Making Calculations on Several Textfiles and making a Dataframe from it R - r

Question

I am trying to create a table from calculations that I am doing to several text file. I think this might require a loop of some sort, but I am stuck on how to proceed. I have tried different loops but none seem to be working. I have managed to do what I want with one file. Here is my working code:
flare <- read.table("C:/temp/HD3_Bld_CD8_TEM.txt",
header=T)
head(flare[,c(1,2)])
#sum of the freq column, check to see if close to 1
sum(flare$freq)
#Sum of top 10
ten <- sum(flare$freq[1:10])
#Sum of 11-100
to100 <- sum(flare$freq[11:100])
#Sum of 101-1000
to1000 <- sum(flare$freq[101:1000])
#sum of 1001+
rest <- sum(flare$freq[-c(1:1000)])
#place the values of the sum in a table
df <- data.frame(matrix(ncol = 1, nrow = 4))
x <- c("Sum")
colnames(df) <- x
y <- c("10", "11-100", "101-1000", "1000+")
row.names(df) <- y
df[,1] <- c(ten,to100,to1000,rest)
The dataframe ends up looking like this:
>View(df)
Sum
10 0.1745092
11-100 0.2926735
101-1000 0.4211533
1000+ 0.1116640
This is perfect for making a stacked barplot, which I did. However, this is only for one text file. I have several of the same files. All of them have the same column names, so I know that all of them will be using DF$freq column for the calculations. How do I make a table after doing calculations with each file? I want to keep the names of the text files as the sample names so that way when i make a joint stacked barplot all the names will be there. Also, what is the best way to orient the data when writing the new table/dataframe?
I am still new to R, so any help, any explanation would be most welcome. Thank you.

Answer 1

How about something like this, your example is not reproducible so I made a dummy example which you can adjust:
library(tidyverse)
###load ALL your dataframes
test_df_1 <- data.frame(var1 = matrix(c(1,2,3,4,5,6), nrow = 6, ncol = 1))
test_df_1
test_df_2 <- data.frame(var2 = matrix(c(7,8,9,10,11,12), nrow = 6, ncol = 1))
test_df_2
### Bind them into one big wide dataframe
df <- cbind(test_df_1, test_df_2)
### Add an id column which repeats (in your case adjust this to repeat for the grouping you want, i.e replace the each = 2 with each = 10, and each = 4 with each = 100)
df <- df %>%
mutate(id = paste0("id_", c(rep(1, each = 2), rep(2, each = 4))))
### Gather your dataframes into long format by the id
df_gathered <- df %>%
gather(value = value, key = key, - id)
df_gathered
### use group_by to group data by id and summarise to get the sum of each group
df_gathered_sum <- df_gathered %>%
group_by(id, key) %>%
summarise(sigma = sum(value))
df_gathered_sum
You might have some issues with the ID column if your dfs are not equal length so this is only a partial answer. Can do better with a shortened example of your dataset. Can anyone else weigh in on creating an id column? May have sorted it with a couple of edits...

Answer 2

I think I solved it! It gives me the dataframe I want, and from it, I can make the stacked barplot to display the data.
sumfunction <- function(x) {
wow <- read.table(x, header=T)
#Sum of top 10
ten <- sum(wow$freq[1:10])
#Sum of 11-100
to100 <- sum(wow$freq[11:100])
#Sum of 101-1000
to1000 <- sum(wow$freq[101:1000])
#sum of 1001+
rest <- sum(wow$freq[-c(1:1000)])
blah <- c(ten,to100,to1000,rest)
}
library(data.table)
library(tools)
dir = "C:/temp/"
filenames <- list.files(path = dir, pattern = "*.txt", full.names = FALSE)
alltogether <- lapply(filenames, function(x) sumfunction(x))
data <- as.data.frame(data.table::transpose(alltogether),
col.names =c("Top 10 ", "From 11 to 100", "From 101 to 1000", "From 1000 on "),
row.names = file_path_sans_ext(basename(filenames)))
This gives me the dataframe that I want. I instead of putting the "top 10, 11-100, 101-1000, 1000+" as the row names, I changed them to column names and instead made the names of each text file become the row names. The file_path_sans_ext(basename(filenames)) makes sure to just keep the file name and remove the extension.
I hope this helps anyone that reads this! thank you again! I love this platform because just being part of this environment gets me thinking and always striving to better myself at R.
If anyone has any input, that would be great!!! <3