DOC/CLN: Index shared docs with appending actual docstrings

pandas/core/indexes/category.py

@@ -19,16 +19,13 @@
 
 from pandas.util._decorators import Appender, cache_readonly
 from pandas.core.config import get_option
-from pandas.core.indexes.base import Index, _index_shared_docs
+from pandas.core.indexes.base import Index
 from pandas.core import accessor
 import pandas.core.common as com
 import pandas.core.base as base
 import pandas.core.missing as missing
 import pandas.core.indexes.base as ibase
 
-_index_doc_kwargs = dict(ibase._index_doc_kwargs)
-_index_doc_kwargs.update(dict(target_klass='CategoricalIndex'))
-
 
 class CategoricalIndex(Index, accessor.PandasDelegate):
     """
@@ -191,7 +188,7 @@ def _simple_new(cls, values, name=None, categories=None, ordered=None,
         result._reset_identity()
         return result
 
-    @Appender(_index_shared_docs['_shallow_copy'])
+    @Appender(Index._shallow_copy.__doc__)
     def _shallow_copy(self, values=None, categories=None, ordered=None,
                       dtype=None, **kwargs):
         # categories and ordered can't be part of attributes,
@@ -322,7 +319,7 @@ def ordered(self):
     def _reverse_indexer(self):
         return self._data._reverse_indexer()
 
-    @Appender(_index_shared_docs['__contains__'] % _index_doc_kwargs)
+    @Appender(Index.__contains__.__doc__)
     def __contains__(self, key):
         hash(key)
 
@@ -331,7 +328,7 @@ def __contains__(self, key):
 
         return key in self.values
 
-    @Appender(_index_shared_docs['contains'] % _index_doc_kwargs)
+    @Appender(Index.contains.__doc__)
     def contains(self, key):
         hash(key)
 
@@ -344,7 +341,7 @@ def __array__(self, dtype=None):
         """ the array interface, return my values """
         return np.array(self._data, dtype=dtype)
 
-    @Appender(_index_shared_docs['astype'])
+    @Appender(Index.astype.__doc__)
     def astype(self, dtype, copy=True):
         if is_interval_dtype(dtype):
             from pandas import IntervalIndex
@@ -362,7 +359,7 @@ def _isnan(self):
         """ return if each value is nan"""
         return self._data.codes == -1
 
-    @Appender(ibase._index_shared_docs['fillna'])
+    @Appender(Index.fillna.__doc__)
     def fillna(self, value, downcast=None):
         self._assert_can_do_op(value)
         return CategoricalIndex(self._data.fillna(value), name=self.name)
@@ -389,7 +386,7 @@ def is_monotonic_increasing(self):
     def is_monotonic_decreasing(self):
         return Index(self.codes).is_monotonic_decreasing
 
-    @Appender(_index_shared_docs['index_unique'] % _index_doc_kwargs)
+    @Appender(Index.unique.__doc__)
     def unique(self, level=None):
         if level is not None:
             self._validate_index_level(level)
@@ -399,7 +396,7 @@ def unique(self, level=None):
         return self._shallow_copy(result, categories=result.categories,
                                   ordered=result.ordered)
 
-    @Appender(base._shared_docs['duplicated'] % _index_doc_kwargs)
+    @Appender(Index.duplicated.__doc__)
     def duplicated(self, keep='first'):
         from pandas._libs.hashtable import duplicated_int64
         codes = self.codes.astype('i8')
@@ -462,7 +459,7 @@ def _can_reindex(self, indexer):
         """ always allow reindexing """
         pass
 
-    @Appender(_index_shared_docs['where'])
+    @Appender(Index.where.__doc__)
     def where(self, cond, other=None):
         if other is None:
             other = self._na_value
@@ -558,7 +555,7 @@ def _reindex_non_unique(self, target):
 
         return new_target, indexer, new_indexer
 
-    @Appender(_index_shared_docs['get_indexer'] % _index_doc_kwargs)
+    @Appender(Index.get_indexer.__doc__)
     def get_indexer(self, target, method=None, limit=None, tolerance=None):
         from pandas.core.arrays.categorical import _recode_for_categories
 
@@ -594,7 +591,7 @@ def get_indexer(self, target, method=None, limit=None, tolerance=None):
         indexer, _ = self._engine.get_indexer_non_unique(codes)
         return _ensure_platform_int(indexer)
 
-    @Appender(_index_shared_docs['get_indexer_non_unique'] % _index_doc_kwargs)
+    @Appender(Index.get_indexer_non_unique.__doc__)
     def get_indexer_non_unique(self, target):
         target = ibase._ensure_index(target)
 
@@ -605,15 +602,15 @@ def get_indexer_non_unique(self, target):
         indexer, missing = self._engine.get_indexer_non_unique(codes)
         return _ensure_platform_int(indexer), missing
 
