1 files changed, 0 insertions, 88 deletions
diff --git a/python/pyspark/sql/group.py b/python/pyspark/sql/group.py
index 946b53e71c..71c0bccc5e 100644
--- a/python/pyspark/sql/group.py
+++ b/python/pyspark/sql/group.py
@@ -167,94 +167,6 @@ class GroupedData(object):
         [Row(sum(age)=7, sum(height)=165)]
         """
 
-    @df_varargs_api
-    @since(1.6)
-    def stddev(self, *cols):
-        """Compute the sample standard deviation for each numeric columns for each group.
-
-        :param cols: list of column names (string). Non-numeric columns are ignored.
-
-        >>> df3.groupBy().stddev('age', 'height').collect()
-        [Row(STDDEV(age)=2.12..., STDDEV(height)=3.53...)]
-        """
-
-    @df_varargs_api
-    @since(1.6)
-    def stddev_samp(self, *cols):
-        """Compute the sample standard deviation for each numeric columns for each group.
-
-        :param cols: list of column names (string). Non-numeric columns are ignored.
-
-        >>> df3.groupBy().stddev_samp('age', 'height').collect()
-        [Row(STDDEV_SAMP(age)=2.12..., STDDEV_SAMP(height)=3.53...)]
-        """
-
-    @df_varargs_api
-    @since(1.6)
-    def stddev_pop(self, *cols):
-        """Compute the population standard deviation for each numeric columns for each group.
-
-        :param cols: list of column names (string). Non-numeric columns are ignored.
-
-        >>> df3.groupBy().stddev_pop('age', 'height').collect()
-        [Row(STDDEV_POP(age)=1.5, STDDEV_POP(height)=2.5)]
-        """
-
-    @df_varargs_api
-    @since(1.6)
-    def variance(self, *cols):
-        """Compute the sample variance for each numeric columns for each group.
-
-        :param cols: list of column names (string). Non-numeric columns are ignored.
-
-        >>> df3.groupBy().variance('age', 'height').collect()
-        [Row(VARIANCE(age)=2.25, VARIANCE(height)=6.25)]
-        """
-
-    @df_varargs_api
-    @since(1.6)
-    def var_pop(self, *cols):
-        """Compute the sample variance for each numeric columns for each group.
-
-        :param cols: list of column names (string). Non-numeric columns are ignored.
-
-        >>> df3.groupBy().var_pop('age', 'height').collect()
-        [Row(VAR_POP(age)=2.25, VAR_POP(height)=6.25)]
-        """
-
-    @df_varargs_api
-    @since(1.6)
-    def var_samp(self, *cols):
-        """Compute the sample variance for each numeric columns for each group.
-
-        :param cols: list of column names (string). Non-numeric columns are ignored.
-
-        >>> df3.groupBy().var_samp('age', 'height').collect()
-        [Row(VAR_SAMP(age)=4.5, VAR_SAMP(height)=12.5)]
-        """
-
-    @df_varargs_api
-    @since(1.6)
-    def skewness(self, *cols):
-        """Compute the skewness for each numeric columns for each group.
-
-        :param cols: list of column names (string). Non-numeric columns are ignored.
-
-        >>> df3.groupBy().skewness('age', 'height').collect()
-        [Row(SKEWNESS(age)=0.0, SKEWNESS(height)=0.0)]
-        """
-
-    @df_varargs_api
-    @since(1.6)
-    def kurtosis(self, *cols):
-        """Compute the kurtosis for each numeric columns for each group.
-
-        :param cols: list of column names (string). Non-numeric columns are ignored.
-
-        >>> df3.groupBy().kurtosis('age', 'height').collect()
-        [Row(KURTOSIS(age)=-2.0, KURTOSIS(height)=-2.0)]
-        """
-
 
 def _test():
     import doctest