Closed
Description
In [1]: import pandas as pd; import numpy as np
In [2]: arr = pd.core.arrays.period_array([2000, 2001], 'D')
In [3]: arr[:1] = ['2001']
---------------------------------------------------------------------------
TypeError Traceback (most recent call last)
<ipython-input-3-907919e36fd9> in <module>()
----> 1 arr[:1] = ['2001']
~/sandbox/pandas/pandas/core/arrays/period.py in __setitem__(self, key, value)
358 # work, since the freq can't be inferred.
359 if is_list_like(value):
--> 360 if len(key) != len(value) and not com.is_bool_indexer(key):
361 msg = ("shape mismatch: value array of length '{}' does not "
362 "match indexing result of length '{}'.")
TypeError: object of type 'slice' has no len()We should be checking that the if key is a slice
is_slice = isinstance(key, slice)
if (not is_slice
and len(key) != len(value)
and not com.is_bool_indexer(key)):
msg = ("shape mismatch: value array of length '{}' does not "
"match indexing result of length '{}'.")
raise ValueError(msg.format(len(key), len(value)))
if not is_slice and len(key) == 0:
returnThen, if they slice length doesn't match with value, NumPy will complain at the end when we do self._data[key] = value.
I've fixed this on my all-in-one branch. To close this issue, we should also add a base extension tests to BaseSetitemTests like
def test_setitem_slice_mismatch_length_raises(self, data):
arr = data[:5]
with pytest.raises(ValueError):
arr[:1] = arr[:2]and a successful one like
def test_setitem_slice_array(self, data):
arr = data[:5].copy()
arr[:5] = data[-5:]
self.assert_extension_array_equal(arr, data[-5:])(those are untested)