REGR: Series.update raises ValueError with tz-aware types

[simonjayhawkins]

• I have checked that this issue has not already been reported.

• I have confirmed this bug exists on the latest version of pandas.

• (optional) I have confirmed this bug exists on the master branch of pandas.

---

Code Sample, a copy-pastable example

import pandas as pd

print(pd.__version__)

dti = pd.date_range("1/1/2000", periods=3, tz="Europe/London")

a = pd.Series([dti[0], None, dti[2]])
b = pd.Series([None, dti[1], None])
a.update(b)

print(a)

Problem description

on master

1.1.0.dev0+1468.g3cebe3024
Traceback (most recent call last):
  File "C:/Users/simon/test.py", line 10, in <module>
    a.update(b)
  File "c:\users\simon\pandas\pandas\core\series.py", line 2855, in update
    self._mgr = self._mgr.putmask(mask=mask, new=other)
  File "c:\users\simon\pandas\pandas\core\internals\managers.py", line 544, in putmask
    return self.apply(
  File "c:\users\simon\pandas\pandas\core\internals\managers.py", line 397, in apply
    applied = getattr(b, f)(**kwargs)
  File "c:\users\simon\pandas\pandas\core\internals\blocks.py", line 1604, in putmask
    new_values[mask] = new
  File "c:\users\simon\pandas\pandas\core\arrays\datetimelike.py", line 609, in __setitem__
    self._data[key] = value
ValueError: NumPy boolean array indexing assignment cannot assign 3 input values to the 1 output values where the mask is true

regression in #27428

d717ad8 is the first bad commit
commit d717ad8
Author: jbrockmendel jbrockmendel@gmail.com
Date: Tue Jul 23 16:55:40 2019 -0700

CLN/REF: stop allowing iNaT in DatetimeBlock (#27428)

cc @jbrockmendel

Expected Output

on 0.25.3

0.25.3
0   2000-01-01 00:00:00+00:00
1   2000-01-02 00:00:00+00:00
2   2000-01-03 00:00:00+00:00
dtype: datetime64[ns, Europe/London]

Output of pd.show_versions()

[paste the output of pd.show_versions() here leaving a blank line after the details tag]

[simonjayhawkins]

xref #25744 AFAICT this is a regression from 0.25.3 whereas #25744 was already failing on 0.25.3 hence separate issue.

[simonjayhawkins]

fixed in master, xref #33984

>>> import pandas as pd
>>>
>>> print(pd.__version__)
1.1.0.dev0+1482.g18a7e973c
>>>
>>> dti = pd.date_range("1/1/2000", periods=3, tz="Europe/London")
>>>
>>> a = pd.Series([dti[0], None, dti[2]])
>>> b = pd.Series([None, dti[1], None])
>>> a.update(b)
>>>
>>> print(a)
0   2000-01-01 00:00:00+00:00
1   2000-01-02 00:00:00+00:00
2   2000-01-03 00:00:00+00:00
dtype: datetime64[ns, Europe/London]
>>>