Here is a tidyverse option that might not the most elegant, but offers some flexibility in terms of what is included in the summary:
library(tidyverse)
dir_path <- '~/path/to/data/directory/'
file_pattern <- 'Df\\.[0-9]\\.csv' # regex pattern to match the file name format
read_dir <- function(dir_path, file_name){
read_csv(paste0(dir_path, file_name)) %>%
mutate(file_name = file_name) %>% # add the file name as a column
gather(variable, value, A:B) %>% # convert the data from wide to long
group_by(file_name, variable) %>%
summarize(sum = sum(value, na.rm = TRUE),
min = min(value, na.rm = TRUE),
mean = mean(value, na.rm = TRUE),
median = median(value, na.rm = TRUE),
max = max(value, na.rm = TRUE))
}
df_summary <-
list.files(dir_path, pattern = file_pattern) %>%
map_df(~ read_dir(dir_path, .))
df_summary
# A tibble: 8 x 7
# Groups: file_name [?]
file_name variable sum min mean median max
<chr> <chr> <int> <dbl> <dbl> <dbl> <dbl>
1 Df.1.csv A 34 4 5.67 5.5 8
2 Df.1.csv B 22 1 3.67 3 9
3 Df.2.csv A 21 1 3.5 3.5 6
4 Df.2.csv B 16 1 2.67 2.5 5
5 Df.3.csv A 30 0 5 5 11
6 Df.3.csv B 43 1 7.17 6.5 15
7 Df.4.csv A 21 0 3.5 3 8
8 Df.4.csv B 42 1 7 6 16