Fix: Use only one blank line to separate sections or paragraphs

pandas/core/algorithms.py

@@ -343,7 +343,6 @@ def unique(values):
     --------
     pandas.Index.unique
     pandas.Series.unique
-
     """
 
     values = _ensure_arraylike(values)

pandas/core/config.py

@@ -385,7 +385,6 @@ class option_context(object):
 
     >>> with option_context('display.max_rows', 10, 'display.max_columns', 5):
     ...     ...
-
     """
 
     def __init__(self, *args):

pandas/core/dtypes/common.py

@@ -2067,7 +2067,6 @@ def pandas_dtype(dtype):
     Raises
     ------
     TypeError if not a dtype
-
     """
     # short-circuit
     if isinstance(dtype, np.ndarray):

pandas/core/frame.py

@@ -877,7 +877,6 @@ def iterrows(self):
         --------
         itertuples : Iterate over DataFrame rows as namedtuples of the values.
         iteritems : Iterate over (column name, Series) pairs.
-
         """
         columns = self.columns
         klass = self._constructor_sliced
@@ -1722,7 +1721,6 @@ def from_csv(cls, path, header=0, sep=',', index_col=0, parse_dates=True,
         Returns
         -------
         y : DataFrame
-
         """
 
         warnings.warn("from_csv is deprecated. Please use read_csv(...) "
@@ -1963,7 +1961,6 @@ def to_feather(self, fname):
         ----------
         fname : str
             string file path
-
         """
         from pandas.io.feather_format import to_feather
         to_feather(self, fname)
@@ -3578,7 +3575,6 @@ def lookup(self, row_labels, col_labels):
         --------
         values : ndarray
             The found values
-
         """
         n = len(row_labels)
         if n != len(col_labels):
@@ -4881,7 +4877,6 @@ def swaplevel(self, i=-2, j=-1, axis=0):
 
            The indexes ``i`` and ``j`` are now optional, and default to
            the two innermost levels of the index.
-
         """
         result = self.copy()
 
@@ -7115,7 +7110,6 @@ def count(self, axis=0, level=None, numeric_only=False):
         John      2
         Lewis     1
         Myla      1
-
         """
         axis = self._get_axis_number(axis)
         if level is not None:

pandas/core/groupby/generic.py

@@ -1294,7 +1294,6 @@ class DataFrameGroupBy(NDFrameGroupBy):
     pandas.DataFrame.groupby.apply
     pandas.DataFrame.groupby.transform
     pandas.DataFrame.aggregate
-
     """)
 
     @Appender(_agg_doc)

pandas/core/groupby/groupby.py

@@ -42,7 +42,6 @@ class providing the base-class of operations.
 from pandas.core.sorting import get_group_index_sorter
 
 _doc_template = """
-
         See Also
         --------
         pandas.Series.%(name)s
@@ -1049,7 +1048,8 @@ def any(self, skipna=True):
     @Substitution(name='groupby')
     @Appender(_doc_template)
     def all(self, skipna=True):
-        """Returns True if all values in the group are truthful, else False
+        """
+        Returns True if all values in the group are truthful, else False
 
         Parameters
         ----------

pandas/core/indexes/base.py

@@ -1224,7 +1224,6 @@ def to_frame(self, index=True, name=None):
             or the original Index is returned.
 
             .. versionadded:: 0.19.0
-
         """
 
     @Appender(_index_shared_docs['astype'])
@@ -2539,7 +2538,6 @@ def asof_locs(self, where, mask):
         """
         where : array of timestamps
         mask : array of booleans where data is not NA
-
         """
         locs = self.values[mask].searchsorted(where.values, side='right')
 
@@ -2785,7 +2783,6 @@ def union(self, other):
         >>> idx2 = pd.Index([3, 4, 5, 6])
         >>> idx1.union(idx2)
         Int64Index([1, 2, 3, 4, 5, 6], dtype='int64')
-
         """
         self._assert_can_do_setop(other)
         other = ensure_index(other)
@@ -2884,7 +2881,6 @@ def intersection(self, other):
         >>> idx2 = pd.Index([3, 4, 5, 6])
         >>> idx1.intersection(idx2)
         Int64Index([3, 4], dtype='int64')
-
         """
         self._assert_can_do_setop(other)
         other = ensure_index(other)
@@ -2956,7 +2952,6 @@ def difference(self, other, sort=True):
         Int64Index([1, 2], dtype='int64')
         >>> idx1.difference(idx2, sort=False)
         Int64Index([2, 1], dtype='int64')
-
         """
         self._assert_can_do_setop(other)
 
