DOC: RT03 fix for min,max,mean,meadian,kurt,skew

ci/code_checks.sh

@@ -96,29 +96,24 @@ if [[ -z "$CHECK" || "$CHECK" == "docstrings" ]]; then
         -i "pandas.DataFrame.hist RT03" \
         -i "pandas.DataFrame.infer_objects RT03" \
         -i "pandas.DataFrame.keys SA01" \
-        -i "pandas.DataFrame.kurt RT03,SA01" \
-        -i "pandas.DataFrame.kurtosis RT03,SA01" \
+        -i "pandas.DataFrame.kurt SA01" \
+        -i "pandas.DataFrame.kurtosis SA01" \
         -i "pandas.DataFrame.last_valid_index SA01" \
         -i "pandas.DataFrame.mask RT03" \
-        -i "pandas.DataFrame.max RT03" \
-        -i "pandas.DataFrame.mean RT03,SA01" \
-        -i "pandas.DataFrame.median RT03,SA01" \
-        -i "pandas.DataFrame.min RT03" \
+        -i "pandas.DataFrame.mean SA01" \
+        -i "pandas.DataFrame.median SA01" \
         -i "pandas.DataFrame.pad PR01,SA01" \
         -i "pandas.DataFrame.plot PR02,SA01" \
         -i "pandas.DataFrame.pop SA01" \
-        -i "pandas.DataFrame.prod RT03" \
-        -i "pandas.DataFrame.product RT03" \
         -i "pandas.DataFrame.reorder_levels SA01" \
-        -i "pandas.DataFrame.sem PR01,RT03,SA01" \
-        -i "pandas.DataFrame.skew RT03,SA01" \
+        -i "pandas.DataFrame.sem PR01,SA01" \
+        -i "pandas.DataFrame.skew SA01" \
         -i "pandas.DataFrame.sparse PR01,SA01" \
         -i "pandas.DataFrame.sparse.density SA01" \
         -i "pandas.DataFrame.sparse.from_spmatrix SA01" \
         -i "pandas.DataFrame.sparse.to_coo SA01" \
         -i "pandas.DataFrame.sparse.to_dense SA01" \
-        -i "pandas.DataFrame.std PR01,RT03,SA01" \
-        -i "pandas.DataFrame.sum RT03" \
+        -i "pandas.DataFrame.std PR01,SA01" \
         -i "pandas.DataFrame.swapaxes PR01,SA01" \
         -i "pandas.DataFrame.swaplevel SA01" \
         -i "pandas.DataFrame.to_feather SA01" \
@@ -130,7 +125,7 @@ if [[ -z "$CHECK" || "$CHECK" == "docstrings" ]]; then
         -i "pandas.DataFrame.tz_localize SA01" \
         -i "pandas.DataFrame.unstack RT03" \
         -i "pandas.DataFrame.value_counts RT03" \
-        -i "pandas.DataFrame.var PR01,RT03,SA01" \
+        -i "pandas.DataFrame.var PR01,SA01" \
         -i "pandas.DataFrame.where RT03" \
         -i "pandas.DatetimeIndex.ceil SA01" \
         -i "pandas.DatetimeIndex.date SA01" \
@@ -392,19 +387,17 @@ if [[ -z "$CHECK" || "$CHECK" == "docstrings" ]]; then
         -i "pandas.Series.is_unique SA01" \
         -i "pandas.Series.item SA01" \
         -i "pandas.Series.keys SA01" \
-        -i "pandas.Series.kurt RT03,SA01" \
-        -i "pandas.Series.kurtosis RT03,SA01" \
+        -i "pandas.Series.kurt SA01" \
+        -i "pandas.Series.kurtosis SA01" \
         -i "pandas.Series.last_valid_index SA01" \
         -i "pandas.Series.le PR07,SA01" \
         -i "pandas.Series.list.__getitem__ SA01" \
