Update parameter documentation in get_ags_from_geometry function to c…

…larify input type

edisgo/io/electromobility_import.py

@@ -1,17 +1,18 @@
 from __future__ import annotations
 
+import io
 import json
 import logging
 import os
-import io
+import zipfile
 
 from collections import Counter
 from pathlib import Path, PurePath
 from typing import TYPE_CHECKING
-import requests
+
 import numpy as np
 import pandas as pd
-import zipfile
+import requests
 
 from numpy.random import default_rng
 from sklearn import preprocessing
@@ -479,7 +480,7 @@ def assure_minimum_potential_charging_parks(
     potential_charging_parks_gdf = potential_charging_parks_gdf.sort_values(
         by=["use_case", "ags", "user_centric_weight"], ascending=[True, True, False]
     ).reset_index(drop=True)
-    potential_charging_parks_gdf['ags'] = potential_charging_parks_gdf['ags'].fillna(0)
+    potential_charging_parks_gdf["ags"] = potential_charging_parks_gdf["ags"].fillna(0)
     # in case of polygons use the centroid as potential charging parks point
     # and set crs to match edisgo object
     return (
@@ -1080,11 +1081,11 @@ def distribute_public_charging_demand(edisgo_obj, **kwargs):
                 idx, "charging_point_id"
             ] = charging_point_id
 
-            available_charging_points_df.loc[
-                charging_point_id
-            ] = edisgo_obj.electromobility.charging_processes_df.loc[
-                idx, available_charging_points_df.columns
-            ].tolist()
+            available_charging_points_df.loc[charging_point_id] = (
+                edisgo_obj.electromobility.charging_processes_df.loc[
+                    idx, available_charging_points_df.columns
+                ].tolist()
+            )
 
             designated_charging_point_capacity_df.at[
                 charging_park_id, "designated_charging_point_capacity"
@@ -1148,89 +1149,96 @@ def integrate_charging_parks(edisgo_obj):
         index=charging_park_ids,
     )
 
-def get_ags_from_geometry(gdf):
+
+def get_ags_from_geometry(gdf: gpd.GeoDataFrame) -> gpd.GeoDataFrame:
     """
     Get the AGS from a given geometry.
 
     Parameters
     ----------
-    geometry : :shapely:`shapely.geometry`
-        Geometry object
+    gdf : :geopandas:`geopandas.GeoDataFrame`
+        GeoDataFrame with geometry
 
     Returns
     -------
-    :obj:`int`
-        AGS
+    :geopandas:`geopandas.GeoDataFrame`
+        GeoDataFrame with geometry and AGS
 
     """
-    url = "https://daten.gdz.bkg.bund.de/produkte/vg/vg250_ebenen_0101/aktuell/vg250_01-01.utm32s.gpkg.ebenen.zip"
+    url = "https://daten.gdz.bkg.bund.de/produkte/vg/vg250_ebenen_0101/aktuell/vg250_01-01.utm32s.gpkg.ebenen.zip"  # noqa
     r = requests.get(url)
     z = zipfile.ZipFile(io.BytesIO(r.content))
     z.extractall("/tmp/vg250_data")
-    vg250 = gpd.read_file("/tmp/vg250_data/vg250_01-01.utm32s.gpkg.ebenen/vg250_ebenen_0101/DE_VG250.gpkg", layer="vg250_gem")
+    vg250 = gpd.read_file(
+        "/tmp/vg250_data/vg250_01-01.utm32s.gpkg.ebenen/vg250_ebenen_0101/DE_VG250.gpkg",  # noqa
+        layer="vg250_gem",
+    )
     vg250 = vg250.to_crs(gdf.crs)
     gdf = gdf.to_crs(vg250.crs)
-    gdf = gpd.sjoin(gdf, vg250[['geometry', 'AGS']], how="left", predicate="intersects")
+    gdf = gpd.sjoin(gdf, vg250[["geometry", "AGS"]], how="left", predicate="intersects")
     return gdf
 
