| 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)