Github user rxin commented on a diff in the pull request:
https://github.com/apache/spark/pull/5073#discussion_r26632557
--- Diff: sql/core/src/main/scala/org/apache/spark/sql/DataFrame.scala ---
@@ -752,6 +752,55 @@ class DataFrame private[sql](
}
/**
+ * Compute numerical statistics for given columns of this [[DataFrame]]:
+ * count, mean (avg), stddev (standard deviation), min, max.
+ * Each row of the resulting [[DataFrame]] contains column with
statistic name
+ * and columns with statistic results for each given column.
+ * If no columns are given then computes for all numerical columns.
+ *
+ * {{{
+ * df.describe("age", "height")
+ *
+ * // summary age height
+ * // count 10.0 10.0
+ * // mean 53.3 178.05
+ * // stddev 11.6 15.7
+ * // min 18.0 163.0
+ * // max 92.0 192.0
+ * }}}
+ */
+ @scala.annotation.varargs
+ def describe(cols: String*): DataFrame = {
+
+ def aggCol(name: String = "") = s"'$name' as summary"
+ val statistics = List[(String, Expression => Expression)](
+ "count" -> (expr => Count(expr)),
+ "mean" -> (expr => Average(expr)),
+ "stddev" -> (expr => Sqrt(Subtract(Average(Multiply(expr, expr)),
+ Multiply(Average(expr),
Average(expr))))),
+ "min" -> (expr => Min(expr)),
+ "max" -> (expr => Max(expr)))
+
+ val numCols = if (cols.isEmpty) numericColumns.map(_.prettyString)
else cols
--- End diff --
numCols is a bad name here because this can mean the number of columns
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