 
-
-
 def import_electromobility_from_new_data(
     edisgo_obj: EDisGo,
     data_dir: str,
     **kwargs,
 ):
-    """
-    """
-    csv_files = [f for f in os.listdir(data_dir) if f.endswith('.csv')]
-    gpkg_files = [f for f in os.listdir(data_dir) if f.endswith('.gpkg')]
+    """ """
+    gpkg_files = [f for f in os.listdir(data_dir) if f.endswith(".gpkg")]
 
     # Load CSV files into a dictionary
     # csv_data = {f: pd.read_csv(os.path.join(data_dir, f)) for f in csv_files}
 
     # Load GPKG files into a dictionary
     gpkg_data = {f: gpd.read_file(os.path.join(data_dir, f)) for f in gpkg_files}
-    charging_processes_df = [gdf for key, gdf in gpkg_data.items() if 'charging-events' in key]
-    charging_processes_gdf = gpd.GeoDataFrame(pd.concat(charging_processes_df, ignore_index=True))
+    charging_processes_df = [
+        gdf for key, gdf in gpkg_data.items() if "charging-events" in key
+    ]
+    charging_processes_gdf = gpd.GeoDataFrame(
+        pd.concat(charging_processes_df, ignore_index=True)
+    )
     charging_processes_gdf = get_ags_from_geometry(charging_processes_gdf)
     column_mapping = {
-        'energy': 'chargingdemand_kWh',
-        'use_case': 'use_case',
-        'id': 'car_id',
-        'station_charging_capacity': 'nominal_charging_capacity_kW',
-        'assigned_location': 'ags',
-        'charging_use_case': 'destination',
-        'assigned_location': 'charging_park_id',
+        "energy": "chargingdemand_kWh",
+        "use_case": "use_case",
+        "id": "car_id",
+        "station_charging_capacity": "nominal_charging_capacity_kW",
+        "charging_use_case": "destination",
+        "assigned_location": "charging_park_id",
     }
 
-
     charging_processes_gdf = charging_processes_gdf.rename(columns=column_mapping)
-    charging_processes_gdf['charging_point_id'] = charging_processes_gdf.charging_park_id
+    charging_processes_gdf["charging_point_id"] = (
+        charging_processes_gdf.charging_park_id
+    )
     edisgo_obj.electromobility.charging_processes_df = charging_processes_gdf
 
     charging_parks_gdfs = []
     for key, gdf in gpkg_data.items():
-        if 'charging-locations' in key:
+        if "charging-locations" in key:
             # Extrahiere den use_case aus dem Dateinamen
-            use_case = key.split('_')[1]
+            use_case = key.split("_")[1]
             # Füge die Spalte 'use_case' hinzu
-            gdf['use_case'] = use_case
+            gdf["use_case"] = use_case
             charging_parks_gdfs.append(gdf)
-    charging_parks_gdf = gpd.GeoDataFrame(pd.concat(charging_parks_gdfs, ignore_index=True))
+    charging_parks_gdf = gpd.GeoDataFrame(
+        pd.concat(charging_parks_gdfs, ignore_index=True)
+    )
     charging_parks_gdf.geometry = charging_parks_gdf.geometry.centroid
     mapping_charging_parks = {
-        'probability': 'user_centric_weight',
-        'required_points': 'ags',
-        'use_case': 'use_case',
-        'charging_park_id': 'id',
+        "probability": "user_centric_weight",
+        "required_points": "ags",
+        "use_case": "use_case",
+        "charging_park_id": "id",
     }
     charging_parks_gdf = charging_parks_gdf.rename(columns=mapping_charging_parks)
-    edisgo_obj.electromobility.potential_charging_parks_gdf = assure_minimum_potential_charging_parks(
-        edisgo_obj=edisgo_obj,
-        potential_charging_parks_gdf=charging_parks_gdf,
+    edisgo_obj.electromobility.potential_charging_parks_gdf = (
+        assure_minimum_potential_charging_parks(
+            edisgo_obj=edisgo_obj,
+            potential_charging_parks_gdf=charging_parks_gdf,
         )
-    # edisgo_obj.electromobility.potential_charging_parks = edisgo_obj.electromobility.potential_charging_parks_gdf
+    )
 
 
 def import_electromobility_from_oedb(