Changed x.__class__ to type(x)

Author: MomIsBestFriend

pandas/_libs/tslibs/c_timestamp.pyx

@@ -87,7 +87,7 @@ cdef class _Timestamp(datetime):
                 return PyObject_RichCompareBool(val, other, op)
 
             try:
-                ots = self.__class__(other)
+                ots = type(self)(other)
             except ValueError:
                 return self._compare_outside_nanorange(other, op)
         else:
@@ -96,7 +96,7 @@ cdef class _Timestamp(datetime):
             if ndim != -1:
                 if ndim == 0:
                     if is_datetime64_object(other):
-                        other = self.__class__(other)
+                        other = type(self)(other)
                     elif is_array(other):
                         # zero-dim array, occurs if try comparison with
                         #  datetime64 scalar on the left hand side
@@ -105,7 +105,7 @@ cdef class _Timestamp(datetime):
                         #  the numpy C api to extract it.
                         other = cnp.PyArray_ToScalar(cnp.PyArray_DATA(other),
                                                      other)
-                        other = self.__class__(other)
+                        other = type(self)(other)
                     else:
                         return NotImplemented
                 elif is_array(other):
@@ -226,8 +226,7 @@ cdef class _Timestamp(datetime):
 
         if is_timedelta64_object(other):
             other_int = other.astype('timedelta64[ns]').view('i8')
-            return self.__class__(self.value + other_int,
-                                  tz=self.tzinfo, freq=self.freq)
+            return type(self)(self.value + other_int, tz=self.tzinfo, freq=self.freq)
 
         elif is_integer_object(other):
             maybe_integer_op_deprecated(self)
@@ -238,8 +237,7 @@ cdef class _Timestamp(datetime):
             elif self.freq is None:
                 raise NullFrequencyError(
                     "Cannot add integral value to Timestamp without freq.")
-            return self.__class__((self.freq * other).apply(self),
-                                  freq=self.freq)
+            return type(self)((self.freq * other).apply(self), freq=self.freq)
 
         elif PyDelta_Check(other) or hasattr(other, 'delta'):
             # delta --> offsets.Tick
@@ -253,8 +251,7 @@ cdef class _Timestamp(datetime):
                          other.seconds * 1000000 +
                          other.microseconds) * 1000
 
-            result = self.__class__(self.value + nanos,
-                                    tz=self.tzinfo, freq=self.freq)
+            result = type(self)(self.value + nanos, tz=self.tzinfo, freq=self.freq)
             return result
 
         elif is_array(other):
@@ -272,7 +269,7 @@ cdef class _Timestamp(datetime):
 
         result = datetime.__add__(self, other)
         if PyDateTime_Check(result):
-            result = self.__class__(result)
+            result = type(self)(result)
             result.nanosecond = self.nanosecond
         return result
 
@@ -304,9 +301,9 @@ cdef class _Timestamp(datetime):
         if (PyDateTime_Check(self)
                 and (PyDateTime_Check(other) or is_datetime64_object(other))):
             if isinstance(self, _Timestamp):
-                other = self.__class__(other)
+                other = type(self)(other)
             else:
-                self = other.__class__(self)
+                self = type(other)(self)
 
             # validate tz's
             if not tz_compare(self.tzinfo, other.tzinfo):

pandas/core/groupby/base.py

@@ -41,7 +41,7 @@ def _gotitem(self, key, ndim, subset=None):
         except IndexError:
             groupby = self._groupby
 
-        self = self.__class__(subset, groupby=groupby, parent=self, **kwargs)
+        self = type(self)(subset, groupby=groupby, parent=self, **kwargs)
         self._reset_cache()
         if subset.ndim == 2:
             if is_scalar(key) and key in subset or is_list_like(key):

pandas/core/indexes/frozen.py

@@ -69,13 +69,13 @@ def difference(self, other) -> "FrozenList":
 
     def __getitem__(self, n):
         if isinstance(n, slice):
-            return self.__class__(super().__getitem__(n))
+            return type(self)(super().__getitem__(n))
         return super().__getitem__(n)
 
     def __radd__(self, other):
         if isinstance(other, tuple):
             other = list(other)
-        return self.__class__(other + list(self))
+        return type(self)(other + list(self))
 
     def __eq__(self, other):
         if isinstance(other, (tuple, FrozenList)):
@@ -85,7 +85,7 @@ def __eq__(self, other):
     __req__ = __eq__
 
     def __mul__(self, other):
-        return self.__class__(super().__mul__(other))
+        return type(self)(super().__mul__(other))
 
