describe

Computes statistics for numeric and string columns. If no columns are given, this function computes statistics for all numerical or string columns.

Usage

describe(x, col, ...)

# S4 method for SparkDataFrame,character
describe(x, col, ...)

# S4 method for SparkDataFrame,ANY
describe(x)

Arguments

x

a SparkDataFrame to be computed.

col

a string of name.

...

additional expressions.

Value

A SparkDataFrame.

Note

describe(SparkDataFrame, character) since 1.4.0

describe(SparkDataFrame) since 1.4.0

See also

See summary for expanded statistics and control over which statistics to compute.

Other SparkDataFrame functions: SparkDataFrame-class, agg(), alias(), arrange(), as.data.frame(), attach,SparkDataFrame-method, broadcast(), cache(), checkpoint(), coalesce(), collect(), colnames(), coltypes(), createOrReplaceTempView(), crossJoin(), cube(), dapply(), dapplyCollect(), dim(), distinct(), drop(), dropDuplicates(), dropna(), dtypes(), except(), exceptAll(), explain(), filter(), first(), gapply(), gapplyCollect(), getNumPartitions(), group_by(), head(), hint(), histogram(), insertInto(), intersect(), intersectAll(), isLocal(), isStreaming(), join(), limit(), localCheckpoint(), merge(), mutate(), ncol(), nrow(), persist(), printSchema(), randomSplit(), rbind(), rename(), repartition(), repartitionByRange(), rollup(), sample(), saveAsTable(), schema(), select(), selectExpr(), show(), showDF(), storageLevel(), str(), subset(), summary(), take(), toJSON(), union(), unionAll(), unionByName(), unpersist(), unpivot(), with(), withColumn(), withWatermark(), write.df(), write.jdbc(), write.json(), write.orc(), write.parquet(), write.stream(), write.text()

Examples

if (FALSE) {
sparkR.session()
path <- "path/to/file.json"
df <- read.json(path)
describe(df)
describe(df, "col1")
describe(df, "col1", "col2")
}