Merge pull request #76 from pandas-dev/master

Sync Fork from Upstream Repo

Author: sthagen

pandas/core/algorithms.py

@@ -313,8 +313,8 @@ def unique(values):
 
     See Also
     --------
-    Index.unique
-    Series.unique
+    Index.unique : Return unique values from an Index.
+    Series.unique : Return unique values of Series object.
 
     Examples
     --------
@@ -1515,7 +1515,7 @@ def take(arr, indices, axis: int = 0, allow_fill: bool = False, fill_value=None)
 
     See Also
     --------
-    numpy.take
+    numpy.take : Take elements from an array along an axis.
 
     Examples
     --------

pandas/core/frame.py

@@ -358,9 +358,9 @@ class DataFrame(NDFrame):
     --------
     DataFrame.from_records : Constructor from tuples, also record arrays.
     DataFrame.from_dict : From dicts of Series, arrays, or dicts.
-    read_csv
-    read_table
-    read_clipboard
+    read_csv : Read a comma-separated values (csv) file into DataFrame.
+    read_table : Read general delimited file into DataFrame.
+    read_clipboard : Read text from clipboard into DataFrame.
 
     Examples
     --------
@@ -7393,8 +7393,9 @@ def corr(self, method="pearson", min_periods=1) -> "DataFrame":
 
         See Also
         --------
-        DataFrame.corrwith
-        Series.corr
+        DataFrame.corrwith : Compute pairwise correlation with another
+            DataFrame or Series.
+        Series.corr : Compute the correlation between two Series.
 
         Examples
         --------
@@ -7596,7 +7597,7 @@ def corrwith(self, other, axis=0, drop=False, method="pearson") -> Series:
 
         See Also
         --------
-        DataFrame.corr
+        DataFrame.corr : Compute pairwise correlation of columns.
         """
         axis = self._get_axis_number(axis)
         this = self._get_numeric_data()
@@ -8001,7 +8002,7 @@ def idxmin(self, axis=0, skipna=True) -> Series:
 
         See Also
         --------
-        Series.idxmin
+        Series.idxmin : Return index of the minimum element.
 
         Notes
         -----
@@ -8039,7 +8040,7 @@ def idxmax(self, axis=0, skipna=True) -> Series:
 
         See Also
         --------
-        Series.idxmax
+        Series.idxmax : Return index of the maximum element.
 
         Notes
         -----

pandas/core/indexes/base.py

@@ -32,7 +32,6 @@
     is_categorical,
     is_categorical_dtype,
     is_datetime64_any_dtype,
-    is_datetime64tz_dtype,
     is_dtype_equal,
     is_extension_array_dtype,
     is_float,
@@ -2525,14 +2524,8 @@ def _union(self, other, sort):
             return other._get_reconciled_name_object(self)
 
         # TODO(EA): setops-refactor, clean all this up
-        if is_datetime64tz_dtype(self):
-            lvals = self._ndarray_values
-        else:
-            lvals = self._values
-        if is_datetime64tz_dtype(other):
-            rvals = other._ndarray_values
-        else:
-            rvals = other._values
+        lvals = self._values
+        rvals = other._values
 
         if sort is None and self.is_monotonic and other.is_monotonic:
             try:
@@ -3078,48 +3071,6 @@ def _get_partial_string_timestamp_match_key(self, key):
         # GH#10331
         return key
 
-    def _convert_scalar_indexer(self, key, kind: str_t):
-        """
-        Convert a scalar indexer.
-
-        Parameters
-        ----------
-        key : label of the slice bound
-        kind : {'loc', 'getitem'}
-        """
-        assert kind in ["loc", "getitem"]
-
-        if len(self) and not isinstance(self, ABCMultiIndex):
-
-            # we can raise here if we are definitive that this
-            # is positional indexing (eg. .loc on with a float)
-            # or label indexing if we are using a type able
-            # to be represented in the index
-
-            if kind == "getitem" and is_float(key):
-                if not self.is_floating():
-                    raise KeyError(key)
-
-            elif kind == "loc" and is_float(key):
-
-                # we want to raise KeyError on string/mixed here
-                # technically we *could* raise a TypeError
-                # on anything but mixed though
-                if self.inferred_type not in [
-                    "floating",
-                    "mixed-integer-float",
-                    "integer-na",
-                    "string",
-                    "mixed",
-                ]:
-                    raise KeyError(key)
-
-            elif kind == "loc" and is_integer(key):
-                if not (is_integer_dtype(self.dtype) or is_object_dtype(self.dtype)):
-                    raise KeyError(key)
-
-        return key
-
     def _validate_positional_slice(self, key: slice):
         """
         For positional indexing, a slice must have either int or None

pandas/core/indexes/category.py

@@ -574,16 +574,6 @@ def get_indexer_non_unique(self, target):
         indexer, missing = self._engine.get_indexer_non_unique(codes)
         return ensure_platform_int(indexer), missing
 
