STYLE: flake8 upgraded to 3.3 on conda (pandas-dev#15412)

fixes for E305, 2 blank lines after a class definition

Author: jreback

pandas/compat/numpy/__init__.py

@@ -67,6 +67,7 @@ def np_array_datetime64_compat(arr, *args, **kwargs):
 
     return np.array(arr, *args, **kwargs)
 
+
 __all__ = ['np',
            '_np_version_under1p8',
            '_np_version_under1p9',

pandas/compat/numpy/function.py

@@ -55,6 +55,7 @@ def __call__(self, args, kwargs, fname=None,
             raise ValueError("invalid validation method "
                              "'{method}'".format(method=method))
 
+
 ARGMINMAX_DEFAULTS = dict(out=None)
 validate_argmin = CompatValidator(ARGMINMAX_DEFAULTS, fname='argmin',
                                   method='both', max_fname_arg_count=1)
@@ -97,6 +98,7 @@ def validate_argmax_with_skipna(skipna, args, kwargs):
     validate_argmax(args, kwargs)
     return skipna
 
+
 ARGSORT_DEFAULTS = OrderedDict()
 ARGSORT_DEFAULTS['axis'] = -1
 ARGSORT_DEFAULTS['kind'] = 'quicksort'
@@ -121,6 +123,7 @@ def validate_argsort_with_ascending(ascending, args, kwargs):
     validate_argsort(args, kwargs, max_fname_arg_count=1)
     return ascending
 
+
 CLIP_DEFAULTS = dict(out=None)
 validate_clip = CompatValidator(CLIP_DEFAULTS, fname='clip',
                                 method='both', max_fname_arg_count=3)
@@ -141,6 +144,7 @@ def validate_clip_with_axis(axis, args, kwargs):
     validate_clip(args, kwargs)
     return axis
 
+
 COMPRESS_DEFAULTS = OrderedDict()
 COMPRESS_DEFAULTS['axis'] = None
 COMPRESS_DEFAULTS['out'] = None
@@ -170,6 +174,7 @@ def validate_cum_func_with_skipna(skipna, args, kwargs, name):
     validate_cum_func(args, kwargs, fname=name)
     return skipna
 
+
 LOGICAL_FUNC_DEFAULTS = dict(out=None)
 validate_logical_func = CompatValidator(LOGICAL_FUNC_DEFAULTS, method='kwargs')
 
@@ -236,6 +241,7 @@ def validate_take_with_convert(convert, args, kwargs):
     validate_take(args, kwargs, max_fname_arg_count=3, method='both')
     return convert
 
+
 TRANSPOSE_DEFAULTS = dict(axes=None)
 validate_transpose = CompatValidator(TRANSPOSE_DEFAULTS, fname='transpose',
                                      method='both', max_fname_arg_count=0)
@@ -318,6 +324,7 @@ def validate_groupby_func(name, args, kwargs, allowed=None):
             "with groupby. Use .groupby(...)."
             "{func}() instead".format(func=name)))
 
+
 RESAMPLER_NUMPY_OPS = ('min', 'max', 'sum', 'prod',
                        'mean', 'std', 'var')
 

pandas/computation/expr.py

@@ -669,6 +669,7 @@ def visitor(x, y):
         operands = node.values
         return reduce(visitor, operands)
 
+
 # ast.Call signature changed on 3.5,
 # conditionally change which methods is named
 # visit_Call depending on Python version, #11097

pandas/core/algorithms.py

@@ -926,6 +926,7 @@ def _finalize_nsmallest(arr, kth_val, n, keep, narr):
     else:
         return inds
 
+
 _dtype_map = {'datetime64[ns]': 'int64', 'timedelta64[ns]': 'int64'}
 
 
@@ -959,6 +960,7 @@ def _hashtable_algo(f, values, return_dtype=None):
     # use Object
     return f(htable.PyObjectHashTable, _ensure_object)
 
+
 _hashtables = {
     'float64': (htable.Float64HashTable, htable.Float64Vector),
     'uint64': (htable.UInt64HashTable, htable.UInt64Vector),

pandas/core/config.py

@@ -804,6 +804,7 @@ def inner(x):
 
     return inner
 
+
 # common type validators, for convenience
 # usage: register_option(... , validator = is_int)
 is_int = is_type_factory(int)

pandas/core/config_init.py

@@ -278,6 +278,7 @@ def mpl_style_cb(key):
 
     return val
 
+
 with cf.config_prefix('display'):
     cf.register_option('precision', 6, pc_precision_doc, validator=is_int)
     cf.register_option('float_format', None, float_format_doc,
@@ -380,6 +381,7 @@ def use_inf_as_null_cb(key):
     from pandas.types.missing import _use_inf_as_null
     _use_inf_as_null(key)
 
