| 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. |
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, arrange,
as.data.frame,
attach,SparkDataFrame-method,
cache, checkpoint,
coalesce, collect,
colnames, coltypes,
createOrReplaceTempView,
crossJoin, dapplyCollect,
dapply, describe,
dim, distinct,
dropDuplicates, dropna,
drop, dtypes,
except, explain,
filter, first,
gapplyCollect, gapply,
getNumPartitions, group_by,
head, hint,
insertInto, intersect,
isLocal, isStreaming,
join, limit,
merge, mutate,
ncol, nrow,
persist, printSchema,
randomSplit, rbind,
registerTempTable, rename,
repartition, sample,
saveAsTable, schema,
selectExpr, select,
showDF, show,
storageLevel, str,
subset, take,
toJSON, union,
unpersist, withColumn,
with, write.df,
write.jdbc, write.json,
write.orc, write.parquet,
write.stream, write.text
## 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)