def loc(self):
"""
Access a group of rows by label(s) or a boolean array.
``.loc[]`` is primarily label based, but may also be used with a
boolean array.
If the selection result is a DataFrame or Series, Woodwork typing
information will be initialized for the returned object when possible.
Allowed inputs are:
A single label, e.g. ``5`` or ``'a'``, (note that ``5`` is
interpreted as a *label* of the index, and **never** as an
integer position along the index).
A list or array of labels, e.g. ``['a', 'b', 'c']``.
A slice object with labels, e.g. ``'a':'f'``.
A boolean array of the same length as the axis being sliced,
e.g. ``[True, False, True]``.
An alignable boolean Series. The index of the key will be aligned before
masking.
An alignable Index. The Index of the returned selection will be the input.
A ``callable`` function with one argument (the calling Series or
DataFrame) and that returns valid output for indexing (one of the above)
"""
if self._schema is None:
_raise_init_error()
return _locIndexer(self._dataframe)
def test_locIndexer_class(sample_df):
sample_df.ww.init()
ind = _locIndexer(sample_df)
pd.testing.assert_frame_equal(to_pandas(ind.data), to_pandas(sample_df))
pd.testing.assert_frame_equal(to_pandas(ind[1:2]), to_pandas(sample_df.loc[1:2]))
single_val = ind[0, 'id']
if dd and isinstance(single_val, dd.Series):
# Dask returns a series - convert to pandas to check the value
single_val = single_val.compute()
assert len(single_val) == 1
single_val = single_val.loc[0]
assert single_val == 0