+
 with cf.config_prefix('mode'):
     cf.register_option('use_inf_as_null', False, use_inf_as_null_doc,
                        cb=use_inf_as_null_cb)

pandas/core/frame.py

@@ -5741,9 +5741,9 @@ def _from_nested_dict(data):
 def _put_str(s, space):
     return ('%s' % s)[:space].ljust(space)
 
+
 # ----------------------------------------------------------------------
 # Add plotting methods to DataFrame
-
 DataFrame.plot = base.AccessorProperty(gfx.FramePlotMethods,
                                        gfx.FramePlotMethods)
 DataFrame.hist = gfx.hist_frame

pandas/core/indexing.py

@@ -36,6 +36,7 @@ def get_indexers_list():
         ('iat', _iAtIndexer),
     ]
 
+
 # "null slice"
 _NS = slice(None, None)
 
@@ -1850,6 +1851,7 @@ def _convert_key(self, key, is_setter=False):
                                  "indexers")
         return key
 
+
 # 32-bit floating point machine epsilon
 _eps = np.finfo('f4').eps
 

pandas/formats/format.py

@@ -2479,9 +2479,9 @@ def _has_names(index):
     else:
         return index.name is not None
 
+
 # -----------------------------------------------------------------------------
 # Global formatting options
-
 _initial_defencoding = None
 
 

pandas/indexes/numeric.py

@@ -159,6 +159,7 @@ def _assert_safe_casting(cls, data, subarr):
                 raise TypeError('Unsafe NumPy casting, you must '
                                 'explicitly cast')
 
+
 Int64Index._add_numeric_methods()
 Int64Index._add_logical_methods()
 
@@ -238,6 +239,7 @@ def _assert_safe_casting(cls, data, subarr):
                 raise TypeError('Unsafe NumPy casting, you must '
                                 'explicitly cast')
 
+
 UInt64Index._add_numeric_methods()
 UInt64Index._add_logical_methods()
 
@@ -391,5 +393,6 @@ def isin(self, values, level=None):
         return lib.ismember_nans(np.array(self), value_set,
                                  isnull(list(value_set)).any())
 
+
 Float64Index._add_numeric_methods()
 Float64Index._add_logical_methods_disabled()

pandas/indexes/range.py

@@ -652,5 +652,6 @@ def _evaluate_numeric_binop(self, other):
                 reversed=True,
                 step=operator.div)
 
+
 RangeIndex._add_numeric_methods()
 RangeIndex._add_logical_methods()

pandas/io/common.py

@@ -75,6 +75,7 @@ class ParserError(ValueError):
     """
     pass
 
+
 # gh-12665: Alias for now and remove later.
 CParserError = ParserError
 
@@ -116,6 +117,7 @@ def __iter__(self):
     def __next__(self):
         raise AbstractMethodError(self)
 
+
 if not compat.PY3:
     BaseIterator.next = lambda self: self.__next__()
 

pandas/io/excel.py

@@ -886,12 +886,14 @@ def _convert_to_style(cls, style_dict):
 
         return xls_style
 
+
 register_writer(_Openpyxl1Writer)
 
 
 class _OpenpyxlWriter(_Openpyxl1Writer):
     engine = 'openpyxl'
 
+
 register_writer(_OpenpyxlWriter)
 
 
@@ -1368,6 +1370,7 @@ def write_cells(self, cells, sheet_name=None, startrow=0, startcol=0):
                             for k, v in style_kwargs.items():
                                 setattr(xcell, k, v)
 
+
 register_writer(_Openpyxl22Writer)
 
 
@@ -1491,6 +1494,7 @@ def _convert_to_style(cls, style_dict, num_format_str=None):
 
         return style
 
+
 register_writer(_XlwtWriter)
 
 
@@ -1603,4 +1607,5 @@ def _convert_to_style(self, style_dict, num_format_str=None):
 
         return xl_format
 
+
 register_writer(_XlsxWriter)

pandas/io/gbq.py

@@ -58,6 +58,7 @@ def _test_google_api_imports():
         raise ImportError("Missing module required for Google BigQuery "
                           "support: {0}".format(str(e)))
 
+
 logger = logging.getLogger('pandas.io.gbq')
 logger.setLevel(logging.ERROR)
 

pandas/io/packers.py

@@ -217,6 +217,7 @@ def read(fh):
 
     raise ValueError('path_or_buf needs to be a string file path or file-like')
 
+
 dtype_dict = {21: np.dtype('M8[ns]'),
               u('datetime64[ns]'): np.dtype('M8[ns]'),
               u('datetime64[us]'): np.dtype('M8[us]'),
@@ -237,6 +238,7 @@ def dtype_for(t):
         return dtype_dict[t]
     return np.typeDict.get(t, t)
 
