Fix flake8 issues on v22, v23 and v24rst (#24217)

Author: thoo

doc/source/whatsnew/v0.22.0.rst

@@ -137,8 +137,8 @@ sum and ``1`` for product.
 .. code-block:: ipython
 
  In [11]: s = pd.Series([1, 1, np.nan, np.nan],
- ...:  index=pd.date_range('2017', periods=4))
- ...:  s
+ ....: index=pd.date_range('2017', periods=4))
+ ....: s
  Out[11]:
  2017-01-01 1.0
  2017-01-02 1.0

doc/source/whatsnew/v0.23.0.rst

@@ -53,10 +53,10 @@ A ``DataFrame`` can now be written to and subsequently read back via JSON while
 .. ipython:: python
 
  df = pd.DataFrame({'foo': [1, 2, 3, 4],
- 'bar': ['a', 'b', 'c', 'd'],
- 'baz': pd.date_range('2018-01-01', freq='d', periods=4),
- 'qux': pd.Categorical(['a', 'b', 'c', 'c'])
- }, index=pd.Index(range(4), name='idx'))
+  'bar': ['a', 'b', 'c', 'd'],
+  'baz': pd.date_range('2018-01-01', freq='d', periods=4),
+  'qux': pd.Categorical(['a', 'b', 'c', 'c'])},
+   index=pd.Index(range(4), name='idx'))
  df
  df.dtypes
  df.to_json('test.json', orient='table')
@@ -97,7 +97,7 @@ The :func:`DataFrame.assign` now accepts dependent keyword arguments for python
 
  df = pd.DataFrame({'A': [1, 2, 3]})
  df
- df.assign(B=df.A, C=lambda x:x['A']+ x['B'])
+ df.assign(B=df.A, C=lambda x: x['A'] + x['B'])
 
 .. warning::
 
@@ -122,7 +122,7 @@ The :func:`DataFrame.assign` now accepts dependent keyword arguments for python
 
  .. ipython:: python
 
- df.assign(A=df.A+1, C= lambda df: df.A* -1)
+ df.assign(A=df.A + 1, C=lambda df: df.A * -1)
 
 
 
@@ -284,7 +284,7 @@ For pivotting operations, this behavior is *already* controlled by the ``dropna`
  categories=["a", "b", "z"], ordered=True)
  cat2 = pd.Categorical(["c", "d", "c", "d"],
  categories=["c", "d", "y"], ordered=True)
- df = DataFrame({"A": cat1, "B": cat2, "values": [1, 2, 3, 4]})
+ df = pd.DataFrame({"A": cat1, "B": cat2, "values": [1, 2, 3, 4]})
  df
 
 .. ipython:: python
@@ -336,7 +336,8 @@ outside the existing valid values while preserving those inside. (:issue:`16284
 
 .. ipython:: python
 
- ser = pd.Series([np.nan, np.nan, 5, np.nan, np.nan, np.nan, 13, np.nan, np.nan])
+ ser = pd.Series([np.nan, np.nan, 5, np.nan, np.nan,
+ np.nan, 13, np.nan, np.nan])
  ser
 
 Fill one consecutive inside value in both directions
@@ -600,15 +601,16 @@ Previous Behavior (and current behavior if on Python < 3.6):
 
 .. code-block:: ipython
 
- pd.Series({'Income': 2000,
- 'Expenses': -1500,
- 'Taxes': -200,
- 'Net result': 300})
- Expenses -1500
- Income 2000
- Net result 300
- Taxes -200
- dtype: int64
+ In [16]: pd.Series({'Income': 2000,
+ ....: 'Expenses': -1500,
+ ....: 'Taxes': -200,
+ ....: 'Net result': 300})
+ Out[16]:
+ Expenses -1500
+ Income 2000
+ Net result 300
+ Taxes -200
+ dtype: int64
 
 Note the Series above is ordered alphabetically by the index values.
 
