DOC: Fix format of the See Also descriptions (#23654)

* pandas refs 23630, partial.

Author: syutbai

pandas/core/arrays/categorical.py

@@ -315,8 +315,8 @@ class Categorical(ExtensionArray, PandasObject):
 
  See Also
  --------
- pandas.api.types.CategoricalDtype : Type for categorical data
- CategoricalIndex : An Index with an underlying ``Categorical``
+ pandas.api.types.CategoricalDtype : Type for categorical data.
+ CategoricalIndex : An Index with an underlying ``Categorical``.
  """
 
  # For comparisons, so that numpy uses our implementation if the compare
@@ -1366,9 +1366,9 @@ def isna(self):
 
  See Also
  --------
- isna : top-level isna
- isnull : alias of isna
- Categorical.notna : boolean inverse of Categorical.isna
+ isna : Top-level isna.
+ isnull : Alias of isna.
+ Categorical.notna : Boolean inverse of Categorical.isna.
 
  """
 
@@ -1389,9 +1389,9 @@ def notna(self):
 
  See Also
  --------
- notna : top-level notna
- notnull : alias of notna
- Categorical.isna : boolean inverse of Categorical.notna
+ notna : Top-level notna.
+ notnull : Alias of notna.
+ Categorical.isna : Boolean inverse of Categorical.notna.
 
  """
  return ~self.isna()
@@ -2371,7 +2371,7 @@ def isin(self, values):
 
  See Also
  --------
- pandas.Series.isin : equivalent method on Series
+ pandas.Series.isin : Equivalent method on Series.
 
  Examples
  --------

pandas/core/arrays/datetimes.py

@@ -584,7 +584,7 @@ def tz_convert(self, tz):
 
  See Also
  --------
- DatetimeIndex.tz : A timezone that has a variable offset from UTC
+ DatetimeIndex.tz : A timezone that has a variable offset from UTC.
  DatetimeIndex.tz_localize : Localize tz-naive DatetimeIndex to a
  given time zone, or remove timezone from a tz-aware DatetimeIndex.
 
@@ -894,8 +894,8 @@ def to_period(self, freq=None):
 
  See Also
  --------
- pandas.PeriodIndex: Immutable ndarray holding ordinal values
- pandas.DatetimeIndex.to_pydatetime: Return DatetimeIndex as object
+ pandas.PeriodIndex: Immutable ndarray holding ordinal values.
+ pandas.DatetimeIndex.to_pydatetime: Return DatetimeIndex as object.
  """
  from pandas.core.arrays import PeriodArray
 

pandas/core/arrays/interval.py

@@ -94,11 +94,11 @@
 
 See Also
 --------
-Index : The base pandas Index type
-Interval : A bounded slice-like interval; the elements of an %(klass)s
-interval_range : Function to create a fixed frequency IntervalIndex
-cut : Bin values into discrete Intervals
-qcut : Bin values into equal-sized Intervals based on rank or sample quantiles
+Index : The base pandas Index type.
+Interval : A bounded slice-like interval; the elements of an %(klass)s.
+interval_range : Function to create a fixed frequency IntervalIndex.
+cut : Bin values into discrete Intervals.
+qcut : Bin values into equal-sized Intervals based on rank or sample quantiles.
 """
 
 
@@ -244,9 +244,9 @@ def _from_factorized(cls, values, original):
 
  See Also
  --------
- interval_range : Function to create a fixed frequency IntervalIndex
- %(klass)s.from_arrays : Construct from a left and right array
- %(klass)s.from_tuples : Construct from a sequence of tuples
+ interval_range : Function to create a fixed frequency IntervalIndex.
+ %(klass)s.from_arrays : Construct from a left and right array.
+ %(klass)s.from_tuples : Construct from a sequence of tuples.
  """
 
  @classmethod
@@ -354,13 +354,13 @@ def from_arrays(cls, left, right, closed='right', copy=False, dtype=None):
 
  See Also
  --------
- interval_range : Function to create a fixed frequency IntervalIndex
+ interval_range : Function to create a fixed frequency IntervalIndex.
  %(klass)s.from_arrays : Construct an %(klass)s from a left and
- right array
+ right array.
  %(klass)s.from_breaks : Construct an %(klass)s from an array of
- splits
+ splits.
  %(klass)s.from_tuples : Construct an %(klass)s from an
- array-like of tuples
+ array-like of tuples.
  """
 
  _interval_shared_docs['from_tuples'] = """
@@ -389,11 +389,11 @@ def from_arrays(cls, left, right, closed='right', copy=False, dtype=None):
 
  See Also
  --------
- interval_range : Function to create a fixed frequency IntervalIndex
+ interval_range : Function to create a fixed frequency IntervalIndex.
  %(klass)s.from_arrays : Construct an %(klass)s from a left and
- right array
+ right array.
  %(klass)s.from_breaks : Construct an %(klass)s from an array of
- splits
+ splits.
  """
 