     __imul__ = __mul__
 

pandas/core/indexes/range.py

@@ -609,27 +609,27 @@ def _union(self, other, sort):
                     and (start_s - end_o) <= step_s
                     and (start_o - end_s) <= step_s
                 ):
-                    return self.__class__(start_r, end_r + step_s, step_s)
+                    return type(self)(start_r, end_r + step_s, step_s)
                 if (
                     (step_s % 2 == 0)
                     and (abs(start_s - start_o) <= step_s / 2)
                     and (abs(end_s - end_o) <= step_s / 2)
                 ):
-                    return self.__class__(start_r, end_r + step_s / 2, step_s / 2)
+                    return type(self)(start_r, end_r + step_s / 2, step_s / 2)
             elif step_o % step_s == 0:
                 if (
                     (start_o - start_s) % step_s == 0
                     and (start_o + step_s >= start_s)
                     and (end_o - step_s <= end_s)
                 ):
-                    return self.__class__(start_r, end_r + step_s, step_s)
+                    return type(self)(start_r, end_r + step_s, step_s)
             elif step_s % step_o == 0:
                 if (
                     (start_s - start_o) % step_o == 0
                     and (start_s + step_o >= start_o)
                     and (end_s - step_o <= end_o)
                 ):
-                    return self.__class__(start_r, end_r + step_o, step_o)
+                    return type(self)(start_r, end_r + step_o, step_o)
         return self._int64index._union(other, sort=sort)
 
     @Appender(_index_shared_docs["join"])
@@ -798,7 +798,7 @@ def _evaluate_numeric_binop(self, other):
                         rstart = op(left.start, right)
                         rstop = op(left.stop, right)
 
-                    result = self.__class__(rstart, rstop, rstep, **attrs)
+                    result = type(self)(rstart, rstop, rstep, **attrs)
 
                     # for compat with numpy / Int64Index
                     # even if we can represent as a RangeIndex, return

pandas/core/indexing.py

@@ -105,7 +105,7 @@ class _NDFrameIndexer(_NDFrameIndexerBase):
 
     def __call__(self, axis=None):
         # we need to return a copy of ourselves
-        new_self = self.__class__(self.name, self.obj)
+        new_self = type(self)(self.name, self.obj)
 
         if axis is not None:
             axis = self.obj._get_axis_number(axis)

pandas/core/internals/managers.py

@@ -154,7 +154,7 @@ def make_empty(self, axes=None):
             blocks = np.array([], dtype=self.array_dtype)
         else:
             blocks = []
-        return self.__class__(blocks, axes)
+        return type(self)(blocks, axes)
 
     def __nonzero__(self):
         return True
@@ -435,7 +435,7 @@ def apply(
 
         if len(result_blocks) == 0:
             return self.make_empty(axes or self.axes)
-        bm = self.__class__(
+        bm = type(self)(
             result_blocks, axes or self.axes, do_integrity_check=do_integrity_check
         )
         bm._consolidate_inplace()
@@ -524,7 +524,7 @@ def get_axe(block, qs, axes):
                     for b in blocks
                 ]
 
-            return self.__class__(blocks, new_axes)
+            return type(self)(blocks, new_axes)
 
         # single block, i.e. ndim == {1}
         values = concat_compat([b.values for b in blocks])
@@ -634,7 +634,7 @@ def comp(s, regex=False):
                 rb = new_rb
             result_blocks.extend(rb)
 
-        bm = self.__class__(result_blocks, self.axes)
+        bm = type(self)(result_blocks, self.axes)
         bm._consolidate_inplace()
         return bm
 
@@ -729,7 +729,7 @@ def combine(self, blocks, copy=True):
         axes = list(self.axes)
         axes[0] = self.items.take(indexer)
 
-        return self.__class__(new_blocks, axes, do_integrity_check=False)
+        return type(self)(new_blocks, axes, do_integrity_check=False)
 
     def get_slice(self, slobj, axis=0):
         if axis >= self.ndim:
@@ -746,7 +746,7 @@ def get_slice(self, slobj, axis=0):
         new_axes = list(self.axes)
         new_axes[axis] = new_axes[axis][slobj]
 
-        bm = self.__class__(new_blocks, new_axes, do_integrity_check=False)
+        bm = type(self)(new_blocks, new_axes, do_integrity_check=False)
         bm._consolidate_inplace()
         return bm
 
@@ -922,7 +922,7 @@ def consolidate(self):
         if self.is_consolidated():
             return self
 
-        bm = self.__class__(self.blocks, self.axes)
+        bm = type(self)(self.blocks, self.axes)
         bm._is_consolidated = False
         bm._consolidate_inplace()
         return bm
@@ -1256,7 +1256,7 @@ def reindex_indexer(
 
         new_axes = list(self.axes)
         new_axes[axis] = new_axis
-        return self.__class__(new_blocks, new_axes)
+        return type(self)(new_blocks, new_axes)
 
     def _slice_take_blocks_ax0(self, slice_or_indexer, fill_tuple=None):
         """
@@ -1526,9 +1526,7 @@ def get_slice(self, slobj, axis=0):
         if axis >= self.ndim:
             raise IndexError("Requested axis not found in manager")
 
-        return self.__class__(
-            self._block._slice(slobj), self.index[slobj], fastpath=True
-        )
+        return type(self)(self._block._slice(slobj), self.index[slobj], fastpath=True)
 