@@ -696,7 +698,8 @@ where a list-like (e.g. ``tuple`` or ``list`` is returned) (:issue:`16353`, :iss
 
 .. ipython:: python
 
- df = pd.DataFrame(np.tile(np.arange(3), 6).reshape(6, -1) + 1, columns=['A', 'B', 'C'])
+ df = pd.DataFrame(np.tile(np.arange(3), 6).reshape(6, -1) + 1,
+ columns=['A', 'B', 'C'])
  df
 
 Previous Behavior: if the returned shape happened to match the length of original columns, this would return a ``DataFrame``.
@@ -750,7 +753,7 @@ Returning a ``Series`` allows one to control the exact return structure and colu
 
 .. ipython:: python
 
- df.apply(lambda x: Series([1, 2, 3], index=['D', 'E', 'F']), axis=1)
+ df.apply(lambda x: pd.Series([1, 2, 3], index=['D', 'E', 'F']), axis=1)
 
 .. _whatsnew_0230.api_breaking.concat:
 
@@ -825,10 +828,12 @@ Current Behavior:
 .. ipython:: python
 
  index = pd.Int64Index([-1, 0, 1])
- # division by zero gives -infinity where negative, +infinity where positive, and NaN for 0 / 0
+ # division by zero gives -infinity where negative,
+ # +infinity where positive, and NaN for 0 / 0
  index / 0
 
- # The result of division by zero should not depend on whether the zero is int or float
+ # The result of division by zero should not depend on
+ # whether the zero is int or float
  index / 0.0
 
  index = pd.UInt64Index([0, 1])
@@ -853,7 +858,7 @@ Previous Behavior:
 
  In [1]: s = pd.Series(['number 10', '12 eggs'])
 
- In [2]: extracted = s.str.extract('.*(\d\d).*')
+ In [2]: extracted = s.str.extract(r'.*(\d\d).*')
 
  In [3]: extracted
  Out [3]:
@@ -870,7 +875,7 @@ New Behavior:
 .. ipython:: python
 
  s = pd.Series(['number 10', '12 eggs'])
- extracted = s.str.extract('.*(\d\d).*')
+ extracted = s.str.extract(r'.*(\d\d).*')
  extracted
  type(extracted)
 
@@ -879,7 +884,7 @@ To restore previous behavior, simply set ``expand`` to ``False``:
 .. ipython:: python
 
  s = pd.Series(['number 10', '12 eggs'])
- extracted = s.str.extract('.*(\d\d).*', expand=False)
+ extracted = s.str.extract(r'.*(\d\d).*', expand=False)
  extracted
  type(extracted)
 

doc/source/whatsnew/v0.24.0.rst

@@ -252,7 +252,7 @@ convenient way to apply users' predefined styling functions, and can help reduce
 
 .. ipython:: python
 
- df = pandas.DataFrame({'N': [1250, 1500, 1750], 'X': [0.25, 0.35, 0.50]})
+ df = pd.DataFrame({'N': [1250, 1500, 1750], 'X': [0.25, 0.35, 0.50]})
 
  def format_and_align(styler):
  return (styler.format({'N': '{:,}', 'X': '{:.1%}'})
@@ -282,8 +282,7 @@ See the :ref:`Merge, join, and concatenate
 
 
  left = pd.DataFrame({'A': ['A0', 'A1', 'A2'],
- 'B': ['B0', 'B1', 'B2']},
- index=index_left)
+ 'B': ['B0', 'B1', 'B2']}, index=index_left)
 
 
  index_right = pd.MultiIndex.from_tuples([('K0', 'Y0'), ('K1', 'Y1'),
@@ -292,11 +291,9 @@ See the :ref:`Merge, join, and concatenate
 
 
  right = pd.DataFrame({'C': ['C0', 'C1', 'C2', 'C3'],
- 'D': ['D0', 'D1', 'D2', 'D3']},
- index=index_right)
+ 'D': ['D0', 'D1', 'D2', 'D3']}, index=index_right)
 
-
- left.join(right)
+ left.join(right)
 
 For earlier versions this can be done using the following.
 
