Tz-aware datetime.datetime cannot be converted to datetime64 unless utc=True

[DeshanLokuge]

I tied to run the following query using the fred api:
params = {'limit': 100, 'tag_names': 'daily'}
res = fr.tag.series('daily', params = params)

The objective was to get the set economic data series as a datafrane where the frequency of the data was 'daily'

But it gave an error as follows:

**ValueError Traceback (most recent call last)
/usr/local/lib/python3.6/dist-packages/pandas/core/arrays/datetimes.py in objects_to_datetime64ns(data, dayfirst, yearfirst, utc, errors, require_iso8601, allow_object)
1860 try:
-> 1861 values, tz_parsed = conversion.datetime_to_datetime64(data)
1862 # If tzaware, these values represent unix timestamps, so we

pandas/_libs/tslibs/conversion.pyx in pandas._libs.tslibs.conversion.datetime_to_datetime64()

ValueError: Array must be all same time zone

During handling of the above exception, another exception occurred:

ValueError Traceback (most recent call last)
16 frames
/usr/local/lib/python3.6/dist-packages/pandas/core/arrays/datetimes.py in objects_to_datetime64ns(data, dayfirst, yearfirst, utc, errors, require_iso8601, allow_object)
1855 dayfirst=dayfirst,
1856 yearfirst=yearfirst,
-> 1857 require_iso8601=require_iso8601
1858 )
1859 except ValueError as e:

pandas/_libs/tslib.pyx in pandas._libs.tslib.array_to_datetime()

pandas/_libs/tslib.pyx in pandas._libs.tslib.array_to_datetime()

ValueError: Tz-aware datetime.datetime cannot be converted to datetime64 unless utc=True**

I am doubting whether this is a pandas issue or something else.
I would appreciate a fix for this issue or any directions to get the afore mentioned data series of interest.

Thank you in advance,
Kind Regards,
Deshan Lokuge