histogram {SparkR} | R Documentation |
This function computes a histogram for a given SparkR Column.
## S4 method for signature 'SparkDataFrame,characterOrColumn' histogram(df, col, nbins = 10)
df |
the SparkDataFrame containing the Column to build the histogram from. |
nbins |
the number of bins (optional). Default value is 10. |
colname |
the name of the column to build the histogram from. |
a data.frame with the histogram statistics, i.e., counts and centroids.
Other SparkDataFrame functions: SparkDataFrame-class
,
[[
, agg
,
arrange
, as.data.frame
,
attach
, cache
,
collect
, colnames
,
coltypes
, columns
,
count
, dapply
,
describe
, dim
,
distinct
, dropDuplicates
,
dropna
, drop
,
dtypes
, except
,
explain
, filter
,
first
, group_by
,
head
, insertInto
,
intersect
, isLocal
,
join
, limit
,
merge
, mutate
,
ncol
, persist
,
printSchema
,
registerTempTable
, rename
,
repartition
, sample
,
saveAsTable
, selectExpr
,
select
, showDF
,
show
, str
,
take
, unionAll
,
unpersist
, withColumn
,
write.df
, write.jdbc
,
write.json
, write.parquet
,
write.text
## Not run:
##D
##D # Create a SparkDataFrame from the Iris dataset
##D irisDF <- createDataFrame(sqlContext, 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)