Match scalars and timeseries columns

[FelixMau]

There has to be additional functionality to write correct time series names in columns for time series. The current situation is like this:

• Time series columns are named by initial column name (data) + region e.g. _onshoreHH
• Facade instance is parametrized and every parameter of type sequence is tried to get assigned initial column name (facade) + region e.g _profileHH

Although using a similar method, the result is different as different datasets/columns are referenced. This must somehow be unified:

• mapping will be done in GLOBAL_PARAMETER_MAP.yaml in case there are multiple time series for one process
• if there is only one time series available, this one will be taken

There might be cases where more time series are allowed in the facade as there are provided time series.

• [x] If there are scalars with corresponding/mapped name, these are taken first
• [ ] an additional logic needs to be implemented which checks the number of free sequences
• [ ] a warning or error needs to be implemented in cases which are not trivial

Further: process_data.scalar has a row for each region and year, the refactored time series only have one column for each region and all years. This is not a big problem, but needs to be addressed at some point when it will be integrated into tabular.

[FelixMau]

In 0baca0e76669efafd004e850ef8a511594f32ffc I added "year" to scalars. The region is inherently mapped by the profile column since each region should have its own profile. However, I can imagine a scenario where future users may only want scalar data to vary across regions.

[FelixMau]

Timeseries are currently only matched if field type is matching as a Series and if the Series entries are all found within timeseries columns. This approach assures to only write foreign keys for timeseries if there are Series connected to the Dataset with matching naming.

Timeseries are exploded within data_adapter therefore this issue is outdated and the period csv writing will be tackled in #44