add checks to categorical and tweak imports

Author: rforgione

pandas/computation/eval.py

@@ -148,7 +148,7 @@ def _check_for_locals(expr, stack_level, parser):
 
 def eval(expr, parser='pandas', engine=None, truediv=True,
          local_dict=None, global_dict=None, resolvers=(), level=0,
-         target=None, inplace=None):
+         target=None, inplace=True):
     """Evaluate a Python expression as a string using various backends.
 
     The following arithmetic operations are supported: ``+``, ``-``, ``*``,
@@ -211,10 +211,6 @@ def eval(expr, parser='pandas', engine=None, truediv=True,
         If expression mutates, whether to modify object inplace or return
         copy with mutation.
 
-        WARNING: inplace=None currently falls back to to True, but
-        in a future version, will default to False.  Use inplace=True
-        explicitly rather than relying on the default.
-
     Returns
     -------
     ndarray, numeric scalar, DataFrame, Series
@@ -232,7 +228,7 @@ def eval(expr, parser='pandas', engine=None, truediv=True,
     pandas.DataFrame.query
     pandas.DataFrame.eval
     """
-    inplace = com.enforce_bool_type(inplace)
+    inplace = com._enforce_bool_type(inplace)
     first_expr = True
     if isinstance(expr, string_types):
         exprs = [e for e in expr.splitlines() if e != '']

pandas/core/categorical.py

@@ -23,7 +23,7 @@
                                  is_integer_dtype, is_bool,
                                  is_list_like, is_sequence,
                                  is_scalar)
-from pandas.core.common import is_null_slice
+from pandas.core.common import is_null_slice, _enforce_bool_type
 
 from pandas.core.algorithms import factorize, take_1d
 from pandas.core.base import (PandasObject, PandasDelegate,
@@ -615,6 +615,7 @@ def set_ordered(self, value, inplace=False):
            Whether or not to set the ordered attribute inplace or return a copy
            of this categorical with ordered set to the value
         """
+        inplace = _enforce_bool_type(inplace)
         self._validate_ordered(value)
         cat = self if inplace else self.copy()
         cat._ordered = value
@@ -631,7 +632,7 @@ def as_ordered(self, inplace=False):
            Whether or not to set the ordered attribute inplace or return a copy
            of this categorical with ordered set to True
         """
-        return self.set_ordered(True, inplace=inplace)
+        return self.set_ordered(True, inplace=_enforce_bool_type(inplace))
 
     def as_unordered(self, inplace=False):
         """
@@ -643,7 +644,7 @@ def as_unordered(self, inplace=False):
            Whether or not to set the ordered attribute inplace or return a copy
            of this categorical with ordered set to False
         """
-        return self.set_ordered(False, inplace=inplace)
+        return self.set_ordered(False, inplace=_enforce_bool_type(inplace))
 
     def _get_ordered(self):
         """ Gets the ordered attribute """
@@ -702,6 +703,7 @@ def set_categories(self, new_categories, ordered=None, rename=False,
         remove_categories
         remove_unused_categories
         """
+        inplace = _enforce_bool_type(inplace)
         new_categories = self._validate_categories(new_categories)
         cat = self if inplace else self.copy()
         if rename:
@@ -754,6 +756,7 @@ def rename_categories(self, new_categories, inplace=False):
         remove_unused_categories
         set_categories
         """
+        inplace = _enforce_bool_type(inplace)
         cat = self if inplace else self.copy()
         cat.categories = new_categories
         if not inplace:
@@ -794,6 +797,7 @@ def reorder_categories(self, new_categories, ordered=None, inplace=False):
         remove_unused_categories
         set_categories
         """
+        inplace = _enforce_bool_type(inplace)
         if set(self._categories) != set(new_categories):
             raise ValueError("items in new_categories are not the same as in "
                              "old categories")
@@ -832,6 +836,7 @@ def add_categories(self, new_categories, inplace=False):
         remove_unused_categories
         set_categories
         """
+        inplace = _enforce_bool_type(inplace)
         if not is_list_like(new_categories):
             new_categories = [new_categories]
         already_included = set(new_categories) & set(self._categories)
@@ -877,6 +882,7 @@ def remove_categories(self, removals, inplace=False):
         remove_unused_categories
         set_categories
         """
+        inplace = _enforce_bool_type(inplace)
         if not is_list_like(removals):
             removals = [removals]
 
@@ -917,6 +923,7 @@ def remove_unused_categories(self, inplace=False):
         remove_categories
         set_categories
         """
+        inplace = _enforce_bool_type(inplace)
         cat = self if inplace else self.copy()
         idx, inv = np.unique(cat._codes, return_inverse=True)
 
@@ -1316,6 +1323,7 @@ def sort_values(self, inplace=False, ascending=True, na_position='last'):
         [NaN, NaN, 5.0, 2.0, 2.0]
         Categories (2, int64): [2, 5]
         """
+        inplace = _enforce_bool_type(inplace)
         if na_position not in ['last', 'first']:
             raise ValueError('invalid na_position: {!r}'.format(na_position))
 

pandas/core/frame.py

@@ -2220,7 +2220,7 @@ def query(self, expr, inplace=False, **kwargs):
         else:
             return new_data
 
-    def eval(self, expr, inplace=None, **kwargs):
+    def eval(self, expr, inplace=True, **kwargs):
         """Evaluate an expression in the context of the calling DataFrame
         instance.
 
