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I remember a comment on r-help in 2001 saying that drop = TRUE in [.data.frame was the worst design decision in R history.
dplyr corrects that and does not drop implicitly. When trying to convert old code to dplyr style, this introduces some nasty bugs when d[, 1] or d[1] is assumed a vector.
My current workaround uses unlist as shown below to obtain a 1-column vector. Any better ideas?
library(dplyr)
d2 = data.frame(x = 1:5, y = (1:5) ^ 2)
str(d2[,1]) # implicit drop = TRUE
# int [1:5] 1 2 3 4 5
str(d2[,1, drop = FALSE])
# data.frame': 5 obs. of 1 variable:
# $ x: int 1 2 3 4 5
# With dplyr functions
d1 = data_frame(x = 1:5, y = x ^ 2)
str(d1[,1])
# Classes ‘tbl_df’ and 'data.frame': 5 obs. of 1 variable:
# $ x: int 1 2 3 4 5
str(unlist(d1[,1]))
# This ugly construct gives the same as str(d2[,1])
str(d1[,1][[1]])
911
Deleting a column using dplyr is very easy using the select() function and the - sign. For example, if you want to remove the columns “X” and “Y” you'd do like this: select(Your_Dataframe, -c(X, Y)) .
To remove a single column or multiple columns in R DataFrame use square bracket notation [] or use functions from third-party packages like dplyr.
We can delete multiple columns in the R dataframe by assigning null values through the list() function.
To select variables from a dataset you can use this function dt[,c("x","y")] , where dt is the name of dataset and “x” and “y” name of vaiables. To exclude variables from dataset, use same function but with the sign - before the colon number like dt[,c(-x,-y)] .
You can just use the [[ extract function instead of [.
d1[[1]]
## [1] 1 2 3 4 5
If you use a lot of piping with dplyr, you may also want to use the convenience functions extract and extract2 from the magrittr package:
d1 %>% magrittr::extract(1) %>% str
## Classes ‘tbl_df’ and 'data.frame': 5 obs. of 1 variable:
## $ x: int 1 2 3 4 5
d1 %>% magrittr::extract2(1) %>% str
## int [1:5] 1 2 3 4 5
Or if extract is too verbose for you, you can just use [ directly in the pipe:
d1 %>% `[`(1) %>% str
## Classes ‘tbl_df’ and 'data.frame': 5 obs. of 1 variable:
## $ x: int 1 2 3 4 5
d1 %>% `[[`(1) %>% str
## int [1:5] 1 2 3 4 5
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