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ETA: the point of the below, by the way, is to not have to iterate through my entire set of column vectors, just in case that was a proposed solution (just do what is known to work once at a time).
There's plenty of examples of replacing values in a single vector of a data frame in R with some other value.
if) statement in RAnd also how to replace all values of NA with something else:
What I'm looking for is analogous to the last question, but basically trying to replace one value with another. I'm having trouble generating a data frame of logical values mapped to my actual data frame for cases where multiple columns meet a criteria, or simply trying to do the actions from the first two questions on more than one column.
An example:
data <- data.frame(name = rep(letters[1:3], each = 3), var1 = rep(1:9), var2 = rep(3:5, each = 3)) data name var1 var2 1 a 1 3 2 a 2 3 3 a 3 3 4 b 4 4 5 b 5 4 6 b 6 4 7 c 7 5 8 c 8 5 9 c 9 5 And say I want all of the values of 4 in var1 and var2 to be 10.
I'm sure this is elementary and I'm just not thinking through it properly. I have been trying things like:
data[data[, 2:3] == 4, ] That doesn't work, but if I do the same with data[, 2] instead of data[, 2:3], things work fine. It seems that logical test (like is.na()) work on multiple rows/columns, but that numerical comparisons aren't playing as nicely?
Thanks for any suggestions!
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replace() function in R Language is used to replace the values in the specified string vector x with indices given in list by those given in values. It takes on three parameters first is the list name, then the index at which the element needs to be replaced, and the third parameter is the replacement values.
To pick out single or multiple columns use the select() function. The select() function expects a dataframe as it's first input ('argument', in R language), followed by the names of the columns you want to extract with a comma between each name.
To find the mean of multiple columns based on multiple grouping columns in R data frame, we can use summarise_at function with mean function.
you want to search through the whole data frame for any value that matches the value you're trying to replace. the same way you can run a logical test like replacing all missing values with 10..
data[ is.na( data ) ] <- 10 you can also replace all 4s with 10s.
data[ data == 4 ] <- 10 at least i think that's what you're after?
and let's say you wanted to ignore the first row (since it's all letters)
# identify which columns contain the values you might want to replace data[ , 2:3 ] # subset it with extended bracketing.. data[ , 2:3 ][ data[ , 2:3 ] == 4 ] # ..those were the values you're going to replace # now overwrite 'em with tens data[ , 2:3 ][ data[ , 2:3 ] == 4 ] <- 10 # look at the final data data If you love us? You can donate to us via Paypal or buy me a coffee so we can maintain and grow! Thank you!
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