@@ -441,26 +438,26 @@ Previous Behavior on Windows:
 
 .. code-block:: ipython
 
- In [1]: data = pd.DataFrame({
- ...: "string_with_lf": ["a\nbc"],
- ...: "string_with_crlf": ["a\r\nbc"]
- ...: })
+ In [1]: data = pd.DataFrame({"string_with_lf": ["a\nbc"],
+ ...: "string_with_crlf": ["a\r\nbc"]})
 
- In [2]: # When passing file PATH to to_csv, line_terminator does not work, and csv is saved with '\r\n'.
- ...: # Also, this converts all '\n's in the data to '\r\n'.
- ...: data.to_csv("test.csv", index=False, line_terminator='\n')
+ In [2]: # When passing file PATH to to_csv,
+ ...: # line_terminator does not work, and csv is saved with '\r\n'.
+ ...: # Also, this converts all '\n's in the data to '\r\n'.
+ ...: data.to_csv("test.csv", index=False, line_terminator='\n')
 
  In [3]: with open("test.csv", mode='rb') as f:
- ...: print(f.read())
- b'string_with_lf,string_with_crlf\r\n"a\r\nbc","a\r\r\nbc"\r\n'
+  ...: print(f.read())
+ Out[3]: b'string_with_lf,string_with_crlf\r\n"a\r\nbc","a\r\r\nbc"\r\n'
 
- In [4]: # When passing file OBJECT with newline option to to_csv, line_terminator works.
- ...: with open("test2.csv", mode='w', newline='\n') as f:
- ...: data.to_csv(f, index=False, line_terminator='\n')
+ In [4]: # When passing file OBJECT with newline option to
+ ...: # to_csv, line_terminator works.
+ ...: with open("test2.csv", mode='w', newline='\n') as f:
+ ...: data.to_csv(f, index=False, line_terminator='\n')
 
  In [5]: with open("test2.csv", mode='rb') as f:
- ...: print(f.read())
- b'string_with_lf,string_with_crlf\n"a\nbc","a\r\nbc"\n'
+  ...: print(f.read())
+ Out[5]: b'string_with_lf,string_with_crlf\n"a\nbc","a\r\nbc"\n'
 
 
 New Behavior on Windows:
@@ -471,16 +468,14 @@ New Behavior on Windows:
 
  .. code-block:: ipython
 
- In [1]: data = pd.DataFrame({
- ...: "string_with_lf": ["a\nbc"],
- ...: "string_with_crlf": ["a\r\nbc"]
- ...: })
+ In [1]: data = pd.DataFrame({"string_with_lf": ["a\nbc"],
+ ...: "string_with_crlf": ["a\r\nbc"]})
 
  In [2]: data.to_csv("test.csv", index=False, line_terminator='\n')
 
  In [3]: with open("test.csv", mode='rb') as f:
- ...: print(f.read())
- b'string_with_lf,string_with_crlf\n"a\nbc","a\r\nbc"\n'
+  ...: print(f.read())
+ Out[3]: b'string_with_lf,string_with_crlf\n"a\nbc","a\r\nbc"\n'
 
 
 - On Windows, the value of ``os.linesep`` is ``'\r\n'``,
@@ -489,34 +484,30 @@ New Behavior on Windows:
 
  .. code-block:: ipython
 
- In [1]: data = pd.DataFrame({
- ...: "string_with_lf": ["a\nbc"],
- ...: "string_with_crlf": ["a\r\nbc"]
- ...: })
+ In [1]: data = pd.DataFrame({"string_with_lf": ["a\nbc"],
+ ...: "string_with_crlf": ["a\r\nbc"]})
 
  In [2]: data.to_csv("test.csv", index=False)
 
  In [3]: with open("test.csv", mode='rb') as f:
- ...: print(f.read())
- b'string_with_lf,string_with_crlf\r\n"a\nbc","a\r\nbc"\r\n'
+  ...: print(f.read())
+ Out[3]: b'string_with_lf,string_with_crlf\r\n"a\nbc","a\r\nbc"\r\n'
 
 
 - For files objects, specifying ``newline`` is not sufficient to set the line terminator.
  You must pass in the ``line_terminator`` explicitly, even in this case.
 
