Github user holdenk commented on a diff in the pull request:
https://github.com/apache/spark/pull/10876#discussion_r50753821
--- Diff: python/pyspark/sql/functions.py ---
@@ -263,6 +263,38 @@ def corr(col1, col2):
return Column(sc._jvm.functions.corr(_to_java_column(col1),
_to_java_column(col2)))
+@since(2.0)
+def covar_pop(col1, col2):
+ """Returns a new :class:`Column` for the population covariance of
``col1``
+ and ``col2``.
+
+ >>> a = [x * x - 2 * x + 3.5 for x in range(20)]
+ >>> b = range(20)
+ >>> df = sqlContext.createDataFrame(zip(a, b), ["a", "b"])
+ >>> covDf = df.agg(covar_pop("a", "b").alias('c'))
+ >>> covDf.select("c").collect()
+ [Row(c=565.25)]
--- End diff --
Should we maybe compare with a tolerance as done in the other doctests
since floating point?
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