valid_fill_value -> is_valid_fill_value

Author: ResidentMario

Diff for: pandas/core/generic.py

@@ -25,7 +25,7 @@
                                  is_dict_like,
                                  is_re_compilable)
 from pandas.types.cast import maybe_promote, maybe_upcast_putmask
-from pandas.types.missing import isnull, notnull, valid_fill_value
+from pandas.types.missing import isnull, notnull, is_valid_fill_value
 from pandas.types.generic import ABCSeries, ABCPanel
 
 from pandas.core.common import (_values_from_object,

Diff for: pandas/core/missing.py

@@ -14,7 +14,7 @@
                                  _ensure_float64, is_scalar,
                                  needs_i8_conversion, is_integer,
                                  is_period_arraylike)
-from pandas.types.missing import isnull, valid_fill_value
+from pandas.types.missing import isnull, is_valid_fill_value
 from pandas.types.generic import ABCSeries
 
 
@@ -658,7 +658,7 @@ def maybe_fill(obj, value, errors):
         if errors is None or errors == 'coerce':
             return True
         else:
-            if not valid_fill_value(value, obj.dtype):
+            if not is_valid_fill_value(value, obj.dtype):
                 if errors == 'raise':
                     raise TypeError('"value" parameter must be compatible '
                                     'with the {0} dtype, but you passed a '

Diff for: pandas/tests/types/test_missing.py

@@ -14,7 +14,7 @@
 from pandas.types.dtypes import DatetimeTZDtype
 from pandas.types.missing import (array_equivalent, isnull, notnull,
                                   na_value_for_dtype,
-                                  valid_fill_value)
+                                  is_valid_fill_value)
 
 
 def test_notnull():
@@ -319,7 +319,7 @@ def test_na_value_for_dtype():
                           (timedelta(0), np.timedelta64),
                           (pd.Timedelta(0), np.timedelta64)])
 def test_valid_fill_value(value, dtype):
-    assert valid_fill_value(value, dtype)
+    assert is_valid_fill_value(value, dtype)
 
 
 @pytest.mark.parametrize(('value', 'dtype'),
@@ -334,4 +334,4 @@ def test_valid_fill_value(value, dtype):
                           (datetime(1970, 1, 1), np.dtype('timedelta64')),
                           (pd.Period('1970-01-01'), np.dtype('timedelta64'))])
 def test_invalid_fill_value(value, dtype):
-    assert not valid_fill_value(value, dtype)
+    assert not is_valid_fill_value(value, dtype)

Diff for: pandas/types/missing.py

@@ -396,7 +396,7 @@ def na_value_for_dtype(dtype):
     return np.nan
 
 
-def valid_fill_value(value, dtype):
+def is_valid_fill_value(value, dtype):
     """
     Makes sure the fill value is appropriate for the given dtype.