Fix failing hhs test and address pandas update in delphi_utils

_delphi_utils_python/delphi_utils/flash_eval/eval_day.py

@@ -147,7 +147,7 @@ def output(evd_ranking, day, lag, signal, logger):
     """
     starter_link = f"{HTML_LINK}{(day+pd.Timedelta(f'{lag}d')).strftime('%Y-%m_%d')}"
     p_text = ""
-    for j, (index, value) in enumerate(evd_ranking.sort_values(ascending=False).iteritems()):
+    for j, (index, value) in enumerate(evd_ranking.sort_values(ascending=False).items()):
         if j < 30:
             start_link = f"{starter_link},{day.strftime('%Y-%m_%d')},{index}"
             p_text += f"\t{start_link}|*{index}*, {'{:.2f}'.format(value)}>\n"

_delphi_utils_python/delphi_utils/geomap.py

@@ -401,9 +401,9 @@ def replace_geocode(
             df.drop("weight", axis=1, inplace=True)
 
         if not date_col is None:
-            df = df.groupby([date_col, new_col]).sum().reset_index()
+            df = df.groupby([date_col, new_col]).sum(numeric_only=True).reset_index()
         else:
-            df = df.groupby([new_col]).sum().reset_index()
+            df = df.groupby([new_col]).sum(numeric_only=True).reset_index()
         return df
 
     def add_population_column(self, data, geocode_type, geocode_col=None, dropna=True):
@@ -501,7 +501,7 @@ def fips_to_megacounty(
         )
         data.set_index([fips_col, date_col], inplace=True)
         data = data.join(mega_data)
-        data = data.reset_index().groupby([date_col, mega_col]).sum()
+        data = data.reset_index().groupby([date_col, mega_col]).sum(numeric_only=True)
         return data.reset_index()
 
     def as_mapper_name(self, geo_type, state="state_id"):

_delphi_utils_python/delphi_utils/validator/dynamic.py

@@ -195,7 +195,7 @@ def replace_first_six(df, start_date):
             start_date = self.params.time_window.start_date)
 
         if not error_df.empty:
-            for index, value in error_df.iteritems():
+            for index, value in error_df.items():
                 report.add_raised_error(
                     ValidationFailure("check_val_missing",
                                       geo_type=geo_type,

_delphi_utils_python/tests/test_export.py

@@ -250,15 +250,15 @@ def test_export_with_null_removal(self):
         """Test that `remove_null_samples = True` removes entries with null samples."""
         _clean_directory(self.TEST_DIR)
 
-        df_with_nulls = self.DF.copy().append(
-            {
+        df_with_nulls = pd.concat(
+            [self.DF.copy(),
+            pd.DataFrame({
                 "geo_id": "66666",
                 "timestamp": datetime(2020, 6, 6),
                 "val": 10,
                 "se": 0.2,
                 "sample_size": pd.NA,
-            },
-            ignore_index=True,
+            }, index = [0])]
         )
 
         create_export_csv(
@@ -283,15 +283,15 @@ def test_export_without_null_removal(self):
         """Test that `remove_null_samples = False` does not remove entries with null samples."""
         _clean_directory(self.TEST_DIR)
 
-        df_with_nulls = self.DF.copy().append(
-            {
+        df_with_nulls = pd.concat(
+            [self.DF.copy(),
+            pd.DataFrame({
                 "geo_id": "66666",
                 "timestamp": datetime(2020, 6, 6),
                 "val": 10,
                 "se": 0.2,
                 "sample_size": pd.NA,
-            },
-            ignore_index=True,
+            }, index = [0])]
         )
 
         create_export_csv(

_delphi_utils_python/tests/test_geomap.py

@@ -196,7 +196,7 @@ def test_load_fips_chngfips_table(self, geomapper):
 
     def test_load_jhu_uid_fips_table(self, geomapper):
         jhu_data = geomapper.get_crosswalk(from_code="jhu_uid", to_code="fips")
-        assert np.allclose(jhu_data.groupby("jhu_uid").sum(), 1.0)
+        assert np.allclose(jhu_data.groupby("jhu_uid").sum(numeric_only=True), 1.0)
 
     def test_load_zip_hrr_table(self, geomapper):
         zip_data = geomapper.get_crosswalk(from_code="zip", to_code="hrr")

_delphi_utils_python/tests/validator/test_dynamic.py

@@ -48,7 +48,7 @@ def test_half_padding(self):
             ref_df, test_df, ref_date, ref_date)
 
         # Check it only takes missing dates - so the last 5 dates
-        assert new_ref_df.time_value.max() == datetime.strptime("2021-01-11",
+        assert new_ref_df.time_value.max().date() == datetime.strptime("2021-01-11",
             "%Y-%m-%d").date()
         assert new_ref_df.shape[0] == 11
         assert new_ref_df["val"].iloc[5] == 2
@@ -71,7 +71,7 @@ def test_full_padding(self):
             ref_df, test_df, ref_date, ref_date)
 
         # Check it only takes missing dates up to the day before the reference
-        assert new_ref_df.time_value.max() == datetime.strptime("2021-01-15",
+        assert new_ref_df.time_value.max().date() == datetime.strptime("2021-01-15",
             "%Y-%m-%d").date()
         assert new_ref_df.shape[0] == 15
         assert new_ref_df["val"].iloc[5] == 2

hhs_hosp/tests/test_run.py

@@ -100,8 +100,8 @@ def test_transform_signal_pop():
         'timestamp': [datetime(year=2020, month=1, day=1)]*2,
         'val': [15., 150.],})
 
-    pa_pop = int(state_pop.loc[state_pop.state_id == "pa", "pop"])
-    wv_pop = int(state_pop.loc[state_pop.state_id == "wv", "pop"])
+    pa_pop = int(state_pop[state_pop.state_id == "pa"]["pop"].iloc[0])
+    wv_pop = int(state_pop[state_pop.state_id == "wv"]["pop"].iloc[0])
     pd.testing.assert_frame_equal(
         transform_signal(
             CONFIRMED_PROP,