I have an R data frame with 6 columns, and I want to create a new dataframe that only has three of the columns.
Assuming my data frame is df
, and I want to extract columns A
, B
, and E
, this is the only command I can figure out:
data.frame(df$A,df$B,df$E)
Is there a more compact way of doing this?
You can subset using a vector of column names. I strongly prefer this approach over those that treat column names as if they are object names (e.g. subset()
), especially when programming in functions, packages, or applications.
# data for reproducible example
# (and to avoid confusion from trying to subset `stats::df`)
df <- setNames(data.frame(as.list(1:5)), LETTERS[1:5])
# subset
df[c("A","B","E")]
Note there's no comma (i.e. it's not df[,c("A","B","C")]
). That's because df[,"A"]
returns a vector, not a data frame. But df["A"]
will always return a data frame.
str(df["A"])
## 'data.frame': 1 obs. of 1 variable:
## $ A: int 1
str(df[,"A"]) # vector
## int 1
Thanks to David Dorchies for pointing out that df[,"A"]
returns a vector instead of a data.frame, and to Antoine Fabri for suggesting a better alternative (above) to my original solution (below).
# subset (original solution--not recommended)
df[,c("A","B","E")] # returns a data.frame
df[,"A"] # returns a vector