Compute histogram statistics for given column

Description

This function computes a histogram for a given SparkR Column.

Usage

## S4 method for signature 'SparkDataFrame,characterOrColumn'
histogram(df, col, nbins = 10)

Arguments

Value

a data.frame with the histogram statistics, i.e., counts and centroids.

Note

histogram since 2.0.0

See Also

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(), 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(), 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 
##D # Create a SparkDataFrame from the Iris dataset
##D irisDF <- createDataFrame(iris)
##D 
##D # Compute histogram statistics
##D histStats <- histogram(irisDF, irisDF$Sepal_Length, nbins = 12)
##D 
##D # Once SparkR has computed the histogram statistics, the histogram can be
##D # rendered using the ggplot2 library:
##D 
##D require(ggplot2)
##D plot <- ggplot(histStats, aes(x = centroids, y = counts)) +
##D         geom_bar(stat = "identity") +
##D         xlab("Sepal_Length") + ylab("Frequency")
## End(Not run)