def convert_to_index_sliceable(self, key):
"""Converts and performs error checking on the passed slice
Args:
key: slice to convert and check
"""
return convert_to_index_sliceable(self._coord_df, key)
def __getitem__(self, key):
from pandas.core.dtypes.common import is_list_like, is_integer, is_iterator
key = com.apply_if_callable(key, self)
# shortcut if the key is in columns
try:
if self.columns.is_unique and key in self.columns:
if self.columns.nlevels > 1:
return self._getitem_multilevel(key)
return self._get_item_cache(key)
except (TypeError, ValueError):
# The TypeError correctly catches non hashable "key" (e.g. list)
# The ValueError can be removed once GH #21729 is fixed
pass
# Do we have a slicer (on rows)?
indexer = convert_to_index_sliceable(self, key)
if indexer is not None:
return self._slice(indexer, axis=0)
# Do we have a (boolean) DataFrame?
if isinstance(key, DataFrame):
return self._getitem_frame(key)
# Do we have a (boolean) 1d indexer?
if com.is_bool_indexer(key):
return self._getitem_bool_array(key)
# We are left with two options: a single key, and a collection of keys,
# We interpret tuples as collections only for non-MultiIndex
is_single_key = isinstance(key, tuple) or not is_list_like(key)
if is_single_key:
if self.columns.nlevels > 1:
return self._getitem_multilevel(key)
indexer = self.columns.get_loc(key)
if is_integer(indexer):
indexer = [indexer]
else:
if is_iterator(key):
key = list(key)
# noinspection PyProtectedMember
indexer = self.loc._convert_to_indexer(key, axis=1, raise_missing=True)
# take() does not accept boolean indexers
if getattr(indexer, "dtype", None) == bool:
indexer = np.where(indexer)[0]
data = self._take(indexer, axis=1)
if is_single_key:
# What does looking for a single key in a non-unique index return?
# The behavior is inconsistent. It returns a Series, except when
# - the key itself is repeated (test on data.shape, #9519), or
# - we have a MultiIndex on columns (test on self.columns, #21309)
if data.shape[1] == 1 and not isinstance(self.columns, MultiIndex):
data = data[key]
return data
def __getitem__(self, key):
# noinspection PyProtectedMember
key = com._apply_if_callable(key, self)
# shortcut if we are an actual column
is_mi_columns = isinstance(self.columns, MultiIndex)
# noinspection PyBroadException
try:
if key in self.columns and not is_mi_columns:
self._getitem_column(key)
except:
pass
# see if we can slice the rows
indexer = convert_to_index_sliceable(self, key)
if indexer is not None:
return self._getitem_slice(indexer)
if isinstance(key, (Series, np.ndarray, Index, list)):
# either boolean or fancy integer index
return self._getitem_array(key)
elif isinstance(key, DataFrame):
return self._getitem_frame(key)
elif is_mi_columns:
return self._getitem_multilevel(key)
else:
return self._getitem_column(key)
def __getitem__(self, key):
"""
The rebuilt method of __getitem__, which will redirect the DataFrame and Series to OneData and OneSeries.
"""
key = lib.item_from_zerodim(key)
key = com.apply_if_callable(key, self)
if is_hashable(key):
if self.columns.is_unique and key in self.columns:
if self.columns.nlevels > 1:
return OneSeries(self._getitem_multilevel(key))
return OneSeries(self._get_item_cache(key))
indexer = convert_to_index_sliceable(self, key)
if indexer is not None:
return OneData(self._slice(indexer, axis=0))
if isinstance(key, DataFrame) or isinstance(key, OneData):
return self.where(key)
if com.is_bool_indexer(key):
return OneData(self._getitem_bool_array(key))
is_single_key = isinstance(key, tuple) or not is_list_like(key)
if is_single_key:
if self.columns.nlevels > 1:
return self._getitem_multilevel(key)
indexer = self.columns.get_loc(key)
if is_integer(indexer):
indexer = [indexer]
else:
if is_iterator(key):
key = list(key)
indexer = self.loc._get_listlike_indexer(key,
axis=1,
raise_missing=True)[1]
if getattr(indexer, "dtype", None) == bool:
indexer = np.where(indexer)[0]
data = self._take_with_is_copy(indexer, axis=1)
if is_single_key:
if data.shape[1] == 1 and not isinstance(self.columns,
ABCMultiIndex):
data = data[key]
return OneData(data)