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Showing content from https://spark.apache.org/docs/latest/api/R/reference/histogram.html below:

Compute histogram statistics for given column — histogram • SparkR

This function computes a histogram for a given SparkR Column.

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

df

the SparkDataFrame containing the Column to build the histogram from.

col

the column as Character string or a Column to build the histogram from.

nbins

the number of bins (optional). Default value is 10.

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

histogram since 2.0.0

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(), 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(), unpivot(), withColumn(), withWatermark(), with(), write.df(), write.jdbc(), write.json(), write.orc(), write.parquet(), write.stream(), write.text()

if (FALSE) { # \dontrun{

# Create a SparkDataFrame from the Iris dataset
irisDF <- createDataFrame(iris)

# Compute histogram statistics
histStats <- histogram(irisDF, irisDF$Sepal_Length, nbins = 12)

# Once SparkR has computed the histogram statistics, the histogram can be
# rendered using the ggplot2 library:

require(ggplot2)
plot <- ggplot(histStats, aes(x = centroids, y = counts)) +
        geom_bar(stat = "identity") +
        xlab("Sepal_Length") + ylab("Frequency")
} # }

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