mutate {SparkR}R Documentation

Mutate

Description

Return a new SparkDataFrame with the specified columns added or replaced.

Usage

mutate(.data, ...)

transform(`_data`, ...)

## S4 method for signature 'SparkDataFrame'
mutate(.data, ...)

## S4 method for signature 'SparkDataFrame'
transform(`_data`, ...)

Arguments

.data

a SparkDataFrame.

...

additional column argument(s) each in the form name = col.

_data

a SparkDataFrame.

Value

A new SparkDataFrame with the new columns added or replaced.

Note

mutate since 1.4.0

transform since 1.5.0

See Also

rename withColumn

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, ncol, nrow, persist, printSchema, randomSplit, rbind, rename, repartitionByRange, repartition, rollup, sample, saveAsTable, schema, selectExpr, select, showDF, show, storageLevel, str, subset, summary, take, toJSON, unionAll, unionByName, union, unpersist, withColumn, withWatermark, with, write.df, write.jdbc, write.json, write.orc, write.parquet, write.stream, write.text

Examples

## Not run: 
##D sparkR.session()
##D path <- "path/to/file.json"
##D df <- read.json(path)
##D newDF <- mutate(df, newCol = df$col1 * 5, newCol2 = df$col1 * 2)
##D names(newDF) # Will contain newCol, newCol2
##D newDF2 <- transform(df, newCol = df$col1 / 5, newCol2 = df$col1 * 2)
##D 
##D df <- createDataFrame(list(list("Andy", 30L), list("Justin", 19L)), c("name", "age"))
##D # Replace the "age" column
##D df1 <- mutate(df, age = df$age + 1L)
## End(Not run)

[Package SparkR version 3.0.0 Index]