chore: include statewide total in county summary

agrc · Oct 31, 2024 · a917787 · a917787
1 parent 0d0b910
commit a917787
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Showing 2 changed files with 15 additions and 7 deletions.
diff --git a/src/wmrc/yearly.py b/src/wmrc/yearly.py
@@ -57,6 +57,10 @@ def county_summaries(year_df: pd.DataFrame, county_fields: list[str]) -> pd.Data
     counties_df["county_wide_msw_composted"] = composted_df.sum()
     counties_df["county_wide_msw_digested"] = digested_df.sum()
     counties_df["county_wide_msw_landfilled"] = landfilled_df.sum()
+    statewide = counties_df.sum()
+    statewide.name = "Statewide"
+    counties_df = pd.concat([counties_df, pd.DataFrame(statewide).T], axis=0)
+
     counties_df["county_wide_msw_diverted_total"] = (
         counties_df["county_wide_msw_recycled"]
         + counties_df["county_wide_msw_composted"]

diff --git a/tests/test_yearly.py b/tests/test_yearly.py
@@ -20,14 +20,18 @@ def test_county_wide_metrics_happy_path(self):
 
         expected_output = pd.DataFrame(
             {
-                "county_wide_msw_recycled": [7.5, 7.5],
-                "county_wide_msw_composted": [12.5, 12.5],
-                "county_wide_msw_digested": [2.5, 2.5],
-                "county_wide_msw_landfilled": [55.0, 55.0],
-                "county_wide_msw_diverted_total": [22.5, 22.5],
-                "county_wide_msw_recycling_rate": [22.5 / (22.5 + 55.0) * 100, 22.5 / (22.5 + 55.0) * 100],
+                "county_wide_msw_recycled": [7.5, 7.5, 15.0],
+                "county_wide_msw_composted": [12.5, 12.5, 25.0],
+                "county_wide_msw_digested": [2.5, 2.5, 5.0],
+                "county_wide_msw_landfilled": [55.0, 55.0, 110.0],
+                "county_wide_msw_diverted_total": [22.5, 22.5, 45.0],
+                "county_wide_msw_recycling_rate": [
+                    22.5 / (22.5 + 55.0) * 100,
+                    22.5 / (22.5 + 55.0) * 100,
+                    45.0 / (45.0 + 110.0) * 100,
+                ],
             },
-            index=["Cache_County__c", "Utah_County__c"],
+            index=["Cache_County__c", "Utah_County__c", "Statewide"],
         )
 
         output = yearly.county_summaries(facility_year_df, ["Cache_County__c", "Utah_County__c"])