  .. code-block:: ipython
 
- In [1]: data = pd.DataFrame({
- ...: "string_with_lf": ["a\nbc"],
- ...: "string_with_crlf": ["a\r\nbc"]
- ...: })
+ In [1]: data = pd.DataFrame({"string_with_lf": ["a\nbc"],
+ ...: "string_with_crlf": ["a\r\nbc"]})
 
  In [2]: with open("test2.csv", mode='w', newline='\n') as f:
- ...: data.to_csv(f, index=False)
+  ...: data.to_csv(f, index=False)
 
  In [3]: with open("test2.csv", mode='rb') as f:
- ...: print(f.read())
- b'string_with_lf,string_with_crlf\r\n"a\nbc","a\r\nbc"\r\n'
+  ...: print(f.read())
+ Out[3]: b'string_with_lf,string_with_crlf\r\n"a\nbc","a\r\nbc"\r\n'
 
 .. _whatsnew_0240.api.timezone_offset_parsing:
 
@@ -563,7 +554,8 @@ Parsing datetime strings with different UTC offsets will now create an Index of
 
 .. ipython:: python
 
- idx = pd.to_datetime(["2015-11-18 15:30:00+05:30", "2015-11-18 16:30:00+06:30"])
+ idx = pd.to_datetime(["2015-11-18 15:30:00+05:30",
+ "2015-11-18 16:30:00+06:30"])
  idx
  idx[0]
  idx[1]
@@ -573,7 +565,8 @@ that the dates have been converted to UTC
 
 .. ipython:: python
 
- pd.to_datetime(["2015-11-18 15:30:00+05:30", "2015-11-18 16:30:00+06:30"], utc=True)
+ pd.to_datetime(["2015-11-18 15:30:00+05:30",
+ "2015-11-18 16:30:00+06:30"], utc=True)
 
 .. _whatsnew_0240.api_breaking.calendarday:
 
@@ -845,7 +838,7 @@ Previous Behavior:
  In [4]: df = pd.DataFrame(arr)
 
  In [5]: df == arr[[0], :]
- ...: # comparison previously broadcast where arithmetic would raise
+  ...: # comparison previously broadcast where arithmetic would raise
  Out[5]:
  0 1
  0 True True
@@ -856,8 +849,8 @@ Previous Behavior:
  ValueError: Unable to coerce to DataFrame, shape must be (3, 2): given (1, 2)
 
  In [7]: df == (1, 2)
- ...: # length matches number of columns;
- ...: # comparison previously raised where arithmetic would broadcast
+  ...: # length matches number of columns;
+  ...: # comparison previously raised where arithmetic would broadcast
  ...
  ValueError: Invalid broadcasting comparison [(1, 2)] with block values
  In [8]: df + (1, 2)
@@ -868,8 +861,8 @@ Previous Behavior:
  2 5 7
 
  In [9]: df == (1, 2, 3)
- ...: # length matches number of rows
- ...: # comparison previously broadcast where arithmetic would raise
+  ...:  # length matches number of rows
+  ...:  # comparison previously broadcast where arithmetic would raise
  Out[9]:
  0 1
  0 False True
@@ -1032,7 +1025,8 @@ Current Behavior:
 
 .. code-block:: ipython
 
- In [3]: df = pd.DataFrame({'a': [1, 2, 2, 2, 2], 'b': [3, 3, 4, 4, 4],
+ In [3]: df = pd.DataFrame({'a': [1, 2, 2, 2, 2],
+ ...: 'b': [3, 3, 4, 4, 4],
  ...: 'c': [1, 1, np.nan, 1, 1]})
  In [4]: pd.crosstab(df.a, df.b, normalize='columns')
 

setup.cfg

@@ -71,11 +71,8 @@ exclude =
  doc/source/whatsnew/v0.19.0.rst
  doc/source/whatsnew/v0.20.0.rst
  doc/source/whatsnew/v0.21.0.rst
- doc/source/whatsnew/v0.22.0.rst
- doc/source/whatsnew/v0.23.0.rst
  doc/source/whatsnew/v0.23.1.rst
  doc/source/whatsnew/v0.23.2.rst
- doc/source/whatsnew/v0.24.0.rst
  doc/source/basics.rst
  doc/source/contributing_docstring.rst
  doc/source/enhancingperf.rst