Fix several deprecation warnings in pandas 2.1 which became actual errors in 2.2. Also updated several test cases to use iloc when comparing results.

Author: bixbyr

AUTHORS.rst

@@ -29,3 +29,4 @@ Contributions
 - `Anton Ian Sipos <https://github.com/aisipos>`_
 - `Chuan-Jhe Hwong <https://github.com/CJHwong>`_
 - `Thomas Grainger <https://github.com/graingert/>`_
+- `Ryan Smith <https://github.com/bixbyr/>`_

django_pandas/io.py

@@ -84,7 +84,7 @@ def read_frame(qs, fieldnames=(), index_col=None, coerce_float=False,
     """
 
     if fieldnames:
-        fieldnames = pd.unique(fieldnames)
+        fieldnames = pd.unique(pd.Series(fieldnames))
         if index_col is not None and index_col not in fieldnames:
             # Add it to the field names if not already there
             fieldnames = tuple(fieldnames) + (index_col,)

django_pandas/tests/test_manager.py

@@ -87,9 +87,9 @@ def setUp(self):
                                                        col4=cols['col4']))
         WideTimeSeriesDateField.objects.bulk_create(create_list)
 
-        create_list = [LongTimeSeries(date_ix=r[0], series_name=r[1][0],
-                                      value=r[1][1])
-                       for r in self.ts2.iterrows()]
+        create_list = [LongTimeSeries(date_ix=timestamp, series_name=s.iloc[0],
+                                      value=s.iloc[1])
+                       for timestamp, s in self.ts2.iterrows()]
 
         LongTimeSeries.objects.bulk_create(create_list)
 
@@ -222,11 +222,10 @@ def setUp(self):
                                   'value_col_d': np.random.randn(11),
                                   'value_col_e': np.random.randn(11),
                                   'value_col_f': np.random.randn(11)})
-
-        create_list = [PivotData(row_col_a=r[1][0], row_col_b=r[1][1],
-                                 row_col_c=r[1][2], value_col_d=r[1][3],
-                                 value_col_e=r[1][4], value_col_f=r[1][5])
-                       for r in self.data.iterrows()]
+        create_list = [PivotData(row_col_a=r.iloc[0], row_col_b=r.iloc[1],
+                                 row_col_c=r.iloc[2], value_col_d=r.iloc[3],
+                                 value_col_e=r.iloc[4], value_col_f=r.iloc[5])
+                       for _, r in self.data.iterrows()]
 
         PivotData.objects.bulk_create(create_list)
 

django_pandas/utils.py

@@ -48,8 +48,7 @@ def get_cache_key_from_pk(pk):
 
     def inner(pk_series):
         pk_series = pk_series.astype(object).where(pk_series.notnull(), None)
-        cache_keys = pk_series.apply(
-            get_cache_key_from_pk, convert_dtype=False)
+        cache_keys = pk_series.apply(get_cache_key_from_pk)
         unique_cache_keys = list(filter(None, cache_keys.unique()))
 
         if not unique_cache_keys: