Attached is a screenshot of a dataframe I am working with. In order to use some other software that I have, I need all of the data to be on one row. What I essentially want to do is to copy all of the data from row 2 and onwards and just paste it onto the end of row one. I have tried to do that a few times in R but I usually end up with something that either orders all of the data (for example, every data point under "ParticipantName" would show up first then everything under "Name", "Age", and so on) or will have all of the data under a certain column in just one cell. My current code is this:
alan=read.csv("Alan.csv")
print(alan)
combined_data <- apply(alan, 2, function(x) paste(x, collapse = ""))
combined_alan <- data.frame(t(combined_data))
file_path <- "C:\\my_path\\alan.csv" #(Not my actual file path)
# Save the dataframe as a CSV file
write.csv(collapsed_row, file = file_path, row.names = FALSE)
That is a weird requirement, and I would say R might not be the best tool for that.
If you have Notepad++ installed you can open your csv file, use "Replace" (ctrl + H), at the bottom select "Extended (\n, \r, \t, \0, \x, ...)", then replace any occurence of \r\n with , and save as a new csv.
I'm thinking of an alternative solution that uses the tidyverse package, but would need to confirm whether you'd want your final csv file to be one row of data with a header row, or one row without. And if without, whether a one-column csv would work, too.
I would want my final csv file to be one row of data with a header row. I have to use SPSS software to perform some analysis and it requires that data belongs on one row.
You can something like this after you install the tidyverse package:
library(tidyverse)
# make toy table
small <- tibble(b = 6:9, a = letters[9:6], c = c(T,F,F,T))
# view contents
small
#> # A tibble: 4 × 3
#> b a c
#> <int> <chr> <lgl>
#> 1 6 i TRUE
#> 2 7 h FALSE
#> 3 8 g FALSE
#> 4 9 f TRUE
# build two-row table with old column names in first row and data in second
small |>
# convert data to strings (for later conversion to matrix for transposing)
mutate(across(everything(), as.character)) |>
# store all data in a single column, with column names in another column
pivot_longer(everything()) |>
# convert table to matrix
as.matrix() |>
# transpose matrix
t() |>
# convert back to table (old column names become first row)
as_tibble() |>
# view contents
print() |>
# write as csv file without header row (since column names now in first row)
write_csv("one_row.csv", col_names = FALSE)
#> # A tibble: 2 × 12
#> V1 V2 V3 V4 V5 V6 V7 V8 V9 V10 V11 V12
#> <chr> <chr> <chr> <chr> <chr> <chr> <chr> <chr> <chr> <chr> <chr> <chr>
#> 1 b a c b a c b a c b a c
#> 2 6 i TRUE 7 h FALSE 8 g FALSE 9 f TRUE