DOC: Fix docstring title sections

pandas/_libs/tslibs/period.pyx

@@ -1739,7 +1739,7 @@ cdef class _Period(object):
         -------
         Timestamp
 
-        See also
+        See Also
         --------
         Period.end_time : Return the end Timestamp.
         Period.dayofyear : Return the day of year.

pandas/core/accessor.py

@@ -247,7 +247,7 @@ def plot(self):
     >>> ds.geo.plot()
     # plots data on a map
 
-See also
+See Also
 --------
 %(others)s
 """

pandas/core/arrays/categorical.py

@@ -313,7 +313,7 @@ class Categorical(ExtensionArray, PandasObject):
     See the `user guide
     <http://pandas.pydata.org/pandas-docs/stable/categorical.html>`_ for more.
 
-    See also
+    See Also
     --------
     pandas.api.types.CategoricalDtype : Type for categorical data
     CategoricalIndex : An Index with an underlying ``Categorical``
@@ -457,7 +457,7 @@ def categories(self):
             If the new categories do not validate as categories or if the
             number of new categories is unequal the number of old categories
 
-        See also
+        See Also
         --------
         rename_categories
         reorder_categories
@@ -823,7 +823,7 @@ def set_categories(self, new_categories, ordered=None, rename=False,
         -------
         cat : Categorical with reordered categories or None if inplace.
 
-        See also
+        See Also
         --------
         rename_categories
         reorder_categories
@@ -894,7 +894,7 @@ def rename_categories(self, new_categories, inplace=False):
            With ``inplace=False``, the new categorical is returned.
            With ``inplace=True``, there is no return value.
 
-        See also
+        See Also
         --------
         reorder_categories
         add_categories
@@ -971,7 +971,7 @@ def reorder_categories(self, new_categories, ordered=None, inplace=False):
         -------
         cat : Categorical with reordered categories or None if inplace.
 
-        See also
+        See Also
         --------
         rename_categories
         add_categories
@@ -1010,7 +1010,7 @@ def add_categories(self, new_categories, inplace=False):
         -------
         cat : Categorical with new categories added or None if inplace.
 
-        See also
+        See Also
         --------
         rename_categories
         reorder_categories
@@ -1058,7 +1058,7 @@ def remove_categories(self, removals, inplace=False):
         -------
         cat : Categorical with removed categories or None if inplace.
 
-        See also
+        See Also
         --------
         rename_categories
         reorder_categories
@@ -1100,7 +1100,7 @@ def remove_unused_categories(self, inplace=False):
         -------
         cat : Categorical with unused categories dropped or None if inplace.
 
-        See also
+        See Also
         --------
         rename_categories
         reorder_categories
@@ -1364,7 +1364,7 @@ def isna(self):
         -------
         a boolean array of whether my values are null
 
-        See also
+        See Also
         --------
         isna : top-level isna
         isnull : alias of isna
@@ -1387,7 +1387,7 @@ def notna(self):
         -------
         a boolean array of whether my values are not null
 
-        See also
+        See Also
         --------
         notna : top-level notna
         notnull : alias of notna
@@ -1503,7 +1503,7 @@ def argsort(self, *args, **kwargs):
         -------
         argsorted : numpy array
 
-        See also
+        See Also
         --------
         numpy.ndarray.argsort
 
@@ -2322,7 +2322,7 @@ def repeat(self, repeats, *args, **kwargs):
         """
         Repeat elements of a Categorical.
 
-        See also
+        See Also
         --------
         numpy.ndarray.repeat
 

pandas/core/arrays/datetimes.py

@@ -874,7 +874,7 @@ def to_period(self, freq=None):
         PeriodIndex(['2017-01-01', '2017-01-02'],
                     dtype='period[D]', freq='D')
 
-        See also
+        See Also
         --------
         pandas.PeriodIndex: Immutable ndarray holding ordinal values
         pandas.DatetimeIndex.to_pydatetime: Return DatetimeIndex as object

pandas/core/arrays/period.py

@@ -636,7 +636,7 @@ def repeat(self, repeats, *args, **kwargs):
         """
         Repeat elements of a PeriodArray.
 
-        See also
+        See Also
         --------
         numpy.ndarray.repeat
         """

pandas/core/base.py

@@ -820,7 +820,7 @@ def argmax(self, axis=None):
         """
         return a ndarray of the maximum argument indexer
 
-        See also
+        See Also
         --------
         numpy.ndarray.argmax
         """
@@ -863,7 +863,7 @@ def argmin(self, axis=None):
         """
         return a ndarray of the minimum argument indexer
 
-        See also
+        See Also
         --------
         numpy.ndarray.argmin
         """

pandas/core/frame.py

@@ -346,7 +346,7 @@ class DataFrame(NDFrame):
     1  4  5  6
     2  7  8  9
 
-    See also
+    See Also
     --------
     DataFrame.from_records : constructor from tuples, also record arrays
     DataFrame.from_dict : from dicts of Series, arrays, or dicts
@@ -1694,7 +1694,7 @@ def from_csv(cls, path, header=0, sep=',', index_col=0, parse_dates=True,
             datetime format based on the first datetime string. If the format
             can be inferred, there often will be a large parsing speed-up.
 
