API/DEPR: change raise_on_error kwarg with errors kwarg in astype #14878 (#14967)

Author: m-charlton

doc/source/whatsnew/v0.20.0.txt

@@ -258,7 +258,7 @@ Deprecations
 - ``Index.repeat()`` and ``MultiIndex.repeat()`` have deprecated the ``n`` parameter in favor of ``repeats`` (:issue:`12662`)
 - ``Categorical.searchsorted()`` and ``Series.searchsorted()`` have deprecated the ``v`` parameter in favor of ``value`` (:issue:`12662`)
 - ``TimedeltaIndex.searchsorted()``, ``DatetimeIndex.searchsorted()``, and ``PeriodIndex.searchsorted()`` have deprecated the ``key`` parameter in favor of ``value`` (:issue:`12662`)
-
+- ``DataFrame.astype()`` has deprecated the ``raise_on_error`` parameter in favor of ``errors`` (:issue:`14878`)
 
 
 

pandas/core/generic.py

@@ -3061,7 +3061,9 @@ def blocks(self):
         """Internal property, property synonym for as_blocks()"""
         return self.as_blocks()
 
-    def astype(self, dtype, copy=True, raise_on_error=True, **kwargs):
+    @deprecate_kwarg(old_arg_name='raise_on_error', new_arg_name='errors',
+                     mapping={True: 'raise', False: 'ignore'})
+    def astype(self, dtype, copy=True, errors='raise', **kwargs):
         """
         Cast object to input numpy.dtype
         Return a copy when copy = True (be really careful with this!)
@@ -3073,7 +3075,15 @@ def astype(self, dtype, copy=True, raise_on_error=True, **kwargs):
             the same type. Alternatively, use {col: dtype, ...}, where col is a
             column label and dtype is a numpy.dtype or Python type to cast one
             or more of the DataFrame's columns to column-specific types.
-        raise_on_error : raise on invalid input
+        errors : {'raise', 'ignore'}, default 'raise'.
+            Control raising of exceptions on invalid data for provided dtype.
+
+            - ``raise`` : allow exceptions to be raised
+            - ``ignore`` : suppress exceptions. On error return original object
+
+            .. versionadded:: 0.20.0
+
+        raise_on_error : DEPRECATED use ``errors`` instead
         kwargs : keyword arguments to pass on to the constructor
 
         Returns
@@ -3086,7 +3096,7 @@ def astype(self, dtype, copy=True, raise_on_error=True, **kwargs):
                     raise KeyError('Only the Series name can be used for '
                                    'the key in Series dtype mappings.')
                 new_type = list(dtype.values())[0]
-                return self.astype(new_type, copy, raise_on_error, **kwargs)
+                return self.astype(new_type, copy, errors, **kwargs)
             elif self.ndim > 2:
                 raise NotImplementedError(
                     'astype() only accepts a dtype arg of type dict when '
@@ -3107,8 +3117,8 @@ def astype(self, dtype, copy=True, raise_on_error=True, **kwargs):
             return concat(results, axis=1, copy=False)
 
         # else, only a single dtype is given
-        new_data = self._data.astype(dtype=dtype, copy=copy,
-                                     raise_on_error=raise_on_error, **kwargs)
+        new_data = self._data.astype(dtype=dtype, copy=copy, errors=errors,
+                                     **kwargs)
         return self._constructor(new_data).__finalize__(self)
 
     def copy(self, deep=True):

pandas/core/internals.py

@@ -455,17 +455,23 @@ def downcast(self, dtypes=None, mgr=None):
 
         return blocks
 
-    def astype(self, dtype, copy=False, raise_on_error=True, values=None,
-               **kwargs):
-        return self._astype(dtype, copy=copy, raise_on_error=raise_on_error,
-                            values=values, **kwargs)
+    def astype(self, dtype, copy=False, errors='raise', values=None, **kwargs):
+        return self._astype(dtype, copy=copy, errors=errors, values=values,
+                            **kwargs)
 
