Closed
Description
In [17]: a = pd.timedelta_range('2H', periods=4)
In [18]: a <= np.array(a.to_numpy()[0])
---------------------------------------------------------------------------
TypeError Traceback (most recent call last)
<ipython-input-18-e196011a0cff> in <module>
----> 1 a <= np.array(a.to_numpy()[0])
~/sandbox/pandas/pandas/core/indexes/datetimelike.py in wrapper(self, other)
116 other = other._values
117
--> 118 result = op(self._data, maybe_unwrap_index(other))
119 return result
120
~/sandbox/pandas/pandas/core/arrays/timedeltas.py in wrapper(self, other)
78
79 elif not is_list_like(other):
---> 80 return ops.invalid_comparison(self, other, op)
81
82 elif len(other) != len(self):
~/sandbox/pandas/pandas/core/ops.py in invalid_comparison(left, right, op)
1196 else:
1197 raise TypeError("Invalid comparison between dtype={dtype} and {typ}"
-> 1198 .format(dtype=left.dtype, typ=type(right).__name__))
1199 return res_values
1200
TypeError: Invalid comparison between dtype=timedelta64[ns] and ndarray
Works for DatetimeIndex.
Raises a different error for PeriodIndex
In [24]: a = pd.period_range('2000', periods=4)
In [25]: a <= np.array(a.to_numpy()[0])
---------------------------------------------------------------------------
TypeError Traceback (most recent call last)
<ipython-input-25-e196011a0cff> in <module>
----> 1 a <= np.array(a.to_numpy()[0])
~/sandbox/pandas/pandas/core/indexes/datetimelike.py in wrapper(self, other)
116 other = other._values
117
--> 118 result = op(self._data, maybe_unwrap_index(other))
119 return result
120
~/sandbox/pandas/pandas/core/arrays/period.py in wrapper(self, other)
76 result.fill(nat_result)
77 else:
---> 78 other = Period(other, freq=self.freq)
79 result = op(other.ordinal)
80
~/sandbox/pandas/pandas/_libs/tslibs/period.pyx in pandas._libs.tslibs.period.Period.__new__()
2448 ordinal = converted.ordinal
2449
-> 2450 elif is_null_datetimelike(value) or value in nat_strings:
2451 ordinal = NPY_NAT
2452
TypeError: unhashable type: 'numpy.ndarray'
@jbrockmendel would you be interested in looking at this?