More compatibility fixes with new pandas version

.github/workflows/pythonpackage.yml

@@ -9,7 +9,7 @@ jobs:
     strategy:
       matrix:
         os: [ubuntu-latest, macos-latest, windows-latest]
-        python-version: ["3.9", "3.10", "3.11"]
+        python-version: ["3.9", "3.10", "3.11", "3.12"]
 
     steps:
     - uses: actions/checkout@v4

enlopy/analysis.py

@@ -26,9 +26,15 @@ def reshape_timeseries(Load, x='dayofyear', y=None, aggfunc='sum'):
         raise ValueError('Works only with 1D')
 
     if x is not None:
-        a[x] = getattr(a.index, x)
+        if x == 'week':  # For a strange reason pandas moved week accesor to isocalendar
+            a[x] = a.index.isocalendar()['week']
+        else:
+            a[x] = getattr(a.index, x)
     if y is not None:
-        a[y] = getattr(a.index, y)
+        if y == 'week':
+            a[y] = a.index.isocalendar()['week']
+        else:
+            a[y] = getattr(a.index, y)
     a = a.reset_index(drop=True)
 
     return a.pivot_table(index=x, columns=y,

enlopy/plot.py

@@ -89,7 +89,7 @@ def plot_percentiles(Load, x='hour', zz='week', perc_list=[[5, 95], [25, 75], 50
     if ax is None: # Hack for nice jupyter notebook compatibility
         ax=plt.gca()
     a = reshape_timeseries(Load, x=x, y=zz, aggfunc='mean')
-    xx = a.columns.values
+    xx = a.columns.to_list()
 
     # TODO: s 2s 3s instead of percentiles
 

tests/test_analysis.py

@@ -10,6 +10,12 @@ def test_reshape_timeseries():
     assert b.shape == (24,365)
     assert np.isclose(b.sum().sum(), a.sum())
 
+def test_reshape_timeseries_week():
+    a = np.random.rand(8760)
+    b = reshape_timeseries(a, x='hour', y='week', aggfunc='mean')
+    assert b.shape == (52,24)
+    assert np.isclose(b.mean().mean(), a.mean(),0.001)
+
 def test_reshape_multiannual():
     a = np.random.rand(8760*2)
     a = make_timeseries(a, year=2019, freq='h')

tests/test_generate.py

@@ -82,7 +82,7 @@ def test_disag_daily_to_hourly(self):
         x = np.arange(0, 365)
         y = (np.cos(2 * np.pi / 364 * x) * 50 + 100)
 
-        y = make_timeseries(y, freq='d')
+        y = make_timeseries(y, freq='D')
 
         disag_profile = np.random.rand(24)
         y_disag = disag_upsample(y, disag_profile)

tests/test_utils.py

@@ -20,7 +20,7 @@ def test_ndarray_15m(self):
 
     def test_ndarray_x(self):
         a = np.random.rand(8730)
-        b = make_timeseries(a, freq='H')
+        b = make_timeseries(a, freq='h')
         assert isinstance(b, pd.Series)
         assert sum(a) == sum(b)
 
@@ -47,11 +47,11 @@ def test_2d_ndarray(self):
 
     def test_empty_frame(self):
         a = np.array([])
-        b = make_timeseries(a, freq='H')
+        b = make_timeseries(a, freq='h')
         assert type(b) == pd.Series and len(b)==0
 
     def test_empty_frame_to_indexed_empty(self):
-        b = make_timeseries(freq='H', length=8760)
+        b = make_timeseries(freq='h', length=8760)
         assert isinstance(b, pd.Series) and len(b) == 8760
 
     def test_multiannual_timeseries(self):