-        See also
+        See Also
         --------
         pandas.read_csv
 
@@ -5589,7 +5589,7 @@ def pivot(self, index=None, columns=None, values=None):
         -------
         table : DataFrame
 
-        See also
+        See Also
         --------
         DataFrame.pivot : pivot without aggregation that can handle
             non-numeric data
@@ -5794,7 +5794,7 @@ def unstack(self, level=-1, fill_value=None):
 
             .. versionadded:: 0.18.0
 
-        See also
+        See Also
         --------
         DataFrame.pivot : Pivot a table based on column values.
         DataFrame.stack : Pivot a level of the column labels (inverse operation
@@ -5864,7 +5864,7 @@ def unstack(self, level=-1, fill_value=None):
     col_level : int or string, optional
         If columns are a MultiIndex then use this level to melt.
 
-    See also
+    See Also
     --------
     %(other)s
     pivot_table
@@ -6105,7 +6105,7 @@ def _gotitem(self,
     3    NaN
     dtype: float64
 
-    See also
+    See Also
     --------
     DataFrame.apply : Perform any type of operations.
     DataFrame.transform : Perform transformation type operations.
@@ -6239,7 +6239,7 @@ def apply(self, func, axis=0, broadcast=None, raw=False, reduce=None,
         side-effects, as they will take effect twice for the first
         column/row.
 
-        See also
+        See Also
         --------
         DataFrame.applymap: For elementwise operations
         DataFrame.aggregate: only perform aggregating type operations
@@ -6348,7 +6348,7 @@ def applymap(self, func):
         DataFrame
             Transformed DataFrame.
 
-        See also
+        See Also
         --------
         DataFrame.apply : Apply a function along input axis of DataFrame
 
@@ -6431,7 +6431,7 @@ def append(self, other, ignore_index=False,
         those rows to a list and then concatenate the list with the original
         DataFrame all at once.
 
-        See also
+        See Also
         --------
         pandas.concat : General function to concatenate DataFrame, Series
             or Panel objects

pandas/core/generic.py

@@ -1848,7 +1848,7 @@ def empty(self):
         >>> df.dropna().empty
         True
 
-        See also
+        See Also
         --------
         pandas.Series.dropna
         pandas.DataFrame.dropna
@@ -5307,7 +5307,7 @@ def astype(self, dtype, copy=True, errors='raise', **kwargs):
         1     2
         dtype: int64
 
-        See also
+        See Also
         --------
         pandas.to_datetime : Convert argument to datetime.
         pandas.to_timedelta : Convert argument to timedelta.
@@ -10088,7 +10088,7 @@ def _doc_parms(cls):
 """
 
 _all_see_also = """\
-See also
+See Also
 --------
 pandas.Series.all : Return True if all elements are True
 pandas.DataFrame.any : Return True if one (or more) elements are True
@@ -10115,7 +10115,7 @@ def _doc_parms(cls):
 -------
 %(outname)s : %(name1)s or %(name2)s\n
 %(examples)s
-See also
+See Also
 --------
 pandas.core.window.Expanding.%(accum_func_name)s : Similar functionality
     but ignores ``NaN`` values.

pandas/core/groupby/generic.py

@@ -733,7 +733,7 @@ def _selection_name(self):
     1    1    2
     2    3    4
 
-    See also
+    See Also
     --------
     pandas.Series.groupby.apply
     pandas.Series.groupby.transform
@@ -1288,7 +1288,7 @@ class DataFrameGroupBy(NDFrameGroupBy):
     1   1   2  0.590716
     2   3   4  0.704907
 
-    See also
+    See Also
     --------
     pandas.DataFrame.groupby.apply
     pandas.DataFrame.groupby.transform

pandas/core/groupby/groupby.py

@@ -42,7 +42,7 @@ class providing the base-class of operations.
 
 _doc_template = """
 
-        See also
+        See Also
         --------
         pandas.Series.%(name)s
         pandas.DataFrame.%(name)s
@@ -90,7 +90,7 @@ class providing the base-class of operations.
     --------
     {examples}
 
-    See also
+    See Also
     --------
     pipe : Apply function to the full GroupBy object instead of to each
         group.
@@ -252,7 +252,7 @@ class providing the base-class of operations.
 -------
 %(klass)s
 
-See also
+See Also
 --------
 aggregate, transform
 
@@ -1623,7 +1623,7 @@ def ngroup(self, ascending=True):
         5    0
         dtype: int64
 
-        See also
+        See Also
         --------
         .cumcount : Number the rows in each group.
         """
@@ -1679,7 +1679,7 @@ def cumcount(self, ascending=True):
         5    0
         dtype: int64
 
-        See also
+        See Also
         --------
         .ngroup : Number the groups themselves.
         """