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I am trying to make a pivot table of a large .tsv data set in R and exporting it back to Excel.

I tried using the dplyer functions:

summary <- df %>%
group_by(Run,Prot) %>%
summarize(count_by_Id = n()) %>%
as.data.frame()

This almost works, but rows with e.g. "P61981;P62258" and "P62258" in the Prot column are counted together. How do I make R only summarize rows that have exactly the same strings in the Prot columns. So that in case of the above example there will be two different rows (for "P61981;P62258" and "P62258") in the summary data I am creating.

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  • Can you provide dput(df)? Commented Mar 10, 2023 at 3:08
  • 5
    Based on your code, it won't be counted as same if they are different strings. Make sure to use dplyr::summarise assuming the summarise is not getting masked by plyr::summarise Commented Mar 10, 2023 at 3:12
  • Does this answer your question? Why does summarize or mutate not work with group_by when I load `plyr` after `dplyr`? Commented Mar 10, 2023 at 9:33
  • Thank you all for the feedback; I am new to R, and can definitely use some help. @jrcalabrese: see below. There are more rows with 0's above what I copied, and more lines below with other variables. I can only copy a few because of the character limit 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0)), row.names = c(NA, -305177L), spec = structure(list(cols = list(File.Name = structure(list(), class = c("collector_character", "collector")), Run = structure(list(), class = c("collector_character", "collector")), Prot = structure(list(), class = c("collector_character", Commented Mar 10, 2023 at 16:37
  • @akrun : I tried this, but it did not make any difference. Commented Mar 10, 2023 at 16:40
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