Merge pull request #951 from CodeForPhilly/lebovits/issu919-fix-land-…

…bank-props

Lebovits/issu919 fix land bank props

data/src/data_utils/access_process.py

@@ -1,4 +1,20 @@
-def access_process(dataset):
+from typing import Any
+
+def access_process(dataset: Any) -> Any:
+    """
+    Process a dataset to determine the access process for each property based on
+    city ownership and market value. The result is added as a new column in the dataset.
+
+    Args:
+        dataset (Any): The dataset containing a GeoDataFrame named `gdf` with
+                       columns "city_owner_agency" and "market_value".
+
+    Returns:
+        Any: The updated dataset with an additional "access_process" column.
+
+    Side Effects:
+        Prints the distribution of the "access_process" column.
+    """
     access_processes = []
 
     for _, row in dataset.gdf.iterrows():
@@ -9,9 +25,9 @@ def access_process(dataset):
         )
 
         # Simplified decision logic
-        if city_owner_agency == "PLB":
-            access_process = "Land Bank"
-        elif city_owner_agency in ["PRA", "PHDC"]:
+        if city_owner_agency == "Land Bank (PHDC)":
+            access_process = "Go through Land Bank"
+        elif city_owner_agency == "PRA":
             access_process = "Do Nothing"
         else:
             if market_value_over_1000:
@@ -22,4 +38,10 @@ def access_process(dataset):
         access_processes.append(access_process)
 
     dataset.gdf["access_process"] = access_processes
+
+    # Print the distribution of "access_process"
+    distribution = dataset.gdf["access_process"].value_counts()
+    print("Distribution of access process:")
+    print(distribution)
+
     return dataset

data/src/data_utils/city_owned_properties.py

@@ -1,8 +1,21 @@
+from typing import Any
 from classes.featurelayer import FeatureLayer
 from constants.services import CITY_OWNED_PROPERTIES_TO_LOAD
 
+def city_owned_properties(primary_featurelayer: FeatureLayer) -> FeatureLayer:
+    """
+    Processes city-owned property data by joining it with the primary feature layer,
+    renaming columns, and updating access information for properties based on ownership.
+    All instances where the "city_owner_agency" is "PLB" are changed to "Land Bank (PHDC)".
 
-def city_owned_properties(primary_featurelayer):
+    Args:
+        primary_featurelayer (FeatureLayer): The primary feature layer to which city-owned 
+                                             property data will be joined.
+
+    Returns:
+        FeatureLayer: The updated primary feature layer with processed city ownership 
+                      information.
+    """
     city_owned_properties = FeatureLayer(
         name="City Owned Properties",
         esri_rest_urls=CITY_OWNED_PROPERTIES_TO_LOAD,
@@ -60,4 +73,9 @@ def city_owned_properties(primary_featurelayer):
         "side_yard_eligible"
     ].fillna("No")
 
+    # Update all instances where city_owner_agency is "PLB" to "Land Bank (PHDC)"
+    primary_featurelayer.gdf.loc[
+        primary_featurelayer.gdf["city_owner_agency"] == "PLB", "city_owner_agency"
+    ] = "Land Bank (PHDC)"
+
     return primary_featurelayer

data/src/data_utils/conservatorship.py

@@ -44,7 +44,7 @@ def conservatorship(primary_featurelayer):
             sale_date_6_months_ago = False
 
         # Simplified decision logic
-        if city_owner_agency == "PLB" or (
+        if city_owner_agency == "Land Bank (PHDC)" or (
             not sale_date_6_months_ago and market_value_over_1000
         ):
             conservatorship = "No"