-    @Appender(_index_shared_docs['_convert_scalar_indexer'])
+    @Appender(Index._convert_scalar_indexer.__doc__)
     def _convert_scalar_indexer(self, key, kind=None):
         if self.categories._defer_to_indexing:
             return self.categories._convert_scalar_indexer(key, kind=kind)
 
         return super(CategoricalIndex, self)._convert_scalar_indexer(
             key, kind=kind)
 
-    @Appender(_index_shared_docs['_convert_list_indexer'])
+    @Appender(Index._convert_list_indexer.__doc__)
     def _convert_list_indexer(self, keyarr, kind=None):
         # Return our indexer or raise if all of the values are not included in
         # the categories
@@ -631,7 +628,7 @@ def _convert_list_indexer(self, keyarr, kind=None):
 
         return self.get_indexer(keyarr)
 
-    @Appender(_index_shared_docs['_convert_arr_indexer'])
+    @Appender(Index._convert_arr_indexer.__doc__)
     def _convert_arr_indexer(self, keyarr):
         keyarr = com._asarray_tuplesafe(keyarr)
 
@@ -640,11 +637,11 @@ def _convert_arr_indexer(self, keyarr):
 
         return self._shallow_copy(keyarr)
 
-    @Appender(_index_shared_docs['_convert_index_indexer'])
+    @Appender(Index._convert_index_indexer.__doc__)
     def _convert_index_indexer(self, keyarr):
         return self._shallow_copy(keyarr)
 
-    @Appender(_index_shared_docs['take'] % _index_doc_kwargs)
+    @Appender(Index.take.__doc__)
     def take(self, indices, axis=0, allow_fill=True,
              fill_value=None, **kwargs):
         nv.validate_take(tuple(), kwargs)

pandas/core/indexes/datetimelike.py

@@ -44,15 +44,12 @@
 from pandas.errors import NullFrequencyError, PerformanceWarning
 import pandas.io.formats.printing as printing
 
-from pandas.core.indexes.base import Index, _index_shared_docs
+from pandas.core.indexes.base import Index
 from pandas.util._decorators import Appender, cache_readonly
 import pandas.core.dtypes.concat as _concat
 import pandas.tseries.frequencies as frequencies
 from pandas.tseries.offsets import Tick, DateOffset
 
-import pandas.core.indexes.base as ibase
-_index_doc_kwargs = dict(ibase._index_doc_kwargs)
-
 
 class DatelikeOps(object):
     """ common ops for DatetimeIndex/PeriodIndex, but not TimedeltaIndex """
@@ -256,7 +253,7 @@ def _box_values_as_index(self):
     def _format_with_header(self, header, **kwargs):
         return header + list(self._format_native_types(**kwargs))
 
-    @Appender(_index_shared_docs['__contains__'] % _index_doc_kwargs)
+    @Appender(Index.__contains__.__doc__)
     def __contains__(self, key):
         try:
             res = self.get_loc(key)
@@ -400,7 +397,7 @@ def sort_values(self, return_indexer=False, ascending=True):
 
             return self._simple_new(sorted_values, **attribs)
 
-    @Appender(_index_shared_docs['take'] % _index_doc_kwargs)
+    @Appender(Index.take.__doc__)
     def take(self, indices, axis=0, allow_fill=True,
              fill_value=None, **kwargs):
         nv.validate_take(tuple(), kwargs)
@@ -953,7 +950,7 @@ def repeat(self, repeats, *args, **kwargs):
         return self._shallow_copy(self.asi8.repeat(repeats),
                                   freq=freq)
 
-    @Appender(_index_shared_docs['where'] % _index_doc_kwargs)
+    @Appender(Index.where.__doc__)
     def where(self, cond, other=None):
         other = _ensure_datetimelike_to_i8(other)
         values = _ensure_datetimelike_to_i8(self)

pandas/core/indexes/datetimes.py

@@ -36,7 +36,7 @@
 from pandas.errors import PerformanceWarning
 from pandas.core.algorithms import checked_add_with_arr
 
-from pandas.core.indexes.base import Index, _index_shared_docs
+from pandas.core.indexes.base import Index
 from pandas.core.indexes.numeric import Int64Index, Float64Index
 import pandas.compat as compat
 from pandas.tseries.frequencies import to_offset, get_period_alias, Resolution
@@ -968,7 +968,7 @@ def _format_native_types(self, na_rep='NaT', date_format=None, **kwargs):
                                                 format=format,
                                                 na_rep=na_rep)
 
