| withColumn {SparkR} | R Documentation |
Return a new SparkDataFrame by adding a column or replacing the existing column that has the same name.
withColumn(x, colName, col) ## S4 method for signature 'SparkDataFrame,character' withColumn(x, colName, col)
x |
a SparkDataFrame. |
colName |
a column name. |
col |
a Column expression (which must refer only to this SparkDataFrame), or an atomic vector in the length of 1 as literal value. |
A SparkDataFrame with the new column added or the existing column replaced.
withColumn since 1.4.0
Other SparkDataFrame functions:
SparkDataFrame-class,
agg(),
alias(),
arrange(),
as.data.frame(),
attach,SparkDataFrame-method,
broadcast(),
cache(),
checkpoint(),
coalesce(),
collect(),
colnames(),
coltypes(),
createOrReplaceTempView(),
crossJoin(),
cube(),
dapplyCollect(),
dapply(),
describe(),
dim(),
distinct(),
dropDuplicates(),
dropna(),
drop(),
dtypes(),
exceptAll(),
except(),
explain(),
filter(),
first(),
gapplyCollect(),
gapply(),
getNumPartitions(),
group_by(),
head(),
hint(),
histogram(),
insertInto(),
intersectAll(),
intersect(),
isLocal(),
isStreaming(),
join(),
limit(),
localCheckpoint(),
merge(),
mutate(),
ncol(),
nrow(),
persist(),
printSchema(),
randomSplit(),
rbind(),
rename(),
repartitionByRange(),
repartition(),
rollup(),
sample(),
saveAsTable(),
schema(),
selectExpr(),
select(),
showDF(),
show(),
storageLevel(),
str(),
subset(),
summary(),
take(),
toJSON(),
unionByName(),
union(),
unpersist(),
withWatermark(),
with(),
write.df(),
write.jdbc(),
write.json(),
write.orc(),
write.parquet(),
write.stream(),
write.text()
## Not run:
##D sparkR.session()
##D path <- "path/to/file.json"
##D df <- read.json(path)
##D newDF <- withColumn(df, "newCol", df$col1 * 5)
##D # Replace an existing column
##D newDF2 <- withColumn(newDF, "newCol", newDF$col1)
##D newDF3 <- withColumn(newDF, "newCol", 42)
##D # Use extract operator to set an existing or new column
##D df[["age"]] <- 23
##D df[[2]] <- df$col1
##D df[[2]] <- NULL # drop column
## End(Not run)