Fix date_col docstring, add None option to date_col, add test for that option

Author: dshemetov

_delphi_utils_python/delphi_utils/geomap.py

@@ -375,6 +375,9 @@ def replace_geocode(
         new_code: {'fips', 'zip', 'state_code', 'state_id', 'state_name', 'hrr', 'msa',
                    'hhs_region_number'}
             Specifies the geocode type of the data in new_col.
+        date_col: str or None, default "date"
+            Specify which column contains the date values. Used for value aggregation.
+            If None, then the aggregation is done only on geo_id.
         data_cols: list, default None
             A list of data column names to aggregate when doing a weighted coding. If set to
             None, then all the columns are used except for date_col and new_col.
@@ -403,7 +406,11 @@ def replace_geocode(
             # Multiply and aggregate (this automatically zeros NAs)
             df[data_cols] = df[data_cols].multiply(df["weight"], axis=0)
             df.drop("weight", axis=1, inplace=True)
-        df = df.groupby([date_col, new_col]).sum().reset_index()
+
+        if not date_col is None:
+            df = df.groupby([date_col, new_col]).sum().reset_index()
+        else:
+            df = df.groupby([new_col]).sum().reset_index()
         return df
 
     def add_population_column(self, data, geocode_type, geocode_col=None):

_delphi_utils_python/tests/test_geomap.py

@@ -439,4 +439,14 @@ def test_add_geocode(self):
         assert not gmpr.add_geocode(self.fips_data_3, "fips", "hrr").isna().any().any()
         assert gmpr.add_geocode(self.fips_data_3, "fips", "hrr", dropna=False).isna().any().any()
 
-TestGeoMapper().test_add_geocode()
+        # fips -> zip (date_col=None chech)
+        new_data = gmpr.replace_geocode(self.fips_data_5.drop(columns=["date"]), "fips", "hrr", date_col=None)
+        assert new_data.equals(
+            pd.DataFrame().from_dict(
+                {
+                    'hrr': {0: '1', 1: '183', 2: '184', 3: '382', 4: '7'},
+                    'count': {0: 1.772347174163783, 1: 7157.392403522299, 2: 2863.607596477701, 3: 1.0, 4: 0.22765282583621685},
+                    'total': {0: 3.544694348327566, 1: 71424.64801363471, 2: 28576.35198636529, 3: 1.0, 4: 0.4553056516724337}
+                }
+            )
+        )