-    @Appender(_index_shared_docs['astype'])
+    @Appender(Index.astype.__doc__)
     def astype(self, dtype, copy=True):
         dtype = pandas_dtype(dtype)
         if (is_datetime64_ns_dtype(dtype) and

pandas/core/indexes/interval.py

@@ -24,8 +24,7 @@
     is_integer,
     pandas_dtype)
 from pandas.core.indexes.base import (
-    Index, _ensure_index,
-    default_pprint, _index_shared_docs)
+    Index, _ensure_index, default_pprint)
 
 from pandas._libs import Timestamp, Timedelta
 from pandas._libs.interval import (
@@ -42,12 +41,6 @@
 from pandas.tseries.frequencies import to_offset
 from pandas.tseries.offsets import DateOffset
 
-import pandas.core.indexes.base as ibase
-_index_doc_kwargs = dict(ibase._index_doc_kwargs)
-_index_doc_kwargs.update(
-    dict(klass='IntervalIndex',
-         target_klass='IntervalIndex or list of Intervals'))
-
 
 _VALID_CLOSED = set(['left', 'right', 'both', 'neither'])
 
@@ -302,7 +295,7 @@ def _simple_new(cls, left, right, closed=None, name=None, copy=False,
         result._reset_identity()
         return result
 
-    @Appender(_index_shared_docs['_shallow_copy'])
+    @Appender(Index._shallow_copy.__doc__)
     def _shallow_copy(self, left=None, right=None, **kwargs):
         if left is None:
 
@@ -729,15 +722,15 @@ def __reduce__(self):
         d.update(self._get_attributes_dict())
         return _new_IntervalIndex, (self.__class__, d), None
 
-    @Appender(_index_shared_docs['copy'])
+    @Appender(Index.copy.__doc__)
     def copy(self, deep=False, name=None):
         left = self.left.copy(deep=True) if deep else self.left
         right = self.right.copy(deep=True) if deep else self.right
         name = name if name is not None else self.name
         closed = self.closed
         return type(self).from_arrays(left, right, closed=closed, name=name)
 
-    @Appender(_index_shared_docs['astype'])
+    @Appender(Index.astype.__doc__)
     def astype(self, dtype, copy=True):
         dtype = pandas_dtype(dtype)
         if is_interval_dtype(dtype) and dtype != self.dtype:
@@ -832,7 +825,7 @@ def is_non_overlapping_monotonic(self):
         return bool((self.right[:-1] <= self.left[1:]).all() or
                     (self.left[:-1] >= self.right[1:]).all())
 
-    @Appender(_index_shared_docs['_convert_scalar_indexer'])
+    @Appender(Index._convert_scalar_indexer.__doc__)
     def _convert_scalar_indexer(self, key, kind=None):
         if kind == 'iloc':
             return super(IntervalIndex, self)._convert_scalar_indexer(
@@ -842,7 +835,7 @@ def _convert_scalar_indexer(self, key, kind=None):
     def _maybe_cast_slice_bound(self, label, side, kind):
         return getattr(self, side)._maybe_cast_slice_bound(label, side, kind)
 
-    @Appender(_index_shared_docs['_convert_list_indexer'])
+    @Appender(Index._convert_list_indexer.__doc__)
     def _convert_list_indexer(self, keyarr, kind=None):
         """
         we are passed a list-like indexer. Return the
@@ -1034,7 +1027,7 @@ def get_value(self, series, key):
             loc = self.get_loc(key)
         return series.iloc[loc]
 
-    @Appender(_index_shared_docs['get_indexer'] % _index_doc_kwargs)
+    @Appender(Index.get_indexer.__doc__)
     def get_indexer(self, target, method=None, limit=None, tolerance=None):
 
         self._check_method(method)
@@ -1135,12 +1128,12 @@ def _get_reindexer(self, target):
 
         return np.concatenate(indexer)
 
-    @Appender(_index_shared_docs['get_indexer_non_unique'] % _index_doc_kwargs)
+    @Appender(Index.get_indexer_non_unique.__doc__)
     def get_indexer_non_unique(self, target):
         target = self._maybe_cast_indexed(_ensure_index(target))
         return super(IntervalIndex, self).get_indexer_non_unique(target)
 
-    @Appender(_index_shared_docs['where'])
+    @Appender(Index.where.__doc__)
     def where(self, cond, other=None):
         if other is None:
             other = self._na_value
@@ -1215,7 +1208,7 @@ def _concat_same_dtype(self, to_concat, name):
             raise ValueError(msg)
         return super(IntervalIndex, self)._concat_same_dtype(to_concat, name)
 
-    @Appender(_index_shared_docs['take'] % _index_doc_kwargs)
+    @Appender(Index.take.__doc__)
     def take(self, indices, axis=0, allow_fill=True,
              fill_value=None, **kwargs):
         nv.validate_take(tuple(), kwargs)