+
 c2f_dict = {'complex': np.float64,
             'complex128': np.float64,
             'complex64': np.float32}

pandas/io/parsers.py

@@ -409,6 +409,7 @@ def _read(filepath_or_buffer, kwds):
 
     return data
 
+
 _parser_defaults = {
     'delimiter': None,
 
@@ -655,6 +656,7 @@ def parser_f(filepath_or_buffer,
 
     return parser_f
 
+
 read_csv = _make_parser_function('read_csv', sep=',')
 read_csv = Appender(_read_csv_doc)(read_csv)
 

pandas/io/pytables.py

@@ -74,6 +74,7 @@ def _ensure_encoding(encoding):
             encoding = _default_encoding
     return encoding
 
+
 Term = Expr
 
 
@@ -112,6 +113,7 @@ class ClosedFileError(Exception):
 class IncompatibilityWarning(Warning):
     pass
 
+
 incompatibility_doc = """
 where criteria is being ignored as this version [%s] is too old (or
 not-defined), read the file in and write it out to a new file to upgrade (with
@@ -122,6 +124,7 @@ class IncompatibilityWarning(Warning):
 class AttributeConflictWarning(Warning):
     pass
 
+
 attribute_conflict_doc = """
 the [%s] attribute of the existing index is [%s] which conflicts with the new
 [%s], resetting the attribute to None
@@ -131,6 +134,7 @@ class AttributeConflictWarning(Warning):
 class DuplicateWarning(Warning):
     pass
 
+
 duplicate_doc = """
 duplicate entries in table, taking most recently appended
 """

pandas/io/sql.py

@@ -495,6 +495,7 @@ def has_table(table_name, con, flavor=None, schema=None):
     pandas_sql = pandasSQL_builder(con, flavor=flavor, schema=schema)
     return pandas_sql.has_table(table_name)
 
+
 table_exists = has_table
 
 

pandas/io/stata.py

@@ -459,6 +459,7 @@ class PossiblePrecisionLoss(Warning):
 class ValueLabelTypeMismatch(Warning):
     pass
 
+
 value_label_mismatch_doc = """
 Stata value labels (pandas categories) must be strings. Column {0} contains
 non-string labels which will be converted to strings.  Please check that the

pandas/msgpack/__init__.py

@@ -41,6 +41,7 @@ def packb(o, **kwargs):
     """
     return Packer(**kwargs).pack(o)
 
+
 # alias for compatibility to simplejson/marshal/pickle.
 load = unpack
 loads = unpackb

pandas/sparse/frame.py

@@ -863,6 +863,7 @@ def homogenize(series_dict):
 
     return output
 
+
 # use unaccelerated ops for sparse objects
 ops.add_flex_arithmetic_methods(SparseDataFrame, use_numexpr=False,
                                 **ops.frame_flex_funcs)

pandas/sparse/series.py

@@ -832,6 +832,7 @@ def from_coo(cls, A, dense_index=False):
         """
         return _coo_to_sparse_series(A, dense_index=dense_index)
 
+
 # overwrite series methods with unaccelerated versions
 ops.add_special_arithmetic_methods(SparseSeries, use_numexpr=False,
                                    **ops.series_special_funcs)

pandas/stats/moments.py

@@ -385,6 +385,7 @@ def ewmstd(arg, com=None, span=None, halflife=None, alpha=None, min_periods=0,
                          bias=bias,
                          func_kw=['bias'])
 
+
 ewmvol = ewmstd
 
 
@@ -476,6 +477,7 @@ def f(arg, window, min_periods=None, freq=None, center=False,
                              **kwargs)
     return f
 
+
 rolling_max = _rolling_func('max', 'Moving maximum.', how='max')
 rolling_min = _rolling_func('min', 'Moving minimum.', how='min')
 rolling_sum = _rolling_func('sum', 'Moving sum.')
@@ -683,6 +685,7 @@ def f(arg, min_periods=1, freq=None, **kwargs):
                              **kwargs)
     return f
 
+
 expanding_max = _expanding_func('max', 'Expanding maximum.')
 expanding_min = _expanding_func('min', 'Expanding minimum.')
 expanding_sum = _expanding_func('sum', 'Expanding sum.')

pandas/tests/sparse/test_libsparse.py

@@ -560,8 +560,8 @@ def _check_case(xloc, xlen, yloc, ylen, eloc, elen):
 
         check_cases(_check_case)
 
-# too cute? oh but how I abhor code duplication
 
+# too cute? oh but how I abhor code duplication
 check_ops = ['add', 'sub', 'mul', 'truediv', 'floordiv']
 
 

pandas/tests/test_generic.py

@@ -1588,6 +1588,7 @@ def test_to_xarray(self):
             # non-convertible
             self.assertRaises(ValueError, lambda: result.to_pandas())
 
+
 # run all the tests, but wrap each in a warning catcher
 for t in ['test_rename', 'test_rename_axis', 'test_get_numeric_data',
           'test_get_default', 'test_nonzero',