Fix compatibility issue with pandas >=2

[abretaud]

While testing funannotate compare 1.8.15 in a freshly installed conda env, I got this error:

[Apr 25 03:14 PM]: Summarizing fungal transcription factors
[Apr 25 03:14 PM]: Running GO enrichment for each genome
Traceback (most recent call last):
  File "/_conda/envs/__funannotate@1.8.15/lib/python3.8/site-packages/pandas/core/indexes/base.py", line 3652, in get_loc
    return self._engine.get_loc(casted_key)
  File "pandas/_libs/index.pyx", line 147, in pandas._libs.index.IndexEngine.get_loc
  File "pandas/_libs/index.pyx", line 176, in pandas._libs.index.IndexEngine.get_loc
  File "pandas/_libs/hashtable_class_helper.pxi", line 7080, in pandas._libs.hashtable.PyObjectHashTable.get_item
  File "pandas/_libs/hashtable_class_helper.pxi", line 7088, in pandas._libs.hashtable.PyObjectHashTable.get_item
KeyError: 'GO'

The above exception was the direct cause of the following exception:

Traceback (most recent call last):
  File "/_conda/envs/__funannotate@1.8.15/bin/funannotate", line 10, in <module>
    sys.exit(main())
  File "/_conda/envs/__funannotate@1.8.15/lib/python3.8/site-packages/funannotate/funannotate.py", line 716, in main
    mod.main(arguments)
  File "/_conda/envs/__funannotate@1.8.15/lib/python3.8/site-packages/funannotate/compare.py", line 986, in main
    + df2["GO"].astype(str)
  File "/_conda/envs/__funannotate@1.8.15/lib/python3.8/site-packages/pandas/core/frame.py", line 3760, in __getitem__
    indexer = self.columns.get_loc(key)
  File "/_conda/envs/__funannotate@1.8.15/lib/python3.8/site-packages/pandas/core/indexes/base.py", line 3654, in get_loc
    raise KeyError(key) from err
KeyError: 'GO'

After some debugging, I found out that it comes from a breaking change in pandas2

Change the default argument of regex for Series.str.replace() from True to False. Additionally, a single character pat with regex=True is now treated as a regular expression instead of a string literal. (GH36695, GH24804)

Here's a PR that always set the regex param to True, so it should work whatever pandas version is installed