Github user davies commented on a diff in the pull request:
https://github.com/apache/spark/pull/10876#discussion_r52645800
--- Diff: python/pyspark/sql/functions.py ---
@@ -254,15 +254,44 @@ def corr(col1, col2):
>>> a = [x * x - 2 * x + 3.5 for x in range(20)]
>>> b = range(20)
- >>> corrDf = sqlContext.createDataFrame(zip(a, b))
- >>> corrDf = corrDf.agg(corr(corrDf._1, corrDf._2).alias('c'))
- >>> corrDf.selectExpr('abs(c - 0.9572339139475857) < 1e-16 as
t').collect()
- [Row(t=True)]
+ >>> df = sqlContext.createDataFrame(zip(a, b))
+ >>> df.agg(corr(df._1, df._2))
+ DataFrame[corr(_1,_2): double]
"""
sc = SparkContext._active_spark_context
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"])
+ >>> df.agg(covar_pop("a", "b"))
+ DataFrame[covar_pop(a,b): double]
+ """
+ sc = SparkContext._active_spark_context
+ return Column(sc._jvm.functions.covar_pop(_to_java_column(col1),
_to_java_column(col2)))
+
+
+@since(2.0)
+def covar_samp(col1, col2):
+ """Returns a new :class:`Column` for the sample 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"])
--- End diff --
How about a == b, then the result will be zero?
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