$Percent <- format(round(raw_percent, 2), nsmall = 2)
x$'Valid Percent' <- format(round(valid_percent, 2), nsmall = 2)
x$'Cumulative Percent' <- format(round(cumsum(valid_percent), 2), nsmall = 2)
x$'Cumulative Percent'[t_row:nrow(x)] <- ""
x$'Valid Percent'[(t_row + 1):nrow(x)] <- ""
return(x)
})
}
Now instead of
freq(MoriskyAdherence)
#> Building tables
#> |===========================================================================| 100%
#> $`x:`
#> x label Freq Percent Valid Percent Cumulative Percent
#> 2 Valid High Adherence 56 35.0 35.0 35.0
#> 3 Low Adherence 66 41.3 41.3 76.3
#> 4 Medium Adherence 38 23.8 23.8 100.0
#> 41 Total 160 100.0 100.0
#> 1 Missing <blank> 0 0.0
#> 5 <NA> 0 0.0
#> 7 Total 160 100.0
you can do
freq2(MoriskyAdherence)
#> Building tables
#> |===========================================================================| 100%
#> $`x:`
#> x label Freq Percent Valid Percent Cumulative Percent
#> 2 Valid High Adherence 56 35.00 35.00 35.00
#> 3 Low Adherence 66 41.25 41.25 76.25
#> 4 Medium Adherence 38 23.75 23.75 100.00
#> 41 Total 160 100.00 100.00
#> 1 Missing <blank> 0 0.00
#> 5 <NA> 0 0.00
#> 7 Total 160 100.00
which is exactly what you were looking for.

Answer 2

Two (potential) solutions:
Solution #1:
Make changes inside the function freq. This can be done by retrieving the function's code with the command freq (without round brackets), or by retrieving the code, with comments, from https://rdrr.io/github/wilcoxa/frequencies/src/R/freq.R.
My hunch is that to obtain more decimals, changes must be implemented at this point in the code:
# create a list of frequencies
message("Building tables")
all_freqs <- lapply_pb(names(x), function(y, x1 = as.data.frame(x), maxrow1 = maxrow, trim1 = trim){
makefreqs(x1, y, maxrow1, trim1)
})
Solution #2:
If you're only after percentages with more decimals, you can use aggregate. Let's suppose your data has this structure: a dataframe with two variables, one numeric, one a factor by which you want to group:
set.seed(123)
Var1 <- sample(LETTERS[1:4], 10, replace = T)
Var2 <- sample(10:100, 10, replace = T)
df <- data.frame(Var1, Var2)
Var1 Var2
1 B 97
2 D 51
3 B 71
4 D 62
5 D 19
6 A 91
7 C 32
8 D 13
9 C 39
10 B 96
Then to obtain your percentages by factor, you would use aggregatethus:
aggregate(Var2 ~ Var1, data = df, function(x) sum(x)/sum(Var2)*100)
Var1 Var2
1 A 15.93695
2 B 46.23468
3 C 12.43433
4 D 25.39405
You can control the number of decimals by using round:
aggregate(Var2 ~ Var1, data = df, function(x) round(sum(x)/sum(Var2)*100,3))