CLN: D208 Docstring is over-indented (#31890)

Author: simonjayhawkins

pandas/conftest.py

@@ -106,8 +106,8 @@ def axis(request):
 @pytest.fixture(params=[0, "index"], ids=lambda x: f"axis {repr(x)}")
 def axis_series(request):
     """
-     Fixture for returning the axis numbers of a Series.
-     """
+    Fixture for returning the axis numbers of a Series.
+    """
     return request.param
 
 

pandas/core/computation/pytables.py

@@ -601,8 +601,7 @@ def __init__(self, value, converted, kind: str):
         self.kind = kind
 
     def tostring(self, encoding) -> str:
-        """ quote the string if not encoded
-            else encode and return """
+        """ quote the string if not encoded else encode and return """
         if self.kind == "string":
             if encoding is not None:
                 return str(self.converted)

pandas/io/excel/_xlrd.py

@@ -57,8 +57,9 @@ def get_sheet_data(self, sheet, convert_float):
         epoch1904 = self.book.datemode
 
         def _parse_cell(cell_contents, cell_typ):
-            """converts the contents of the cell into a pandas
-               appropriate object"""
+            """
+            converts the contents of the cell into a pandas appropriate object
+            """
 
             if cell_typ == XL_CELL_DATE:
 

pandas/io/formats/format.py

@@ -979,7 +979,7 @@ def to_html(
         border : int
             A ``border=border`` attribute is included in the opening
             ``<table>`` tag. Default ``pd.options.display.html.border``.
-         """
+        """
         from pandas.io.formats.html import HTMLFormatter, NotebookFormatter
 
         Klass = NotebookFormatter if notebook else HTMLFormatter

pandas/io/parsers.py

@@ -1456,8 +1456,10 @@ def _should_parse_dates(self, i):
     def _extract_multi_indexer_columns(
         self, header, index_names, col_names, passed_names=False
     ):
-        """ extract and return the names, index_names, col_names
-            header is a list-of-lists returned from the parsers """
+        """
+        extract and return the names, index_names, col_names
+        header is a list-of-lists returned from the parsers
+        """
         if len(header) < 2:
             return header[0], index_names, col_names, passed_names
 

pandas/io/pytables.py

@@ -569,9 +569,10 @@ def __getattr__(self, name: str):
         )
 
     def __contains__(self, key: str) -> bool:
-        """ check for existence of this key
-              can match the exact pathname or the pathnm w/o the leading '/'
-              """
+        """
+        check for existence of this key
+        can match the exact pathname or the pathnm w/o the leading '/'
+        """
         node = self.get_node(key)
         if node is not None:
             name = node._v_pathname
@@ -1831,18 +1832,19 @@ def get_result(self, coordinates: bool = False):
 
 
 class IndexCol:
-    """ an index column description class
+    """
+    an index column description class
 
-        Parameters
-        ----------
+    Parameters
+    ----------
 
-        axis   : axis which I reference
-        values : the ndarray like converted values
-        kind   : a string description of this type
-        typ    : the pytables type
-        pos    : the position in the pytables
+    axis   : axis which I reference
+    values : the ndarray like converted values
+    kind   : a string description of this type
+    typ    : the pytables type
+    pos    : the position in the pytables
 
-        """
+    """
 
     is_an_indexable = True
     is_data_indexable = True
@@ -1999,9 +2001,11 @@ def __iter__(self):
         return iter(self.values)
 
     def maybe_set_size(self, min_itemsize=None):
-        """ maybe set a string col itemsize:
-               min_itemsize can be an integer or a dict with this columns name
-               with an integer size """
+        """
+        maybe set a string col itemsize:
+            min_itemsize can be an integer or a dict with this columns name
+            with an integer size
+        """
         if _ensure_decoded(self.kind) == "string":
 
             if isinstance(min_itemsize, dict):
@@ -2051,8 +2055,10 @@ def validate_attr(self, append: bool):
                 )
 
     def update_info(self, info):
-        """ set/update the info for this indexable with the key/value
-            if there is a conflict raise/warn as needed """
+        """
+        set/update the info for this indexable with the key/value
+        if there is a conflict raise/warn as needed
+        """
 
         for key in self._info_fields:
 
