added geospatial data for slocog

project_list/_specific_list_utils.py

@@ -40,42 +40,3 @@ def find_keywords(df, columns_to_search: list, keywords_search: list):
 
     return df2
 
-def filter_cordon(
-    df, columns_to_search: list, keywords_search: list, save_to_gcs: bool = True):
-
-    # Filter out for Cordon
-    df = find_keywords(df, columns_to_search, keywords_search)
-    df2 = (df[(df.lower_case_project_title_keyword_search != "keyword not found")| (df.lower_case_project_description_keyword_search != "keyword not found")]).reset_index(drop=True)
-
-    # Delete out non HOV projects that were accidentally picked up
-    projects_to_delete = [
-        "SR 17 Corridor Congestion Relief in Los Gatos",
-        "Interstate 380 Congestion Improvements",
-    ]
-    df2 = df2[~df2.project_title.isin(projects_to_delete)].reset_index(drop=True)
-
-    # Change cases
-    for i in ['project_title','project_description']:
-        df2[i] = df2[i].str.title()
-
-    # Drop invalid geometries
-    # gdf = df2[~df2.geometry.is_empty].reset_index(drop=True)
-    gdf = df[df.geometry.is_valid].reset_index(drop=True)
-
-    gdf = gdf.set_geometry("geometry")
-    gdf = gdf.fillna(gdf.dtypes.replace({"float64": 0.0, "object": "None"}))
-
-    # One version that's a df
-    columns_to_drop = ["lower_case_project_title", "lower_case_project_description"]
-    df2 = df2.drop(columns=columns_to_drop + ["geometry"])
-    df2 = df2.fillna(df.dtypes.replace({"float64": 0.0, "object": "None"}))
-
-    if save_to_gcs:
-        df2.to_excel(
-            f"{harmonization_utils.GCS_FILE_PATH}LRTP/congestion_pricing_sample.xlsx",
-            sheet_name="Sheet_name_1",
-            index=False,
-        )
-        gdf.to_file("./congestion_pricing_sample.geojson", driver="GeoJSON")
-
-    return gdf, df2