@@ -3342,7 +3337,6 @@ def droplevel(self, level=0):
 
         Notice that the return value is an array of locations in ``index``
         and ``x`` is marked by -1, as it is not in ``index``.
-
         """
 
     @Appender(_index_shared_docs['get_indexer'] % _index_doc_kwargs)
@@ -4374,7 +4368,6 @@ def get_slice_bound(self, label, side, kind):
         label : object
         side : {'left', 'right'}
         kind : {'ix', 'loc', 'getitem'}
-
         """
         assert kind in ['ix', 'loc', 'getitem', None]
 

pandas/core/indexes/category.py

@@ -42,7 +42,6 @@
     typ='method', overwrite=True)
 class CategoricalIndex(Index, accessor.PandasDelegate):
     """
-
     Immutable Index implementing an ordered, sliceable set. CategoricalIndex
     represents a sparsely populated Index with an underlying Categorical.
 

pandas/core/indexes/datetimes.py

@@ -167,7 +167,6 @@ class DatetimeIndex(DatetimeArray, DatelikeOps, TimelikeOps,
     TimedeltaIndex : Index of timedelta64 data.
     PeriodIndex : Index of Period data.
     pandas.to_datetime : Convert argument to datetime.
-
     """
     _typ = 'datetimeindex'
     _join_precedence = 10
@@ -546,7 +545,6 @@ def to_series(self, keep_tz=None, index=None, name=None):
     def snap(self, freq='S'):
         """
         Snap time stamps to nearest occurring frequency
-
         """
         # Superdumb, punting on any optimizing
         freq = to_offset(freq)

pandas/core/indexes/multi.py

@@ -356,7 +356,6 @@ def set_levels(self, levels, level=None, inplace=False,
         -------
         new index (of same type and class...etc)
 
-
         Examples
         --------
         >>> idx = pd.MultiIndex.from_tuples([(1, u'one'), (1, u'two'),
@@ -1519,7 +1518,6 @@ def remove_unused_levels(self):
         MultiIndex(levels=[[0, 1], ['a', 'b']],
                    labels=[[0, 0, 1, 1], [0, 1, 0, 1]])
 
-
         >>> i[2:]
         MultiIndex(levels=[[0, 1], ['a', 'b']],
                    labels=[[1, 1], [0, 1]])
@@ -1530,7 +1528,6 @@ def remove_unused_levels(self):
         >>> i[2:].remove_unused_levels()
         MultiIndex(levels=[[1], ['a', 'b']],
                    labels=[[0, 0], [0, 1]])
-
         """
 
         new_levels = []
@@ -1912,7 +1909,6 @@ def sortlevel(self, level=0, ascending=True, sort_remaining=True):
             Resulting index
         indexer : np.ndarray
             Indices of output values in original index
-
         """
         from pandas.core.sorting import indexer_from_factorized
 

pandas/core/panel.py

@@ -806,7 +806,6 @@ def major_xs(self, key):
         MultiIndex Slicers is a generic way to get/set values on any level or
         levels and is a superset of major_xs functionality, see
         :ref:`MultiIndex Slicers <advanced.mi_slicers>`
-
         """
         return self.xs(key, axis=self._AXIS_LEN - 2)
 
@@ -831,7 +830,6 @@ def minor_xs(self, key):
         MultiIndex Slicers is a generic way to get/set values on any level or
         levels and is a superset of minor_xs functionality, see
         :ref:`MultiIndex Slicers <advanced.mi_slicers>`
-
         """
         return self.xs(key, axis=self._AXIS_LEN - 1)
 
@@ -856,7 +854,6 @@ def xs(self, key, axis=1):
         MultiIndex Slicers is a generic way to get/set values on any level or
         levels and is a superset of xs functionality, see
         :ref:`MultiIndex Slicers <advanced.mi_slicers>`
-
         """
         axis = self._get_axis_number(axis)
         if axis == 0:

pandas/core/resample.py

@@ -110,7 +110,6 @@ def __iter__(self):
         See Also
         --------
         GroupBy.__iter__
-
         """
         self._set_binner()
         return super(Resampler, self).__iter__()
@@ -204,7 +203,6 @@ def pipe(self, func, *args, **kwargs):
         return super(Resampler, self).pipe(func, *args, **kwargs)
 