-    @Appender(Index._convert_scalar_indexer.__doc__)
-    def _convert_scalar_indexer(self, key, kind: str):
-        assert kind in ["loc", "getitem"]
-        if kind == "loc":
-            try:
-                return self.categories._convert_scalar_indexer(key, kind="loc")
-            except TypeError:
-                raise KeyError(key)
-        return super()._convert_scalar_indexer(key, kind=kind)
-
     @Appender(Index._convert_list_indexer.__doc__)
     def _convert_list_indexer(self, keyarr):
         # Return our indexer or raise if all of the values are not included in

pandas/core/indexes/datetimelike.py

@@ -18,7 +18,6 @@
     is_bool_dtype,
     is_categorical_dtype,
     is_dtype_equal,
-    is_float,
     is_integer,
     is_list_like,
     is_period_dtype,
@@ -377,32 +376,6 @@ def _format_attrs(self):
     # --------------------------------------------------------------------
     # Indexing Methods
 
-    def _convert_scalar_indexer(self, key, kind: str):
-        """
-        We don't allow integer or float indexing on datetime-like when using
-        loc.
-
-        Parameters
-        ----------
-        key : label of the slice bound
-        kind : {'loc', 'getitem'}
-        """
-        assert kind in ["loc", "getitem"]
-
-        if not is_scalar(key):
-            raise TypeError(key)
-
-        # we don't allow integer/float indexing for loc
-        # we don't allow float indexing for getitem
-        is_int = is_integer(key)
-        is_flt = is_float(key)
-        if kind == "loc" and (is_int or is_flt):
-            raise KeyError(key)
-        elif kind == "getitem" and is_flt:
-            raise KeyError(key)
-
-        return super()._convert_scalar_indexer(key, kind=kind)
-
     def _validate_partial_date_slice(self, reso: str):
         raise NotImplementedError
 

pandas/core/indexes/interval.py

@@ -514,12 +514,6 @@ def _should_fallback_to_positional(self):
         #  positional in this case
         return self.dtype.subtype.kind in ["m", "M"]
 
-    @Appender(Index._convert_scalar_indexer.__doc__)
-    def _convert_scalar_indexer(self, key, kind: str):
-        assert kind in ["getitem", "loc"]
-        # never iloc, so no-op
-        return key
-
     def _maybe_cast_slice_bound(self, label, side, kind):
         return getattr(self, side)._maybe_cast_slice_bound(label, side, kind)
 

pandas/core/indexes/numeric.py

@@ -254,14 +254,6 @@ def asi8(self) -> np.ndarray:
         # do not cache or you'll create a memory leak
         return self.values.view(self._default_dtype)
 
-    @Appender(Index._convert_scalar_indexer.__doc__)
-    def _convert_scalar_indexer(self, key, kind: str):
-        assert kind in ["loc", "getitem"]
-
-        # never iloc, which we don't coerce to integers
-        key = self._maybe_cast_indexer(key)
-        return super()._convert_scalar_indexer(key, kind=kind)
-
 
 class Int64Index(IntegerIndex):
     __doc__ = _num_index_shared_docs["class_descr"] % _int64_descr_args
@@ -391,12 +383,6 @@ def astype(self, dtype, copy=True):
     def _should_fallback_to_positional(self):
         return False
 
-    @Appender(Index._convert_scalar_indexer.__doc__)
-    def _convert_scalar_indexer(self, key, kind: str):
-        assert kind in ["loc", "getitem"]
-        # no-op for non-iloc
-        return key
-
     @Appender(Index._convert_slice_indexer.__doc__)
     def _convert_slice_indexer(self, key: slice, kind: str):
         assert kind in ["loc", "getitem"]

pandas/core/indexing.py

@@ -866,16 +866,7 @@ def _validate_key(self, key, axis: int):
         # slice of labels (where start-end in labels)
         # slice of integers (only if in the labels)
         # boolean
-
-        if isinstance(key, slice):
-            return
-
-        if com.is_bool_indexer(key):
-            return
-
-        if not is_list_like_indexer(key):
-            labels = self.obj._get_axis(axis)
-            labels._convert_scalar_indexer(key, kind="loc")
+        pass
 
     def _has_valid_setitem_indexer(self, indexer) -> bool:
         return True
@@ -1139,15 +1130,6 @@ def _convert_to_indexer(self, key, axis: int, is_setter: bool = False):
         if isinstance(key, slice):
             return labels._convert_slice_indexer(key, kind="loc")
 
-        if is_scalar(key):
-            # try to find out correct indexer, if not type correct raise
-            try:
-                key = labels._convert_scalar_indexer(key, kind="loc")
-            except KeyError:
-                # but we will allow setting
-                if not is_setter:
-                    raise
-
         # see if we are positional in nature
         is_int_index = labels.is_integer()
         is_int_positional = is_integer(key) and not is_int_index
@@ -2029,11 +2011,17 @@ def _convert_key(self, key, is_setter: bool = False):
         if is_setter:
             return list(key)
 
-        lkey = list(key)
-        for n, (ax, i) in enumerate(zip(self.obj.axes, key)):
-            lkey[n] = ax._convert_scalar_indexer(i, kind="loc")
+        return key
 
-        return tuple(lkey)
+    def __getitem__(self, key):
+        if self.ndim != 1 or not is_scalar(key):
+            # FIXME: is_scalar check is a kludge
+            return super().__getitem__(key)
+
+        # Like Index.get_value, but we do not allow positional fallback
+        obj = self.obj
+        loc = obj.index.get_loc(key)
+        return obj.index._get_values_for_loc(obj, loc, key)
 
 
 @Appender(IndexingMixin.iat.__doc__)