Changing the value of a duplicated column

Hello, first post here! I'm trying to use reprex, but I'm not sure if I did it right.

I am trying to identify and modify duplicate values in my dataset:

#> function (x, df1, df2, ncp, log = FALSE) 
#> {
#>     if (missing(ncp)) 
#>         .Call(C_df, x, df1, df2, log)
#>     else .Call(C_dnf, x, df1, df2, ncp, log)
#> }
#> <bytecode: 0x0000000013e75248>
#> <environment: namespace:stats>

Created on 2020-06-26 by the reprex package (v0.3.0)

I have two types of duplicate values that I want to remove and/or change:

  1. Columns 7 and 8 contain duplicates across all columns.
  2. Columns 3 and 4 contain duplicates across all columns except the "values" column.

I figured out how to remove these duplicates using this code:

df2 <- df %>% distinct(ID, FamId, question, wave, .keep_all = TRUE)
#> Error in df %>% distinct(ID, FamId, question, wave, .keep_all = TRUE): could not find function "%>%"

Created on 2020-06-26 by the reprex package (v0.3.0)

However, I think the duplicates are a data entry problem (this is a 2nd data analysis) I would like to modify the second "8" in the wave column to "12" (so it reads 1 4 8 12 1 4 8 12). How can I identify the duplicates and then change the value in the wave column such that the duplicate changes to 12?

I am happy to clarify, or to retry the reprex if I didn't do it correctly.

Thanks so much, happy to be joining the R community.


Hi, and welcome!

Please see the FAQ: What's a reproducible example (`reprex`) and how do I do one? Using a reprex, complete with representative data will attract quicker and more answers.

In this case it looks like you've named your data frame df, which is also the name of an R function, which is what appears in the post.

The easiest way to remove a duplicated column, say column_dupe is

my_df %>% select(-column_dupe) -> my_df

For columns 3 and 4 it's not clear what is duplicated. Do you have a row named waves?

If so, you may want to consider reorganizing your data frame to a tidy format, with variables, such as wave represented as columns and observations as rows.

In general, it's not a good idea to hand edit a data frame. If you do, meticulous notes are necessary to have any hope of recreating results.

To change just the single value 8 to a 12 can be done with subsetting.

Data frames are indexed row first, column second. So, for example, if the value 8 appears in row 15, column 2, the value can be replaced by

my_df[15,2] <- 12

Preferable, however, running down the error in the source.

All of this can be done by dplyr. I can suggest you steps and hints

  1. Install package tidyverse
  2. Load package tidyverse
  3. Convert your data frame to a tibble using as_tibble()
  4. To find duplicates use group_by() and then do a summarise with n()
  5. Having found the duplicates do a distinct as you are trying to do
  6. Finally do a if_else() or a case_when() to change specific values and achieve your final goal