         -i "pandas.Series.list.flatten SA01" \
         -i "pandas.Series.list.len SA01" \
         -i "pandas.Series.lt PR07,SA01" \
         -i "pandas.Series.mask RT03" \
-        -i "pandas.Series.max RT03" \
-        -i "pandas.Series.mean RT03,SA01" \
-        -i "pandas.Series.median RT03,SA01" \
-        -i "pandas.Series.min RT03" \
+        -i "pandas.Series.mean SA01" \
+        -i "pandas.Series.median SA01" \
         -i "pandas.Series.mod PR07" \
         -i "pandas.Series.mode SA01" \
         -i "pandas.Series.mul PR07" \
@@ -416,8 +409,6 @@ if [[ -z "$CHECK" || "$CHECK" == "docstrings" ]]; then
         -i "pandas.Series.plot PR02,SA01" \
         -i "pandas.Series.pop RT03,SA01" \
         -i "pandas.Series.pow PR07" \
-        -i "pandas.Series.prod RT03" \
-        -i "pandas.Series.product RT03" \
         -i "pandas.Series.radd PR07" \
         -i "pandas.Series.rdiv PR07" \
         -i "pandas.Series.reorder_levels RT03,SA01" \
@@ -427,18 +418,18 @@ if [[ -z "$CHECK" || "$CHECK" == "docstrings" ]]; then
         -i "pandas.Series.rpow PR07" \
         -i "pandas.Series.rsub PR07" \
         -i "pandas.Series.rtruediv PR07" \
-        -i "pandas.Series.sem PR01,RT03,SA01" \
+        -i "pandas.Series.sem PR01,SA01" \
         -i "pandas.Series.shape SA01" \
         -i "pandas.Series.size SA01" \
-        -i "pandas.Series.skew RT03,SA01" \
+        -i "pandas.Series.skew SA01" \
         -i "pandas.Series.sparse PR01,SA01" \
         -i "pandas.Series.sparse.density SA01" \
         -i "pandas.Series.sparse.fill_value SA01" \
         -i "pandas.Series.sparse.from_coo PR07,SA01" \
         -i "pandas.Series.sparse.npoints SA01" \
         -i "pandas.Series.sparse.sp_values SA01" \
         -i "pandas.Series.sparse.to_coo PR07,RT03,SA01" \
-        -i "pandas.Series.std PR01,RT03,SA01" \
+        -i "pandas.Series.std PR01,SA01" \
         -i "pandas.Series.str PR01,SA01" \
         -i "pandas.Series.str.capitalize RT03" \
         -i "pandas.Series.str.casefold RT03" \
@@ -471,7 +462,6 @@ if [[ -z "$CHECK" || "$CHECK" == "docstrings" ]]; then
         -i "pandas.Series.str.zfill RT03" \
         -i "pandas.Series.struct.dtypes SA01" \
         -i "pandas.Series.sub PR07" \
-        -i "pandas.Series.sum RT03" \
         -i "pandas.Series.swaplevel SA01" \
         -i "pandas.Series.to_dict SA01" \
         -i "pandas.Series.to_frame SA01" \
@@ -486,7 +476,7 @@ if [[ -z "$CHECK" || "$CHECK" == "docstrings" ]]; then
         -i "pandas.Series.unstack SA01" \
         -i "pandas.Series.update PR07,SA01" \
         -i "pandas.Series.value_counts RT03" \
-        -i "pandas.Series.var PR01,RT03,SA01" \
+        -i "pandas.Series.var PR01,SA01" \
         -i "pandas.Series.where RT03" \
         -i "pandas.SparseDtype SA01" \
         -i "pandas.Timedelta PR07,SA01" \

