columns {SparkR} | R Documentation |
Return all column names as a list
## S4 method for signature 'DataFrame' columns(x) ## S4 method for signature 'DataFrame' names(x) ## S4 replacement method for signature 'DataFrame' names(x) <- value ## S4 method for signature 'DataFrame' colnames(x) ## S4 replacement method for signature 'DataFrame,character' colnames(x) <- value colnames(x, do.NULL = TRUE, prefix = "col") colnames(x) <- value
x |
A SparkSQL DataFrame |
Other DataFrame functions: $
,
$<-
, select
,
select
,
select,DataFrame,Column-method
,
select,DataFrame,list-method
,
selectExpr
; DataFrame-class
,
dataFrame
, groupedData
;
[
, [
, [[
,
subset
; agg
,
agg
,
count,GroupedData-method
,
summarize
, summarize
;
arrange
, arrange
,
arrange
, orderBy
,
orderBy
; as.data.frame
,
as.data.frame,DataFrame-method
;
attach
,
attach,DataFrame-method
;
cache
; collect
;
coltypes
, coltypes
,
coltypes<-
, coltypes<-
;
columns
, dtypes
,
printSchema
, schema
,
schema
; count
,
nrow
; describe
,
describe
, describe
,
summary
, summary
,
summary,PipelineModel-method
;
dim
; distinct
,
unique
; dropna
,
dropna
, fillna
,
fillna
, na.omit
,
na.omit
; dtypes
;
except
, except
;
explain
, explain
;
filter
, filter
,
where
, where
;
first
, first
;
groupBy
, groupBy
,
group_by
, group_by
;
head
; insertInto
,
insertInto
; intersect
,
intersect
; isLocal
,
isLocal
; join
;
limit
, limit
;
merge
, merge
;
mutate
, mutate
,
transform
, transform
;
ncol
; persist
;
printSchema
; rbind
,
rbind
, unionAll
,
unionAll
; registerTempTable
,
registerTempTable
; rename
,
rename
, withColumnRenamed
,
withColumnRenamed
;
repartition
; sample
,
sample
, sample_frac
,
sample_frac
;
saveAsParquetFile
,
saveAsParquetFile
,
write.parquet
, write.parquet
;
saveAsTable
, saveAsTable
;
saveDF
, saveDF
,
write.df
, write.df
,
write.df
; selectExpr
;
showDF
, showDF
;
show
, show
,
show,GroupedData-method
; str
;
take
; unpersist
;
withColumn
, withColumn
;
write.json
, write.json
;
write.text
, write.text
## Not run:
##D sc <- sparkR.init()
##D sqlContext <- sparkRSQL.init(sc)
##D path <- "path/to/file.json"
##D df <- read.json(sqlContext, path)
##D columns(df)
##D colnames(df)
## End(Not run)