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The following commit(s) were added to refs/heads/master by this push:
     new 1d2159f8881 [SPARK-40852][CONNECT][PYTHON][DOC][FOLLOWUP] Add document 
for `DataFrame.summary`
1d2159f8881 is described below

commit 1d2159f888139e65c80db2003d521b0f684df83a
Author: Jiaan Geng <belie...@163.com>
AuthorDate: Wed Dec 7 18:49:21 2022 +0800

    [SPARK-40852][CONNECT][PYTHON][DOC][FOLLOWUP] Add document for 
`DataFrame.summary`
    
    ### What changes were proposed in this pull request?
    This PR adds document for `DataFrame.summary`.
    
    ### Why are the changes needed?
    This PR adds document for `DataFrame.summary`.
    
    ### Does this PR introduce _any_ user-facing change?
    'No'.
    `DataFrame.summary` is a new API
    
    ### How was this patch tested?
    N/A
    
    Closes #38962 from beliefer/SPARK-40852_followup.
    
    Authored-by: Jiaan Geng <belie...@163.com>
    Signed-off-by: Ruifeng Zheng <ruife...@apache.org>
---
 python/pyspark/sql/connect/dataframe.py | 32 ++++++++++++++++++++++++++++++++
 1 file changed, 32 insertions(+)

diff --git a/python/pyspark/sql/connect/dataframe.py 
b/python/pyspark/sql/connect/dataframe.py
index 1e1b5dbff21..f268dc431b8 100644
--- a/python/pyspark/sql/connect/dataframe.py
+++ b/python/pyspark/sql/connect/dataframe.py
@@ -1316,6 +1316,38 @@ class DataFrame(object):
         return DataFrameStatFunctions(self)
 
     def summary(self, *statistics: str) -> "DataFrame":
+        """Computes specified statistics for numeric and string columns.
+
+        .. versionadded:: 3.4.0
+
+        Available statistics are:
+        count
+        mean
+        stddev
+        min
+        max
+        arbitrary approximate percentiles specified as a percentage (e.g. 75%)
+        count_distinct
+        approx_count_distinct
+
+        Notes
+        -----
+        If no statistics are given, this function computes 'count', 'mean', 
'stddev', 'min',
+        'approximate quartiles' (percentiles at 25%, 50%, and 75%), and 'max'.
+        This function is meant for exploratory data analysis, as we make no 
guarantee about the
+        backward compatibility of the schema of the resulting 
:class:`DataFrame`. If you want to
+        programmatically compute summary statistics, use the `agg` function 
instead.
+
+        Parameters
+        ----------
+        statistics : str, list, optional
+             Statistics from above list to be computed.
+
+        Returns
+        -------
+        :class:`DataFrame`
+            A new DataFrame that computes specified statistics for given 
DataFrame.
+        """
         _statistics: List[str] = list(statistics)
         for s in _statistics:
             if not isinstance(s, str):


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