  @classmethod
@@ -1027,9 +1027,9 @@ def repeat(self, repeats, **kwargs):
 
  See Also
  --------
- Index.repeat : Equivalent function for Index
- Series.repeat : Equivalent function for Series
- numpy.repeat : Underlying implementation
+ Index.repeat : Equivalent function for Index.
+ Series.repeat : Equivalent function for Series.
+ numpy.repeat : Underlying implementation.
  """
  left_repeat = self.left.repeat(repeats, **kwargs)
  right_repeat = self.right.repeat(repeats, **kwargs)

pandas/core/arrays/period.py

@@ -146,8 +146,8 @@ class PeriodArray(dtl.DatetimeLikeArrayMixin, ExtensionArray):
 
  See Also
  --------
- period_array : Create a new PeriodArray
- pandas.PeriodIndex : Immutable Index for period data
+ period_array : Create a new PeriodArray.
+ pandas.PeriodIndex : Immutable Index for period data.
  """
  # array priority higher than numpy scalars
  __array_priority__ = 1000

pandas/core/base.py

@@ -1014,8 +1014,8 @@ def value_counts(self, normalize=False, sort=True, ascending=False,
 
  See Also
  --------
- Series.count: number of non-NA elements in a Series
- DataFrame.count: number of non-NA elements in a DataFrame
+ Series.count: Number of non-NA elements in a Series.
+ DataFrame.count: Number of non-NA elements in a DataFrame.
 
  Examples
  --------

pandas/core/dtypes/inference.py

@@ -44,7 +44,7 @@ def is_number(obj):
 
  See Also
  --------
- pandas.api.types.is_integer: checks a subgroup of numbers
+ pandas.api.types.is_integer: Checks a subgroup of numbers.
 
  Examples
  --------

pandas/core/dtypes/missing.py

@@ -43,7 +43,7 @@ def isna(obj):
 
  See Also
  --------
- notna : boolean inverse of pandas.isna.
+ notna : Boolean inverse of pandas.isna.
  Series.isna : Detect missing values in a Series.
  DataFrame.isna : Detect missing values in a DataFrame.
  Index.isna : Detect missing values in an Index.
@@ -274,7 +274,7 @@ def notna(obj):
 
  See Also
  --------
- isna : boolean inverse of pandas.notna.
+ isna : Boolean inverse of pandas.notna.
  Series.notna : Detect valid values in a Series.
  DataFrame.notna : Detect valid values in a DataFrame.
  Index.notna : Detect valid values in an Index.

pandas/core/frame.py

@@ -221,9 +221,9 @@
 
 See Also
 --------
-merge_ordered : merge with optional filling/interpolation.
-merge_asof : merge on nearest keys.
-DataFrame.join : similar method using indices.
+merge_ordered : Merge with optional filling/interpolation.
+merge_asof : Merge on nearest keys.
+DataFrame.join : Similar method using indices.
 
 Examples
 --------
@@ -348,10 +348,10 @@ class DataFrame(NDFrame):
 
  See Also
  --------
- DataFrame.from_records : constructor from tuples, also record arrays
- DataFrame.from_dict : from dicts of Series, arrays, or dicts
- DataFrame.from_items : from sequence of (key, value) pairs
- pandas.read_csv, pandas.read_table, pandas.read_clipboard
+ DataFrame.from_records : Constructor from tuples, also record arrays.
+ DataFrame.from_dict : From dicts of Series, arrays, or dicts.
+ DataFrame.from_items : From sequence of (key, value) pairs
+  pandas.read_csv, pandas.read_table, pandas.read_clipboard.
  """
 
  @property
@@ -1066,8 +1066,8 @@ def from_dict(cls, data, orient='columns', dtype=None, columns=None):
  See Also
  --------
  DataFrame.from_records : DataFrame from ndarray (structured
- dtype), list of tuples, dict, or DataFrame
- DataFrame : DataFrame object creation using constructor
+ dtype), list of tuples, dict, or DataFrame.
+ DataFrame : DataFrame object creation using constructor.
 
  Examples
  --------
@@ -1484,9 +1484,9 @@ def to_records(self, index=True, convert_datetime64=None):
 
  See Also
  --------
- DataFrame.from_records: convert structured or record ndarray
+ DataFrame.from_records: Convert structured or record ndarray
  to DataFrame.
- numpy.recarray: ndarray that allows field access using
+ numpy.recarray: An ndarray that allows field access using
  attributes, analogous to typed columns in a
  spreadsheet.
 
@@ -1900,9 +1900,10 @@ def to_stata(self, fname, convert_dates=None, write_index=True,
 
  See Also
  --------
- pandas.read_stata : Import Stata data files
- pandas.io.stata.StataWriter : low-level writer for Stata data files
- pandas.io.stata.StataWriter117 : low-level writer for version 117 files
+ pandas.read_stata : Import Stata data files.
+ pandas.io.stata.StataWriter : Low-level writer for Stata data files.
+ pandas.io.stata.StataWriter117 : Low-level writer for version 117
+ files.
 