pandas/core/generic.py

@@ -11813,7 +11813,9 @@ def last_valid_index(self) -> Hashable:
 
 Returns
 -------
-{name1} or scalar\
+{return_type}
+    The result of applying the {name} function to the {obj_type} elements,
+    possibly just for rows or columns based on the ``axis`` parameter.\
 {see_also}\
 {examples}
 """
@@ -11846,7 +11848,9 @@ def last_valid_index(self) -> Hashable:
 
 Returns
 -------
-{name1} or scalar\
+{return_type}
+    The result of applying the {name} function to the {obj_type} elements,
+    possibly just for rows or columns based on the ``axis`` parameter.\
 {see_also}\
 {examples}
 """
@@ -11876,7 +11880,9 @@ def last_valid_index(self) -> Hashable:
 
 Returns
 -------
-{name1} or {name2} (if level specified) \
+{return_type}
+    The result of applying the {name} function to the {obj_type} elements,
+    possibly just for rows or columns based on the ``axis`` parameter.\
 {notes}\
 {examples}
 """
@@ -11974,9 +11980,9 @@ def last_valid_index(self) -> Hashable:
 
 Returns
 -------
-{name1} or {name2}
-    If level is specified, then, {name2} is returned; otherwise, {name1}
-    is returned.
+{return_type}
+    The result of applying the {name} function to the {obj_type} elements,
+    possibly just for rows or columns based on the ``axis`` parameter.
 
 {see_also}
 {examples}"""
@@ -12061,19 +12067,20 @@ def last_valid_index(self) -> Hashable:
 
 Returns
 -------
-{name1} or {name2}
-    Return cumulative {desc} of {name1} or {name2}.
+{return_type}
+    The result of applying the cumulative {desc} function to the {obj_type} elements,
+    possibly just for rows or columns based on the ``axis`` parameter.
 
 See Also
 --------
 core.window.expanding.Expanding.{accum_func_name} : Similar functionality
     but ignores ``NaN`` values.
-{name2}.{accum_func_name} : Return the {desc} over
-    {name2} axis.
-{name2}.cummax : Return cumulative maximum over {name2} axis.
-{name2}.cummin : Return cumulative minimum over {name2} axis.
-{name2}.cumsum : Return cumulative sum over {name2} axis.
-{name2}.cumprod : Return cumulative product over {name2} axis.
+{obj_type}.{accum_func_name} : Return the {desc} over
+    {obj_type} axis.
+{obj_type}.cummax : Return cumulative maximum over {obj_type} axis.
+{obj_type}.cummin : Return cumulative minimum over {obj_type} axis.
+{obj_type}.cumsum : Return cumulative sum over {obj_type} axis.
+{obj_type}.cumprod : Return cumulative product over {obj_type} axis.
 
 {examples}"""
 
@@ -12527,14 +12534,6 @@ def make_doc(name: str, ndim: int) -> str:
     """
     Generate the docstring for a Series/DataFrame reduction.
     """
-    if ndim == 1:
-        name1 = "scalar"
-        name2 = "Series"
-        axis_descr = "{index (0)}"
-    else:
-        name1 = "Series"
-        name2 = "DataFrame"
-        axis_descr = "{index (0), columns (1)}"
 
     if name == "any":
         base_doc = _bool_doc
@@ -12862,11 +12861,24 @@ def make_doc(name: str, ndim: int) -> str:
     else:
         raise NotImplementedError
 
+    if ndim == 1:
+        return_type = "Scalar"
+        axis_descr = "{index (0)}"
+        obj_type = "Series"
+        if base_doc in (_cnum_doc):
+            return_type = "Series or Scalar"
+    else:
+        return_type = "Series or Scalar"
+        axis_descr = "{index (0), columns (1)}"
+        obj_type = "DataFrame"
+        if base_doc in (_cnum_doc):
+            return_type = "DataFrame or Series"
+
     docstr = base_doc.format(
         desc=desc,
         name=name,
-        name1=name1,
-        name2=name2,
+        return_type=return_type,
+        obj_type=obj_type,
         axis_descr=axis_descr,
         see_also=see_also,
         examples=examples,