CODEWITHSUNDEEP
r
Bio_farmer
Bio_farmer

Reputation: 159

How to add row based on the other rows?

I have a data frame with many rows and columns, for example

treatment   gene1   gene2   gene3   …
A   0   3   0   …
A   0   0   0   …
A   0   0   0   …
A   1   1   0   …
A   0   0   0   …
B   0   1   1   …
B   0   5   2   …
B   0   0   3   …
B   0   0   0   …
…   …   …   …

I would like to have the following data frame based on the rule: if the values of each gene for each treatment are 0, the value of this gene for this treatment is 0 (for example gene1 for treatment A), otherwise 1 (for example gene1 for treatment B). So the new data frame will be the below data frame.

treatment   gene1   gene2   gene3   …
A   1   1   0   …
B   0   1   1   …
…   …   …   …   …

Thank you very much for your help.

Upvotes: 1

Views: 44

Answers (2)

akrun
akrun

Reputation: 887851

An option with base R

+(rowsum(df[-1], df$treatment) > 0)
#    gene1 gene2 gene3
#A     1     1     0
#B     0     1     1

data

df <- structure(list(treatment = c("A", "A", "A", "A", "A", "B", "B", 
"B", "B"), gene1 = c(0L, 0L, 0L, 1L, 0L, 0L, 0L, 0L, 0L), gene2 = c(3L, 
0L, 0L, 1L, 0L, 1L, 5L, 0L, 0L), gene3 = c(0L, 0L, 0L, 0L, 0L, 
1L, 2L, 3L, 0L)), class = "data.frame", row.names = c(NA, -9L
))

Upvotes: 0

tmfmnk
tmfmnk

Reputation: 40171

With dplyr, you can do:

df %>%
 group_by(treatment) %>%
 summarise_all(list(~ as.integer(any(.))))

  treatment gene1 gene2 gene3
  <fct>     <int> <int> <int>
1 A             1     1     0
2 B             0     1     1

The same with base R:

aggregate(. ~ treatment, FUN = function(x) as.integer(any(x)), data = df)

Upvotes: 1

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