colnames

0th

Percentile

Column Names of SparkDataFrame

Return a vector of column names.

Usage
colnames(x, do.NULL = TRUE, prefix = "col")

colnames(x) <- value

columns(x)

# S4 method for SparkDataFrame columns(x)

# S4 method for SparkDataFrame names(x)

# S4 method for SparkDataFrame names(x) <- value

# S4 method for SparkDataFrame colnames(x)

# S4 method for SparkDataFrame colnames(x) <- value

Arguments
x

a SparkDataFrame.

do.NULL

currently not used.

prefix

currently not used.

value

a character vector. Must have the same length as the number of columns to be renamed.

Note

columns since 1.4.0

names since 1.5.0

names<- since 1.5.0

colnames since 1.6.0

colnames<- since 1.6.0

See Also

Other SparkDataFrame functions: SparkDataFrame-class, agg(), alias(), arrange(), as.data.frame(), attach,SparkDataFrame-method, broadcast(), cache(), checkpoint(), coalesce(), collect(), 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(), withColumn(), withWatermark(), with(), write.df(), write.jdbc(), write.json(), write.orc(), write.parquet(), write.stream(), write.text()

Aliases
  • colnames
  • colnames<-
  • columns
  • columns,SparkDataFrame-method
  • names
  • names,SparkDataFrame-method
  • names<-
  • names<-,SparkDataFrame-method
  • colnames,SparkDataFrame-method
  • colnames<-,SparkDataFrame-method
Examples
# NOT RUN {
sparkR.session()
path <- "path/to/file.json"
df <- read.json(path)
columns(df)
colnames(df)
# }
Documentation reproduced from package SparkR, version 2.4.6, License: Apache License (== 2.0)

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