-    def _astype(self, dtype, copy=False, raise_on_error=True, values=None,
+    def _astype(self, dtype, copy=False, errors='raise', values=None,
                 klass=None, mgr=None, **kwargs):
         """
         Coerce to the new type (if copy=True, return a new copy)
         raise on an except if raise == True
         """
+        errors_legal_values = ('raise', 'ignore')
+
+        if errors not in errors_legal_values:
+            invalid_arg = ("Expected value of kwarg 'errors' to be one of {}. "
+                           "Supplied value is '{}'".format(
+                               list(errors_legal_values), errors))
+            raise ValueError(invalid_arg)
 
         # may need to convert to categorical
         # this is only called for non-categoricals
@@ -507,7 +513,7 @@ def _astype(self, dtype, copy=False, raise_on_error=True, values=None,
             newb = make_block(values, placement=self.mgr_locs, dtype=dtype,
                               klass=klass)
         except:
-            if raise_on_error is True:
+            if errors == 'raise':
                 raise
             newb = self.copy() if copy else self
 
@@ -2147,7 +2153,7 @@ def take_nd(self, indexer, axis=0, new_mgr_locs=None, fill_tuple=None):
 
         return self.make_block_same_class(new_values, new_mgr_locs)
 
-    def _astype(self, dtype, copy=False, raise_on_error=True, values=None,
+    def _astype(self, dtype, copy=False, errors='raise', values=None,
                 klass=None, mgr=None):
         """
         Coerce to the new type (if copy=True, return a new copy)

pandas/tests/frame/test_dtypes.py

@@ -357,15 +357,15 @@ def test_astype_with_exclude_string(self):
         df = self.frame.copy()
         expected = self.frame.astype(int)
         df['string'] = 'foo'
-        casted = df.astype(int, raise_on_error=False)
+        casted = df.astype(int, errors='ignore')
 
         expected['string'] = 'foo'
         assert_frame_equal(casted, expected)
 
         df = self.frame.copy()
         expected = self.frame.astype(np.int32)
         df['string'] = 'foo'
-        casted = df.astype(np.int32, raise_on_error=False)
+        casted = df.astype(np.int32, errors='ignore')
 
         expected['string'] = 'foo'
         assert_frame_equal(casted, expected)
@@ -523,6 +523,19 @@ def test_timedeltas(self):
         result = df.get_dtype_counts().sort_values()
         assert_series_equal(result, expected)
 
+    def test_arg_for_errors_in_astype(self):
+        # issue #14878
+
+        df = DataFrame([1, 2, 3])
+
+        with self.assertRaises(ValueError):
+            df.astype(np.float64, errors=True)
+
+        with tm.assert_produces_warning(FutureWarning):
+            df.astype(np.int8, raise_on_error=False)
+
+        df.astype(np.int8, errors='ignore')
+
 
 class TestDataFrameDatetimeWithTZ(tm.TestCase, TestData):
 

pandas/tests/series/test_dtypes.py

@@ -168,3 +168,16 @@ def test_complexx(self):
         b.real = np.arange(5) + 5
         tm.assert_numpy_array_equal(a + 5, b.real)
         tm.assert_numpy_array_equal(4 * a, b.imag)
+
+    def test_arg_for_errors_in_astype(self):
+        # issue #14878
+
+        sr = Series([1, 2, 3])
+
+        with self.assertRaises(ValueError):
+            sr.astype(np.float64, errors=False)
+
+        with tm.assert_produces_warning(FutureWarning):
+            sr.astype(np.int8, raise_on_error=True)
+
+        sr.astype(np.int8, errors='raise')

pandas/tests/test_internals.py

@@ -553,7 +553,7 @@ def test_astype(self):
                          'e: f4; f: f2; g: f8')
         for t in ['float16', 'float32', 'float64', 'int32', 'int64']:
             t = np.dtype(t)
-            tmgr = mgr.astype(t, raise_on_error=False)
+            tmgr = mgr.astype(t, errors='ignore')
             self.assertEqual(tmgr.get('c').dtype.type, t)
             self.assertEqual(tmgr.get('e').dtype.type, t)
             self.assertEqual(tmgr.get('f').dtype.type, t)