I'm racking my brain over the SE implementation of mutate_each_ in dplyr. What I want to do is to subtract the value in one column in a DF from every column in the DF.
Here is a minimum working example of what I'm looking to accomplish, using the iris dataset (I remove the 'Species' column so that it is all numeric). I subtract the Petal.Width column from every column. But I need the column name to be a variable, such as "My.Petal.Width"
# Remove Species column, so that we have only numeric data
iris_numeric <- iris %>% select(-Species)
# This is the desired result, using NSE
result_NSE <- iris_numeric %>% mutate_each(funs(. - `Petal.Width`))
# This is my attempt at using SE
SubtractCol <- "Petal.Width"
result_SE <- iris_numeric %>% mutate_each_(funs(. - as.name(SubtractCol)))
# Second attempt
SubtractCol <- "Petal.Width"
Columns <- colnames(iris_numeric)
mutate_call = lazyeval::interp(~.-a, a = as.name(SubtractCol))
result_SE <- iris_numeric %>% mutate_each_(.dots = setNames(list(mutate_call), Columns))
I get various errors:
Error in colwise_(tbl, funs_(funs), vars) :
argument "vars" is missing, with no default
Error in mutate_each_(., .dots = setNames(list(mutate_call), Columns)) :
unused argument (.dots = setNames(list(mutate_call), Columns))
Please help and many thanks in advance.
What you are looking for is the SE version of funs
, i.e. funs_
:
library(lazyeval); library(dplyr)
SubtractCol <- "Petal.Width"
iris %>% mutate_each(funs_(interp(~.-x, x = as.name(SubtractCol))), -Species) %>% head
# Sepal.Length Sepal.Width Petal.Length Petal.Width Species
#1 4.9 3.3 1.2 0 setosa
#2 4.7 2.8 1.2 0 setosa
#3 4.5 3.0 1.1 0 setosa
#4 4.4 2.9 1.3 0 setosa
#5 4.8 3.4 1.2 0 setosa
#6 5.0 3.5 1.3 0 setosa
You would use mutate_each_
if you wanted to supply what I wrote as "-Species" as a string/variable.
Note that there's no .dots
argument in mutate_each_
and summarise_each_
.
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