Fold updated growth geographies into codebase

[akselx]

Updated growth geographies have slightly different categories and schema, with some columns no longer provided on this dataset, but instead via the parcels dataset. This PR is to fold those changes into the existing code base, and redirect any orphaned data dependencies (like jurisdiction name) to other sources.

Part 1 involves those core changes, mainly via the datasources.py and variables.py, reading in the new dataframe, and fetching alternatives.

Part 2 relates to the zoning mods, which is currently handled as a separate process in a jupyter notebook. That process uses combinations of geographical area groupings (e.g. transit rich areas, high resource areas, growth geographies) - concatenations captured as zoningmodcat as the main vehicle to apply modifications to zoning.

The script, build_zoningmods_general.py, applies zoning modifications to groups of parcels based on columns denoting membership in subareas. It performs the following functions:

• Loads configuration settings from a specified YAML file (zoning_mods_fbp.yaml ).
• Reads a CSV file containing parcel geography data.
• Constructs a new column, zoningmodcat, by concatenating specified columns that denote subarea membership.
• Groups parcels based on the zoningmodcat column to create a DataFrame template for zoning modifications.
• Applies zoning modifications specified in the YAML configuration to the grouped parcels.
• Adds ancillary columns required for specific purposes if they are missing.
• Saves the modified zoning data to an output CSV file - set in the yaml file.

---

• To see the specific tasks where the Asana app for GitHub is being used, see below:
  • https://app.asana.com/0/0/1209286100278506