Add method / tool to convert set of dataset configs to a pandas dataframe

[benkrikler]

The YAML-based configs that curator handles are intended to contain useful meta-data, that's specific to each dataset. This is currently (to my knowledge) only used in the main processing of the input ROOT trees, however the same meta-data can be useful in later stages, such as dataset-specific scale factors (e.g. a cross section). It would be helpful and relevant to curator if it could convert between the YAML format and a pandas dataframe, possibly containing a subset of fields.

The scope of this issue is first and foremost to extract metadata from the yaml configs, but elsewhere the reverse process has been requested: adding meta-data to the configs using a table / spreadsheet / dataframe. Depending on the implementation, that might be (partially) addressed as well.

[benkrikler]

Some of the functionality this issue was intended to add has been partially included now in fast-plotter from: FAST-HEP/fast-plotter#36. However, improving support for these functions within fast-curator itself could be a useful separation of concepts and responsibilities, so I think this is a valid feature request still.