     _agg_doc = dedent("""
-
     Examples
     --------
     >>> s = pd.Series([1,2,3,4,5],
@@ -244,7 +242,6 @@ def pipe(self, func, *args, **kwargs):
     pandas.DataFrame.groupby.aggregate
     pandas.DataFrame.resample.transform
     pandas.DataFrame.aggregate
-
     """)
 
     @Appender(_agg_doc)

pandas/core/reshape/merge.py

@@ -203,7 +203,6 @@ def merge_ordered(left, right, on=None,
     --------
     merge
     merge_asof
-
     """
     def _merger(x, y):
         # perform the ordered merge operation
@@ -312,7 +311,6 @@ def merge_asof(left, right, on=None,
 
         .. versionadded:: 0.20.0
 
-
     Returns
     -------
     merged : DataFrame
@@ -451,7 +449,6 @@ def merge_asof(left, right, on=None,
     --------
     merge
     merge_ordered
-
     """
     op = _AsOfMerge(left, right,
                     on=on, left_on=left_on, right_on=right_on,

pandas/core/reshape/pivot.py

@@ -433,7 +433,6 @@ def crosstab(index, columns, values=None, rownames=None, colnames=None,
 
         .. versionadded:: 0.18.1
 
-
     Notes
     -----
     Any Series passed will have their name attributes used unless row or column

pandas/core/util/hashing.py

@@ -69,7 +69,6 @@ def hash_pandas_object(obj, index=True, encoding='utf8', hash_key=None,
     Returns
     -------
     Series of uint64, same length as the object
-
     """
     from pandas import Series
     if hash_key is None:
@@ -248,7 +247,6 @@ def hash_array(vals, encoding='utf8', hash_key=None, categorize=True):
     Returns
     -------
     1d uint64 numpy array of hash values, same length as the vals
-
     """
 
     if not hasattr(vals, 'dtype'):

pandas/core/window.py

@@ -1613,7 +1613,6 @@ def _validate_freq(self):
     8 -0.289082  2.454418  1.416871
     9  0.212668  0.403198 -0.093924
 
-
     >>> df.rolling(3).agg({'A':'sum', 'B':'min'})
               A         B
     0       NaN       NaN
@@ -1631,7 +1630,6 @@ def _validate_freq(self):
     --------
     pandas.Series.rolling
     pandas.DataFrame.rolling
-
     """)
 
     @Appender(_agg_doc)
@@ -1908,7 +1906,6 @@ def _get_window(self, other=None):
     pandas.DataFrame.expanding.aggregate
     pandas.DataFrame.rolling.aggregate
     pandas.DataFrame.aggregate
-
     """)
 
     @Appender(_agg_doc)
@@ -2209,7 +2206,6 @@ def _constructor(self):
     See Also
     --------
     pandas.DataFrame.rolling.aggregate
-
     """)
 
     @Appender(_agg_doc)
@@ -2233,7 +2229,6 @@ def _apply(self, func, **kwargs):
         Returns
         -------
         y : same type as input argument
-
         """
         blocks, obj, index = self._create_blocks()
         results = []

pandas/errors/__init__.py

@@ -26,7 +26,6 @@ class UnsortedIndexError(KeyError):
     and the index has not been lexsorted. Subclass of `KeyError`.
 
     .. versionadded:: 0.20.0
-
     """
 
 

pandas/io/formats/style.py

@@ -637,7 +637,6 @@ def applymap(self, func, subset=None, **kwargs):
         See Also
         --------
         Styler.where
-
         """
         self._todo.append((lambda instance: getattr(instance, '_applymap'),
                            (func, subset), kwargs))
@@ -672,7 +671,6 @@ def where(self, cond, value, other=None, subset=None, **kwargs):
         See Also
         --------
         Styler.applymap
-
         """
 
         if other is None:
@@ -1104,7 +1102,6 @@ def bar(self, subset=None, axis=0, color='#d65f5f', width=100,
 
             .. versionadded:: 0.24.0
 
-
         Returns
         -------
         self : Styler

pandas/io/json/normalize.py

@@ -129,7 +129,6 @@ def json_normalize(data, record_path=None, meta=None,
 
         .. versionadded:: 0.20.0
 
-
     Returns
     -------
     frame : DataFrame

pandas/io/packers.py

@@ -177,7 +177,6 @@ def read_msgpack(path_or_buf, encoding='utf-8', iterator=False, **kwargs):
     Returns
     -------
     obj : same type as object stored in file
-
     """
     path_or_buf, _, _, should_close = get_filepath_or_buffer(path_or_buf)
     if iterator: