I am trying to remove some columns in a dataframe. I want to know why it worked for a single column but not with multible columns e.g. this works
album2[,5]<- NULL
this doesn't work:
album2[,c(5:7)]<- NULL
Error in `[<-.data.frame`(`*tmp*`, , 5:7, value = NULL) :
replacement has 0 items, need 600
This also doesn't work:
for (i in 5: (length(album2)-1)){
album2[,i]<- NULL
}
Error in `[<-.data.frame`(`*tmp*`, , i, value = NULL) :
new columns would leave holes after existing columns
Basic subsetting:
album2 <- album2[, -5] #delete column 5
album2 <- album2[, -c(5:7)] # delete columns 5 through 7
Adding answer as this was the top hit when searching for "drop multiple columns in r":
The general version of the single column removal, e.g df$column1 <- NULL, is to use list(NULL):
df[ ,c('column1', 'column2')] <- list(NULL)
This also works for position index as well:
df[ ,c(1,2)] <- list(NULL)
This is a more general drop and as some comments have mentioned, removing by indices isn't recommended. Plus the familiar negative subset (used in other answers) doesn't work for columns given as strings:
> iris[ ,-c("Species")]
Error in -"Species" : invalid argument to unary operator
list(NULL) and not just NULL?This works for me.
x <-dplyr::select(dataset_df, -c('column1', 'column2'))
If you only want to remove columns 5 and 7 but not 6 try:
album2 <- album2[,-c(5,7)] #deletes columns 5 and 7
@Ahmed Elmahy following approach should help you out, when you have got a vector of column names you want to remove from your dataframe:
test_df <- data.frame(col1 = c("a", "b", "c", "d", "e"), col2 = seq(1, 5), col3 = rep(3, 5))
rm_col <- c("col2")
test_df[, !(colnames(test_df) %in% rm_col), drop = FALSE]
All the best, ExploreR
Another solution, similar to @Dulakshi Soysa, is to use column names and then assign a range.
For example, if our data frame df(), has column names defined as column_1, column_2, column_3 up to column_15. We are interested in deleting the columns from the 5th to the 10th.
We can specify a range using column names e.g.,
library(dplyr)
x = select(df, -c('column_5':'column_10'))
Specifying the range can save some time when you are deleting multiple adjacent columns. It can also be used if you want to use some adjacent and some non-adjacent columns. For example, if you want to remove the 1st column in addition to the previously specified columns, you would update the code as below:
library(dplyr)
x = select(df, -c('column_1', 'column_5':'column_10'))
The following line will remove col_1 and col_2 from the data frame 'data'
data[!(colnames(data) %in% c('col_1','col_2'))]
Here is an interesting solution I read the other day in @JoachimSchork's blog, Statistics Globe. You can remove columns by column name. You can find out more here.
library(data.table)
mtcars2 <- mtcars
setDT(mtcars2)[, c("mpg", "cyl", "disp", "hp") := NULL]
> head(mtcars2)
drat wt qsec vs am gear carb
1: 3.90 2.620 16.46 0 1 4 4
2: 3.90 2.875 17.02 0 1 4 4
3: 3.85 2.320 18.61 1 1 4 1
4: 3.08 3.215 19.44 1 0 3 1
5: 3.15 3.440 17.02 0 0 3 2
6: 2.76 3.460 20.22 1 0 3 1
album2[,5:7]<- list(NULL)