Fix tests which broke in pandas 2.2.0 because makeTimeDataFrame was a non-public method which was removed. This was done by just taking the parts we needed. Also fixed a couple formatting issues which violate python style guides.

Author: bixbyr

django_pandas/io.py

@@ -151,7 +151,7 @@ def read_frame(qs, fieldnames=(), index_col=None, coerce_float=False,
         df.set_index(index_col, inplace=True)
 
     if datetime_index:
-        df.index = pd.to_datetime(df.index, errors="ignore")
+        df.index = pd.to_datetime(df.index)
     return df
 
 

django_pandas/managers.py

@@ -241,9 +241,9 @@ def to_timeseries(self, fieldnames=(), verbose=True,
 
         if freq is not None:
             if agg_kwargs is None:
-                agg_kwargs=dict()
+                agg_kwargs = dict()
             if agg_args is None:
-                agg_args=[]
+                agg_args = []
             df = df.resample(freq, **rs_kwargs).agg(*agg_args, **agg_kwargs)
 
         return df
@@ -253,7 +253,7 @@ def to_dataframe(self, fieldnames=(), verbose=True, index=None,
         """
         Returns a DataFrame from the queryset
 
-        Paramaters
+        Parameters
         -----------
 
         fieldnames:  The model field names(columns) to utilise in creating

django_pandas/tests/test_manager.py

@@ -1,8 +1,12 @@
+from datetime import datetime
+
 from django.test import TestCase
 import pandas as pd
 import numpy as np
 import pickle
 import django
+from pandas.core.indexes.datetimes import bdate_range
+
 from .models import (
     DataFrame, WideTimeSeries, WideTimeSeriesDateField,
     LongTimeSeries, PivotData, Dude, Car, Spot
@@ -68,8 +72,28 @@ def unpivot(self, frame):
                 'date': np.tile(np.array(frame.index), K)}
         return pd.DataFrame(data, columns=['date', 'variable', 'value'])
 
+    def _makeTimeDataFrame(self, n_rows: int) -> pd.DataFrame:
+        # Beginning in 2.2 pandas._testing.makeTimeDataFrame was removed, however all that is required for the tests
+        # in this module is a dataframe with columns A, B, C, D of random values indexed by a DatetimeIndex.
+        data = {}
+        for c in ['A', 'B', 'C', 'D']:
+            dt = datetime(2000, 1, 1)
+            dr = bdate_range(dt, periods=n_rows, freq='B', name=c)
+            pd.DatetimeIndex(dr, name=c)
+
+            data[c] = pd.Series(
+                np.random.default_rng(2).standard_normal(n_rows),
+                index=pd.DatetimeIndex(dr, name=c),
+                name=c,
+            )
+        return pd.DataFrame(data)
+
     def setUp(self):
-        self.ts = tm.makeTimeDataFrame(100)
+        if PANDAS_VERSIONINFO >= '2.2.0':
+            self.ts = self._makeTimeDataFrame(100)
+        else:
+            self.ts = tm.makeTimeDataFrame(100)
+
         self.ts2 = self.unpivot(self.ts).set_index('date')
         self.ts.columns = ['col1', 'col2', 'col3', 'col4']
         create_list = []
@@ -125,18 +149,24 @@ def test_longstorage(self):
 
     def test_resampling(self):
         qs = LongTimeSeries.objects.all()
-        rs_kwargs = {'kind': 'period'}
         agg_args = None
         agg_kwargs = None
         if PANDAS_VERSIONINFO >= '0.25.0':
             agg_kwargs = {'func': 'sum'}
         else:
-            agg_args= ['sum']
+            agg_args = ['sum']
+
+        if PANDAS_VERSIONINFO >= '2.2.0':
+            freq = 'ME'
+        else:
+            freq = 'M'
+
         df = qs.to_timeseries(index='date_ix', pivot_columns='series_name',
                               values='value', storage='long',
-                              freq='M', rs_kwargs=rs_kwargs,
+                              freq=freq,
                               agg_args=agg_args,
                               agg_kwargs=agg_kwargs)
+        df.index = pd.PeriodIndex(df.index)
 
         self.assertEqual([d.month for d in qs.dates('date_ix', 'month')],
                          df.index.month.tolist())
@@ -147,9 +177,10 @@ def test_resampling(self):
         qs2 = WideTimeSeries.objects.all()
 
         df1 = qs2.to_timeseries(index='date_ix', storage='wide',
-                                freq='M', rs_kwargs=rs_kwargs,
+                                freq=freq,
                                 agg_args=agg_args,
-                                agg_kwargs = agg_kwargs)
+                                agg_kwargs=agg_kwargs)
+        df1.index = pd.PeriodIndex(df1.index)
 
         self.assertEqual([d.month for d in qs.dates('date_ix', 'month')],
                          df1.index.month.tolist())