[[ {SparkR} | R Documentation |
Return subsets of DataFrame according to given conditions
## S4 method for signature 'DataFrame,numericOrcharacter' x[[i]] ## S4 method for signature 'DataFrame,missing' x[i, j, ..., drop = TRUE] ## S4 method for signature 'DataFrame,Column' x[i, j, ..., drop = TRUE] ## S4 method for signature 'DataFrame' subset(x, subset, select, ...)
x |
A DataFrame |
subset |
A logical expression to filter on rows |
select |
expression for the single Column or a list of columns to select from the DataFrame |
A new DataFrame containing only the rows that meet the condition with selected columns
Other subsetting functions: $
,
$<-
, select
,
select
,
select,DataFrame,Column-method
,
select,DataFrame,list-method
,
selectExpr
; filter
,
filter
, where
,
where
## Not run:
##D # Columns can be selected using `[[` and `[`
##D df[[2]] == df[["age"]]
##D df[,2] == df[,"age"]
##D df[,c("name", "age")]
##D # Or to filter rows
##D df[df$age > 20,]
##D # DataFrame can be subset on both rows and Columns
##D df[df$name == "Smith", c(1,2)]
##D df[df$age %in% c(19, 30), 1:2]
##D subset(df, df$age %in% c(19, 30), 1:2)
##D subset(df, df$age %in% c(19), select = c(1,2))
## End(Not run)