BUG: read_pickle omit timezone when reading old pickle

[Itayazolay]

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Reproducible Example

# In python 3.7, pandas==0.24.2
pd.to_pickle(pd.Timestamp('2023-01-01', tz='UTC'), '/tmp/ts.p')

# In python 3.10, pandas==2.0.3
pd.read_pickle('/tmp/ts.p')  # Timestamp('2023-01-01 00:00:00') - no timezone information

Issue Description

Reading pickle from previous version doesn't keep timezone information

Expected Behavior

timestamps should be deserialized with timezone information

Installed Versions

3.7:

INSTALLED VERSIONS

commit: None
python: 3.7.12.final.0
python-bits: 64
OS: Linux
OS-release: 6.2.0-26-generic
machine: x86_64
processor: x86_64
byteorder: little
LC_ALL: None
LANG: en_US.UTF-8
LOCALE: en_US.UTF-8

pandas: 0.24.2
pytest: 7.4.0
pip: 22.0.4
setuptools: 67.5.1
Cython: None
numpy: 1.17.0
scipy: 1.2.1
pyarrow: 2.0.0
xarray: 0.14.1
IPython: 7.32.0
sphinx: None
patsy: 0.5.2
dateutil: 2.8.2
pytz: 2022.1
blosc: None
bottleneck: None
tables: 3.6.1
numexpr: 2.7.0
feather: None
matplotlib: 3.3.2
openpyxl: 3.0.9
xlrd: 1.2.0
xlwt: None
xlsxwriter: None
lxml.etree: 4.8.0
bs4: 4.10.0
html5lib: 1.1
sqlalchemy: 0.7.10
pymysql: None
psycopg2: None
jinja2: 3.0.3
s3fs: None
fastparquet: None
pandas_gbq: 0.13.2
pandas_datareader: None
gcsfs: 0.7.1

3.10:

INSTALLED VERSIONS ------------------ commit : 37ea63d python : 3.10.11.final.0 python-bits : 64 OS : Linux OS-release : 6.2.0-26-generic Version : #26~22.04.1-Ubuntu SMP PREEMPT_DYNAMIC Thu Jul 13 16:27:29 UTC 2 machine : x86_64 processor : x86_64 byteorder : little LC_ALL : None LANG : en_US.UTF-8 LOCALE : en_US.UTF-8 pandas : 2.0.1 numpy : 1.25.2 pytz : 2023.3 dateutil : 2.8.2 setuptools : 57.5.0 pip : 22.3.1 Cython : 0.29.36 pytest : 7.3.1 hypothesis : None sphinx : None blosc : None feather : None xlsxwriter : 3.1.2 lxml.etree : 4.9.3 html5lib : None pymysql : None psycopg2 : None jinja2 : 3.1.2 IPython : 8.13.2 pandas_datareader: None bs4 : 4.12.2 bottleneck : 1.3.7 brotli : fastparquet : None fsspec : 2023.6.0 gcsfs : 2023.6.0 matplotlib : 3.7.2 numba : None numexpr : 2.8.4 odfpy : None openpyxl : 3.1.2 pandas_gbq : 0.17.9 pyarrow : 9.0.0 pyreadstat : None pyxlsb : 1.0.10 s3fs : None scipy : 1.10.1 snappy : sqlalchemy : None tables : 3.8.0 tabulate : None xarray : 2023.6.0 xlrd : 2.0.1 zstandard : 0.21.0 tzdata : 2023.3 qtpy : None pyqt5 : None

[twoertwein]

This might be a pandas version incompatibility (0.24.2 vs. 2.0.3)? I don't know how far pandas aims to be backward compatible, but 0.24.2 seems rather old.

[mroeschke]

I don't believe pandas guarantees backward compatibility for pickles that old unfortunately so closing