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I'm trying to make a decision tree using rpart using a data frame that has ~200 columns. Some of these columns have numbers in their names, some have special characters (e.g. "/"). When I try to generate the tree I get error such as the ones below:
R> gg.rpart <- rpart(nospecialchar ~ Special/char, data=temp, method="class")
Error in eval(expr, envir, enclos) : object 'Special' not found
R> gg.rpart <- rpart(nospecialchar ~ "Special/char", data=temp, method="class")
Error in terms.formula(formula, data = data) : invalid model formula in ExtractVars
R> gg.rpart <- rpart(nospecialchar ~ `Special/char`, data=temp, method="class")
Error in `[.data.frame`(frame, predictors) : undefined columns selected
Do I have to change the names to accommodate R or is there some way to pass column names with special characters to R formulae?
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Use gsub() function to remove a character from a string or text in R.
To select a column in R you can use brackets e.g., YourDataFrame['Column'] will take the column named “Column”. Furthermore, we can also use dplyr and the select() function to get columns by name or index. For instance, select(YourDataFrame, c('A', 'B') will take the columns named “A” and “B” from the dataframe.
To add a new column to a dataframe in R you can use the $-operator. For example, to add the column “NewColumn”, you can do like this: dataf$NewColumn <- Values . Now, this will effectively add your new variable to your dataset.
Data in data frames can be addressed by index (subsetting), by logical vector, or by name (columns only). Use the $ operator to address a column by name.
This works:
dat <- data.frame(M=rnorm(10),'A/B'=1:10,check.names=F)
> lm(M~`A/B`,dat)
Call:
lm(formula = M ~ `A/B`, data = dat)
Coefficients:
(Intercept) `A/B`
-1.0494 0.1214
Joran's comment on my question is the answer - I didn't know of the existence of make.names()
Joran, if you reply as an answer I'll mark you as correct. Cheers!
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