     @property
     def index(self):

pandas/core/resample.py

@@ -885,7 +885,7 @@ def count(self):
         result = self._downsample("count")
         if not len(self.ax):
             if self._selected_obj.ndim == 1:
-                result = self._selected_obj.__class__(
+                result = type(self._selected_obj)(
                     [], index=result.index, dtype="int64", name=self._selected_obj.name
                 )
             else:

pandas/tests/indexes/common.py

@@ -260,8 +260,8 @@ def test_copy_name(self, indices):
         if isinstance(indices, MultiIndex):
             return
 
-        first = indices.__class__(indices, copy=True, name="mario")
-        second = first.__class__(first, copy=False)
+        first = type(indices)(indices, copy=True, name="mario")
+        second = type(first)(first, copy=False)
 
         # Even though "copy=False", we want a new object.
         assert first is not second
@@ -677,9 +677,9 @@ def test_hasnans_isnans(self, indices):
             values[1] = np.nan
 
         if isinstance(indices, PeriodIndex):
-            idx = indices.__class__(values, freq=indices.freq)
+            idx = type(indices)(values, freq=indices.freq)
         else:
-            idx = indices.__class__(values)
+            idx = type(indices)(values)
 
             expected = np.array([False] * len(idx), dtype=bool)
             expected[1] = True
@@ -716,9 +716,9 @@ def test_fillna(self, indices):
                 values[1] = np.nan
 
             if isinstance(indices, PeriodIndex):
-                idx = indices.__class__(values, freq=indices.freq)
+                idx = type(indices)(values, freq=indices.freq)
             else:
-                idx = indices.__class__(values)
+                idx = type(indices)(values)
 
             expected = np.array([False] * len(idx), dtype=bool)
             expected[1] = True

pandas/tests/indexes/multi/test_missing.py

@@ -42,9 +42,9 @@ def test_fillna(idx):
                 values[1] = np.nan
 
             if isinstance(index, PeriodIndex):
-                idx = index.__class__(values, freq=index.freq)
+                idx = type(index)(values, freq=index.freq)
             else:
-                idx = index.__class__(values)
+                idx = type(index)(values)
 
             expected = np.array([False] * len(idx), dtype=bool)
             expected[1] = True
@@ -115,7 +115,7 @@ def test_hasnans_isnans(idx):
     values = index.values
     values[1] = np.nan
 
-    index = idx.__class__(values)
+    index = type(idx)(values)
 
     expected = np.array([False] * len(index), dtype=bool)
     expected[1] = True

pandas/tests/indexes/period/test_partial_slicing.py

@@ -123,7 +123,7 @@ def test_range_slice_outofbounds(self):
 
         for idx in [didx, pidx]:
             df = DataFrame(dict(units=[100 + i for i in range(10)]), index=idx)
-            empty = DataFrame(index=idx.__class__([], freq="D"), columns=["units"])
+            empty = DataFrame(index=type(idx)([], freq="D"), columns=["units"])
             empty["units"] = empty["units"].astype("int64")
 
             tm.assert_frame_equal(df["2013/09/01":"2013/09/30"], empty)

pandas/tests/indexes/test_base.py

@@ -752,7 +752,7 @@ def test_fancy(self):
     @pytest.mark.parametrize("dtype", [np.int_, np.bool_])
     def test_empty_fancy(self, index, dtype):
         empty_arr = np.array([], dtype=dtype)
-        empty_index = index.__class__([])
+        empty_index = type(index)([])
 
         assert index[[]].identical(empty_index)
         assert index[empty_arr].identical(empty_index)
@@ -762,7 +762,7 @@ def test_empty_fancy_raises(self, index):
         # pd.DatetimeIndex is excluded, because it overrides getitem and should
         # be tested separately.
         empty_farr = np.array([], dtype=np.float_)
-        empty_index = index.__class__([])
+        empty_index = type(index)([])
 
         assert index[[]].identical(empty_index)
         # np.ndarray only accepts ndarray of int & bool dtypes, so should Index
@@ -2446,8 +2446,8 @@ def test_copy_name(self):
         # GH12309
         index = self.create_index()
 
-        first = index.__class__(index, copy=True, name="mario")
-        second = first.__class__(first, copy=False)
+        first = type(index)(index, copy=True, name="mario")
+        second = type(first)(first, copy=False)
 
         # Even though "copy=False", we want a new object.
         assert first is not second

pandas/tseries/offsets.py

@@ -402,7 +402,7 @@ def rollback(self, dt):
         """
         dt = as_timestamp(dt)
         if not self.onOffset(dt):
-            dt = dt - self.__class__(1, normalize=self.normalize, **self.kwds)
+            dt = dt - type(self)(1, normalize=self.normalize, **self.kwds)
         return dt
 
     def rollforward(self, dt):
@@ -416,7 +416,7 @@ def rollforward(self, dt):
         """
         dt = as_timestamp(dt)
         if not self.onOffset(dt):
-            dt = dt + self.__class__(1, normalize=self.normalize, **self.kwds)
+            dt = dt + type(self)(1, normalize=self.normalize, **self.kwds)
         return dt
 
     def onOffset(self, dt):