@@ -2140,17 +2146,18 @@ def set_attr(self):
 
 
 class DataCol(IndexCol):
-    """ a data holding column, by definition this is not indexable
+    """
+    a data holding column, by definition this is not indexable
 
-        Parameters
-        ----------
+    Parameters
+    ----------
 
-        data   : the actual data
-        cname  : the column name in the table to hold the data (typically
-                 values)
-        meta   : a string description of the metadata
-        metadata : the actual metadata
-        """
+    data   : the actual data
+    cname  : the column name in the table to hold the data (typically
+                values)
+    meta   : a string description of the metadata
+    metadata : the actual metadata
+    """
 
     is_an_indexable = False
     is_data_indexable = False
@@ -2460,16 +2467,17 @@ class GenericDataIndexableCol(DataIndexableCol):
 
 
 class Fixed:
-    """ represent an object in my store
-        facilitate read/write of various types of objects
-        this is an abstract base class
+    """
+    represent an object in my store
+    facilitate read/write of various types of objects
+    this is an abstract base class
 
-        Parameters
-        ----------
-        parent : HDFStore
-        group : Node
-            The group node where the table resides.
-        """
+    Parameters
+    ----------
+    parent : HDFStore
+    group : Node
+        The group node where the table resides.
+    """
 
     pandas_kind: str
     format_type: str = "fixed"  # GH#30962 needed by dask
@@ -2596,8 +2604,10 @@ def validate_version(self, where=None):
         return True
 
     def infer_axes(self):
-        """ infer the axes of my storer
-              return a boolean indicating if we have a valid storer or not """
+        """
+        infer the axes of my storer
+        return a boolean indicating if we have a valid storer or not
+        """
 
         s = self.storable
         if s is None:
@@ -3105,29 +3115,29 @@ class FrameFixed(BlockManagerFixed):
 
 
 class Table(Fixed):
-    """ represent a table:
-          facilitate read/write of various types of tables
-
-        Attrs in Table Node
-        -------------------
-        These are attributes that are store in the main table node, they are
-        necessary to recreate these tables when read back in.
-
-        index_axes    : a list of tuples of the (original indexing axis and
-            index column)
-        non_index_axes: a list of tuples of the (original index axis and
-            columns on a non-indexing axis)
-        values_axes   : a list of the columns which comprise the data of this
-            table
-        data_columns  : a list of the columns that we are allowing indexing
-            (these become single columns in values_axes), or True to force all
-            columns
-        nan_rep       : the string to use for nan representations for string
-            objects
-        levels        : the names of levels
-        metadata      : the names of the metadata columns
-
-        """
+    """
+    represent a table:
+        facilitate read/write of various types of tables
+
+    Attrs in Table Node
+    -------------------
+    These are attributes that are store in the main table node, they are
+    necessary to recreate these tables when read back in.
+
+    index_axes    : a list of tuples of the (original indexing axis and
+        index column)
+    non_index_axes: a list of tuples of the (original index axis and
+        columns on a non-indexing axis)
+    values_axes   : a list of the columns which comprise the data of this
+        table
+    data_columns  : a list of the columns that we are allowing indexing
+        (these become single columns in values_axes), or True to force all
+        columns
+    nan_rep       : the string to use for nan representations for string
+        objects
+    levels        : the names of levels
+    metadata      : the names of the metadata columns
+    """
 
     pandas_kind = "wide_table"
     format_type: str = "table"  # GH#30962 needed by dask
@@ -4080,10 +4090,11 @@ def read_column(
 
 
 class WORMTable(Table):
-    """ a write-once read-many table: this format DOES NOT ALLOW appending to a
-         table. writing is a one-time operation the data are stored in a format
-         that allows for searching the data on disk
-         """
+    """
+    a write-once read-many table: this format DOES NOT ALLOW appending to a
+    table. writing is a one-time operation the data are stored in a format
+    that allows for searching the data on disk
+    """
 
     table_type = "worm"
 