  Examples
  --------
@@ -3729,9 +3730,9 @@ def drop(self, labels=None, axis=0, index=None, columns=None,
  --------
  DataFrame.loc : Label-location based indexer for selection by label.
  DataFrame.dropna : Return DataFrame with labels on given axis omitted
- where (all or any) data are missing
+ where (all or any) data are missing.
  DataFrame.drop_duplicates : Return DataFrame with duplicate rows
- removed, optionally only considering certain columns
+ removed, optionally only considering certain columns.
  Series.drop : Return Series with specified index labels removed.
 
  Raises
@@ -4683,7 +4684,7 @@ def nlargest(self, n, columns, keep='first'):
  --------
  DataFrame.nsmallest : Return the first `n` rows ordered by `columns` in
  ascending order.
- DataFrame.sort_values : Sort DataFrame by the values
+ DataFrame.sort_values : Sort DataFrame by the values.
  DataFrame.head : Return the first `n` rows without re-ordering.
 
  Notes
@@ -5070,7 +5071,7 @@ def combine(self, other, func, fill_value=None, overwrite=True):
  See Also
  --------
  DataFrame.combine_first : Combine two DataFrame objects and default to
- non-null values in frame calling the method
+ non-null values in frame calling the method.
  """
  other_idxlen = len(other.index) # save for compare
 
@@ -5176,7 +5177,7 @@ def combine_first(self, other):
  See Also
  --------
  DataFrame.combine : Perform series-wise operation on two DataFrames
- using a given function
+ using a given function.
  """
  import pandas.core.computation.expressions as expressions
 
@@ -5388,9 +5389,9 @@ def update(self, other, join='left', overwrite=True, filter_func=None,
 
  See Also
  --------
- DataFrame.pivot_table : generalization of pivot that can handle
+ DataFrame.pivot_table : Generalization of pivot that can handle
  duplicate values for one index/column pair.
- DataFrame.unstack : pivot based on the index values instead of a
+ DataFrame.unstack : Pivot based on the index values instead of a
  column.
 
  Notes
@@ -5576,8 +5577,8 @@ def pivot(self, index=None, columns=None, values=None):
 
  See Also
  --------
- DataFrame.pivot : pivot without aggregation that can handle
- non-numeric data
+ DataFrame.pivot : Pivot without aggregation that can handle
+ non-numeric data.
  """
 
  @Substitution('')
@@ -6226,9 +6227,9 @@ def apply(self, func, axis=0, broadcast=None, raw=False, reduce=None,
 
  See Also
  --------
- DataFrame.applymap: For elementwise operations
- DataFrame.aggregate: only perform aggregating type operations
- DataFrame.transform: only perform transforming type operations
+ DataFrame.applymap: For elementwise operations.
+ DataFrame.aggregate: Only perform aggregating type operations.
+ DataFrame.transform: Only perform transforming type operations.
 
  Examples
  --------
@@ -6335,7 +6336,7 @@ def applymap(self, func):
 
  See Also
  --------
- DataFrame.apply : Apply a function along input axis of DataFrame
+ DataFrame.apply : Apply a function along input axis of DataFrame.
 
  Examples
  --------
@@ -6419,7 +6420,7 @@ def append(self, other, ignore_index=False,
  See Also
  --------
  pandas.concat : General function to concatenate DataFrame, Series
- or Panel objects
+ or Panel objects.
 
  Examples
  --------
@@ -6886,10 +6887,10 @@ def cov(self, min_periods=None):
 
  See Also
  --------
- pandas.Series.cov : compute covariance with another Series
- pandas.core.window.EWM.cov: exponential weighted sample covariance
- pandas.core.window.Expanding.cov : expanding sample covariance
- pandas.core.window.Rolling.cov : rolling sample covariance
+ pandas.Series.cov : Compute covariance with another Series.
+ pandas.core.window.EWM.cov: Exponential weighted sample covariance.
+ pandas.core.window.Expanding.cov : Expanding sample covariance.
+ pandas.core.window.Rolling.cov : Rolling sample covariance.
 
  Notes
  -----
@@ -7046,11 +7047,11 @@ def count(self, axis=0, level=None, numeric_only=False):
 
  See Also
  --------
- Series.count: number of non-NA elements in a Series
- DataFrame.shape: number of DataFrame rows and columns (including NA
- elements)
- DataFrame.isna: boolean same-sized DataFrame showing places of NA
- elements
+ Series.count: Number of non-NA elements in a Series.
+ DataFrame.shape: Number of DataFrame rows and columns (including NA
+ elements).
+ DataFrame.isna: Boolean same-sized DataFrame showing places of NA
+ elements.
 
  Examples
  --------