Is there a function that can move columns up in R studio?

Question

Update: I have a dataset that is output in a staircase format. For example:

I would like the data to move up from row 80-88 to row 1-8 and then the data before the prompts to be in row 1 and the data after the promts to line up with the correct promt. This example would then look like this:

I am hoping there are functions of some sort that I can run in Rstudio to correct these issues because I have almost 200 participants I will have to make these same corrections for. Any ideas?

I have not found a function where I can move a single column up or delete a single cell that would force the data upward. Any ideas would be greatly appreciated.

Answer 1

This first part fo the code is just to get a data.frame with diagonal values

# Recreate the example data.frame
df <- data.frame(diag(c(3, 6, 7, 4, 3), 5, 5))
names(df) <- paste0("Task ", c(1:5))
        
df

# Output 
Task 1 Task 2 Task 3 Task 4 Task 5
1      3      0      0      0      0
2      0      6      0      0      0
3      0      0      7      0      0
4      0      0      0      4      0
5      0      0      0      0      3

Now this function reads diagonal values and add them into the first column

change_df <- function(df) {
  # Get diagonal values
  values <- diag(as.matrix(df))
  # Empty data.frame
  df[,] <- 0
  df[, 1] <- values
  df
}

change_df(df)

# Output 
 Task 1 Task 2 Task 3 Task 4 Task 5
1      3      0      0      0      0
2      6      0      0      0      0
3      7      0      0      0      0
4      4      0      0      0      0
5      3      0      0      0      0

Answer 2

Based on your explaination of the problem, I think this should do what you want to do:

First, a simplified version of your data (It would have made this much easier if you included this yourself):

df <- structure(list(row = 80:88, participant = c(1, 1, 1, 1, 1, 1, 
1, 1, 1), slider_header = c(9, NA, NA, NA, NA, NA, NA, NA, NA
), slider_2_header = c(NA, 2, NA, NA, NA, NA, NA, NA, NA), prompt = c("Please", 
"Do you", "Does this", "Have you", "How many", "Wjat is", "What is", 
"How man", "How many3"), slider_scale = c(NA, NA, NA, 2, NA, 
NA, NA, NA, NA)), class = "data.frame", row.names = c(NA, -9L
))

Using tidyverse functions, we can do what you want by grouping the data by participant, removing the leading NA values from each of the relevant vectors so all the numbers are in the first row of the group, and then padding them so the vectors are all the same length for the data frame (based on this closely related question: Remove leading NAs to align data):

library(tidyverse)

df %>%
    group_by(participant) %>%
    mutate(across(starts_with('slider'), ~ `length<-`(zoo::na.trim(.x), length(.x))))

  participant slider_header slider_2_header prompt    slider_scale
        <dbl>         <dbl>           <dbl> <chr>            <dbl>
1           1             9               2 Please               2
2           1            NA              NA Do you              NA
3           1            NA              NA Does this           NA
4           1            NA              NA Have you            NA
5           1            NA              NA How many            NA
6           1            NA              NA Wjat is             NA
7           1            NA              NA What is             NA
8           1            NA              NA How man             NA
9           1            NA              NA How many3           NA

By grouping on "participant", this process will happen separately for each "participant". If you want to group on other variables (like date), just add it to the group_by function. Then we apply a function to each variable starting with "slider": this function is defined with ~ and uses na.trim from the zoo package to remove the NAs from each variable, and then assigns each of the that variable's original length, resulting in them being padded with trailing NAs as in your requested data.

Answer 3

You havent made it easy to help you , lack of reproducible example. but I can address this :

I have not found a function where I can move a single column up or delete a single cell that would force the data upward.

use dplyr::lead, to slide up all or a portion of a column up by n places (dplyr::lag would be do the slide down)

library(tidyverse)
(example_1 <- tibble(a=1:6,b=1:6))

#im going to slide column b up so that 456 slide up to begin after 2 rather than 3, this will leave a hole where 6 was
example_1$b[3:6] <- dplyr::lead(example_1$b[3:6],n=1)

# look at the result
example_1