Adds TimeTable and Catalog conversion to Pandas DataFrames

[jeandet]

This does a simple conversion to Pandas DataFrames for TT and Catalogs. Note that Catalogs as defined in Speasy doesn't force Events to always have the same meta-data, this leads to a DataFrame where columns are the union of all Events meta-data plus as usual start_time and stop_time.

Closes #35

[codecov[bot]]

Codecov Report

Merging #36 (4645ff6) into main (038c88a) will decrease coverage by 1.41%. The diff coverage is 100.00%.

@@            Coverage Diff             @@
##             main      #36      +/-   ##
==========================================
- Coverage   87.10%   85.69%   -1.42%     
==========================================
  Files          31       31              
  Lines        1474     1489      +15     
  Branches      248      252       +4     
==========================================
- Hits         1284     1276       -8     
- Misses        127      150      +23     
  Partials       63       63              

Flag	Coverage Δ
unittests	85.69% <100.00%> (-1.42%)	:arrow_down:

Flags with carried forward coverage won't be shown. Click here to find out more.

Impacted Files	Coverage Δ
speasy/webservices/amda/ws.py	86.39% <ø> (-2.05%)	:arrow_down:
speasy/products/catalog.py	96.07% <100.00%> (+1.20%)	:arrow_up:
speasy/products/timetable.py	96.87% <100.00%> (+0.32%)	:arrow_up:
speasy/webservices/amda/_impl.py	72.04% <0.00%> (-13.98%)	:arrow_down:
speasy/webservices/amda/rest_client.py	75.55% <0.00%> (-6.67%)	:arrow_down:
speasy/core/__init__.py	95.00% <0.00%> (-2.50%)	:arrow_down:

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