@@ -4094,14 +4105,16 @@ def read(
         start: Optional[int] = None,
         stop: Optional[int] = None,
     ):
-        """ read the indices and the indexing array, calculate offset rows and
-        return """
+        """
+        read the indices and the indexing array, calculate offset rows and return
+        """
         raise NotImplementedError("WORMTable needs to implement read")
 
     def write(self, **kwargs):
-        """ write in a format that we can search later on (but cannot append
-               to): write out the indices and the values using _write_array
-               (e.g. a CArray) create an indexing table so that we can search
+        """
+        write in a format that we can search later on (but cannot append
+        to): write out the indices and the values using _write_array
+        (e.g. a CArray) create an indexing table so that we can search
         """
         raise NotImplementedError("WORMTable needs to implement write")
 
@@ -4170,8 +4183,9 @@ def write(
         table.write_data(chunksize, dropna=dropna)
 
     def write_data(self, chunksize: Optional[int], dropna: bool = False):
-        """ we form the data into a 2-d including indexes,values,mask
-            write chunk-by-chunk """
+        """
+        we form the data into a 2-d including indexes,values,mask write chunk-by-chunk
+        """
 
         names = self.dtype.names
         nrows = self.nrows_expected

pandas/io/sas/sas7bdat.py

@@ -120,8 +120,10 @@ def column_data_offsets(self):
         return np.asarray(self._column_data_offsets, dtype=np.int64)
 
     def column_types(self):
-        """Returns a numpy character array of the column types:
-           s (string) or d (double)"""
+        """
+        Returns a numpy character array of the column types:
+           s (string) or d (double)
+        """
         return np.asarray(self._column_types, dtype=np.dtype("S1"))
 
     def close(self):

pandas/plotting/_matplotlib/core.py

@@ -509,10 +509,11 @@ def _adorn_subplots(self):
                 self.axes[0].set_title(self.title)
 
     def _apply_axis_properties(self, axis, rot=None, fontsize=None):
-        """ Tick creation within matplotlib is reasonably expensive and is
-            internally deferred until accessed as Ticks are created/destroyed
-            multiple times per draw. It's therefore beneficial for us to avoid
-            accessing unless we will act on the Tick.
+        """
+        Tick creation within matplotlib is reasonably expensive and is
+        internally deferred until accessed as Ticks are created/destroyed
+        multiple times per draw. It's therefore beneficial for us to avoid
+        accessing unless we will act on the Tick.
         """
 
         if rot is not None or fontsize is not None:

pandas/tests/extension/test_datetime.py

@@ -44,9 +44,9 @@ def data_missing_for_sorting(dtype):
 @pytest.fixture
 def data_for_grouping(dtype):
     """
-        Expected to be like [B, B, NA, NA, A, A, B, C]
+    Expected to be like [B, B, NA, NA, A, A, B, C]
 
-        Where A < B < C and NA is missing
+    Where A < B < C and NA is missing
     """
     a = pd.Timestamp("2000-01-01")
     b = pd.Timestamp("2000-01-02")

pandas/tests/generic/test_generic.py

@@ -23,9 +23,11 @@ def _axes(self):
         return self._typ._AXIS_ORDERS
 
     def _construct(self, shape, value=None, dtype=None, **kwargs):
-        """ construct an object for the given shape
-            if value is specified use that if its a scalar
-            if value is an array, repeat it as needed """
+        """
+        construct an object for the given shape
+        if value is specified use that if its a scalar
+        if value is an array, repeat it as needed
+        """
 
         if isinstance(shape, int):
             shape = tuple([shape] * self._ndim)

pandas/tests/groupby/test_groupby.py

@@ -1496,7 +1496,7 @@ def test_groupby_reindex_inside_function():
 
     def agg_before(hour, func, fix=False):
         """
-            Run an aggregate func on the subset of data.
+        Run an aggregate func on the subset of data.
         """
 
         def _func(data):

pandas/tests/scalar/timestamp/test_unary_ops.py

@@ -225,9 +225,8 @@ def test_round_dst_border_nonexistent(self, method, ts_str, freq):
         ],
     )
     def test_round_int64(self, timestamp, freq):
-        """check that all rounding modes are accurate to int64 precision
-           see GH#22591
-        """
+        # check that all rounding modes are accurate to int64 precision
+        # see GH#22591
         dt = Timestamp(timestamp)
         unit = to_offset(freq).nanos