@@ -2232,10 +2232,6 @@ def eval(self, expr, inplace=None, **kwargs):
             If the expression contains an assignment, whether to return a new
             DataFrame or mutate the existing.
 
-            WARNING: inplace=None currently falls back to to True, but
-            in a future version, will default to False.  Use inplace=True
-            explicitly rather than relying on the default.
-
             .. versionadded:: 0.18.0
 
         kwargs : dict

pandas/core/internals.py

@@ -361,7 +361,7 @@ def fillna(self, value, limit=None, inplace=False, downcast=None,
         """ fillna on the block with the value. If we fail, then convert to
         ObjectBlock and try again
         """
-        inplace = com.enforce_bool_type(inplace)
+        inplace = _enforce_bool_type(inplace)
 
         if not self._can_hold_na:
             if inplace:
@@ -622,7 +622,7 @@ def replace(self, to_replace, value, inplace=False, filter=None,
         compatibility.
         """
 
-        inplace = com.enforce_bool_type(inplace)
+        inplace = _enforce_bool_type(inplace)
         original_to_replace = to_replace
         mask = isnull(self.values)
 
@@ -896,7 +896,7 @@ def interpolate(self, method='pad', axis=0, index=None, values=None,
                     fill_value=None, coerce=False, downcast=None, mgr=None,
                     **kwargs):
 
-        inplace = com.enforce_bool_type(inplace)
+        inplace = _enforce_bool_type(inplace)
 
         def check_int_bool(self, inplace):
             # Only FloatBlocks will contain NaNs.
@@ -945,7 +945,7 @@ def _interpolate_with_fill(self, method='pad', axis=0, inplace=False,
                                downcast=None, mgr=None):
         """ fillna but using the interpolate machinery """
 
-        inplace = com.enforce_bool_type(inplace)
+        inplace = _enforce_bool_type(inplace)
 
         # if we are coercing, then don't force the conversion
         # if the block can't hold the type
@@ -973,7 +973,7 @@ def _interpolate(self, method=None, index=None, values=None,
                      mgr=None, **kwargs):
         """ interpolate using scipy wrappers """
 
-        inplace = com.enforce_bool_type(inplace)
+        inplace = _enforce_bool_type(inplace)
         data = self.values if inplace else self.values.copy()
 
         # only deal with floats
@@ -1495,7 +1495,7 @@ def putmask(self, mask, new, align=True, inplace=False, axis=0,
         -------
         a new block(s), the result of the putmask
         """
-        inplace = com.enforce_bool_type(inplace)
+        inplace = _enforce_bool_type(inplace)
 
         # use block's copy logic.
         # .values may be an Index which does shallow copy by default
@@ -1783,7 +1783,7 @@ def should_store(self, value):
 
     def replace(self, to_replace, value, inplace=False, filter=None,
                 regex=False, mgr=None):
-        inplace = com.enforce_bool_type(inplace)
+        inplace = _enforce_bool_type(inplace)
         to_replace_values = np.atleast_1d(to_replace)
         if not np.can_cast(to_replace_values, bool):
             return self
@@ -1965,7 +1965,7 @@ def replace(self, to_replace, value, inplace=False, filter=None,
     def _replace_single(self, to_replace, value, inplace=False, filter=None,
                         regex=False, convert=True, mgr=None):
 
-        inplace = com.enforce_bool_type(inplace)
+        inplace = _enforce_bool_type(inplace)
 
         # to_replace is regex compilable
         to_rep_re = regex and is_re_compilable(to_replace)
@@ -3190,7 +3190,7 @@ def replace_list(self, src_list, dest_list, inplace=False, regex=False,
                      mgr=None):
         """ do a list replace """
 
-        inplace = com.enforce_bool_type(inplace)
+        inplace = _enforce_bool_type(inplace)
 
         if mgr is None:
             mgr = self

pandas/core/series.py

@@ -2354,7 +2354,11 @@ def align(self, other, join='outer', axis=None, level=None, copy=True,
 
     @Appender(generic._shared_docs['rename'] % _shared_doc_kwargs)
     def rename(self, index=None, **kwargs):
-        kwargs['inplace'] = _enforce_bool_type(kwargs['inplace'])
+        if 'inplace' in kwargs:
+            kwargs['inplace'] = _enforce_bool_type(kwargs['inplace'])
+        else:
+            kwargs['inplace'] = False
+
         non_mapping = is_scalar(index) or (is_list_like(index) and
                                            not is_dict_like(index))
         if non_mapping:

pandas/tests/frame/test_missing.py

@@ -208,7 +208,7 @@ def test_fillna(self):
         # empty frame (GH #2778)
         df = DataFrame(columns=['x'])
         for m in ['pad', 'backfill']:
-            df.x.fillna(method=m, inplace=1)
+            df.x.fillna(method=m, inplace=True)
             df.x.fillna(method=m)
 
         # with different dtype (GH3386)