Address pandas deprecation warnings (#1995)

* address the many pandas deprecation warnings

* roll back the change from M to ME

looks like ME only exists for pandas 2.2+

* lint

pvlib/inverter.py

@@ -532,9 +532,9 @@ def extract_c(x_d, add):
         p_s0 = solve_quad(a, b, c)
 
         # Add values to dataframe at index d
-        coeffs['a'][d] = a
-        coeffs['p_dc'][d] = p_dc
-        coeffs['p_s0'][d] = p_s0
+        coeffs.loc[d, 'a'] = a
+        coeffs.loc[d, 'p_dc'] = p_dc
+        coeffs.loc[d, 'p_s0'] = p_s0
 
     b_dc0, b_dc1, c1 = extract_c(x_d, coeffs['p_dc'])
     b_s0, b_s1, c2 = extract_c(x_d, coeffs['p_s0'])

pvlib/iotools/solcast.py

@@ -413,14 +413,9 @@ def _solcast2pvlib(data):
     a pandas.DataFrame with the data cast to pvlib's conventions
     """
     # move from period_end to period_middle as per pvlib convention
-    # to support Pandas 0.25 we cast PTXX to XX as ISO8601
-    # durations without days aren't supported:
-    # https://github.com/pandas-dev/pandas/pull/37159\
-    # Can remove once minimum supported Pandas version is >=1.2
-    periods = data.period.str.replace("PT", "").str.replace("M", "m")
 
     data["period_mid"] = pd.to_datetime(
-        data.period_end) - pd.to_timedelta(periods) / 2
+        data.period_end) - pd.to_timedelta(data.period.values) / 2
     data = data.set_index("period_mid").drop(columns=["period_end", "period"])
 
     # rename and convert variables

pvlib/iotools/surfrad.py

@@ -146,7 +146,7 @@ def read_surfrad(filename, map_variables=True):
     metadata['surfrad_version'] = int(metadata_list[-1])
     metadata['tz'] = 'UTC'
 
-    data = pd.read_csv(file_buffer, delim_whitespace=True,
+    data = pd.read_csv(file_buffer, sep=r'\s+',
                        header=None, names=SURFRAD_COLUMNS)
     file_buffer.close()
 

pvlib/tests/iotools/test_sodapro.py

@@ -17,7 +17,8 @@
 testfile_radiation_monthly = DATA_DIR / 'cams_radiation_monthly.csv'
 
 
-index_verbose = pd.date_range('2020-06-01 12', periods=4, freq='1T', tz='UTC')
+index_verbose = pd.date_range('2020-06-01 12', periods=4, freq='1min',
+                              tz='UTC')
 index_monthly = pd.date_range('2020-01-01', periods=4, freq='1M')
 
 

pvlib/tests/test_clearsky.py

@@ -745,7 +745,7 @@ def test__calc_stats(detect_clearsky_helper_data):
 def test_bird():
     """Test Bird/Hulstrom Clearsky Model"""
     times = pd.date_range(start='1/1/2015 0:00', end='12/31/2015 23:00',
-                          freq='H')
+                          freq='h')
     tz = -7  # test timezone
     gmt_tz = pytz.timezone('Etc/GMT%+d' % -(tz))
     times = times.tz_localize(gmt_tz)  # set timezone

pvlib/tests/test_irradiance.py

@@ -27,7 +27,7 @@
 @pytest.fixture
 def times():
     # must include night values
-    return pd.date_range(start='20140624', freq='6H', periods=4,
+    return pd.date_range(start='20140624', freq='6h', periods=4,
                          tz='US/Arizona')
 
 
@@ -349,7 +349,7 @@ def test_perez_driesse_components(irrad_data, ephem_data, dni_et,
 
 
 def test_perez_negative_horizon():
-    times = pd.date_range(start='20190101 11:30:00', freq='1H',
+    times = pd.date_range(start='20190101 11:30:00', freq='1h',
                           periods=5, tz='US/Central')
 
     # Avoid test dependencies on functionality not being tested by hard-coding
@@ -711,7 +711,7 @@ def test_dirint_value():
 
 
 def test_dirint_nans():
-    times = pd.date_range(start='2014-06-24T12-0700', periods=5, freq='6H')
+    times = pd.date_range(start='2014-06-24T12-0700', periods=5, freq='6h')
     ghi = pd.Series([np.nan, 1038.62, 1038.62, 1038.62, 1038.62], index=times)
     zenith = pd.Series([10.567, np.nan, 10.567, 10.567, 10.567], index=times)
     pressure = pd.Series([93193., 93193., np.nan, 93193., 93193.], index=times)
@@ -1226,7 +1226,7 @@ def test_clearsky_index():
     expected = 0.01
     assert_allclose(out, expected, atol=0.001)
     # series
-    times = pd.date_range(start='20180601', periods=2, freq='12H')
+    times = pd.date_range(start='20180601', periods=2, freq='12h')
     ghi_measured = pd.Series([100,  500], index=times)
     ghi_modeled = pd.Series([500, 1000], index=times)
     out = irradiance.clearsky_index(ghi_measured, ghi_modeled)
@@ -1282,7 +1282,7 @@ def test_clearness_index():
     expected = 0.725
     assert_allclose(out, expected, atol=0.001)
     # series
-    times = pd.date_range(start='20180601', periods=2, freq='12H')
+    times = pd.date_range(start='20180601', periods=2, freq='12h')
     ghi = pd.Series([0, 1000], index=times)
     solar_zenith = pd.Series([90, 0], index=times)
     extra_radiation = pd.Series([1360, 1400], index=times)
@@ -1316,7 +1316,7 @@ def test_clearness_index_zenith_independent(airmass_kt):
     expected = 0.443
     assert_allclose(out, expected, atol=0.001)
     # series
-    times = pd.date_range(start='20180601', periods=2, freq='12H')
+    times = pd.date_range(start='20180601', periods=2, freq='12h')
     clearness_index = pd.Series([0, .5], index=times)
     airmass = pd.Series([np.nan, 2], index=times)
     out = irradiance.clearness_index_zenith_independent(clearness_index,
@@ -1327,7 +1327,7 @@ def test_clearness_index_zenith_independent(airmass_kt):
 
 def test_complete_irradiance():
     # Generate dataframe to test on
-    times = pd.date_range('2010-07-05 7:00:00-0700', periods=2, freq='H')
+    times = pd.date_range('2010-07-05 7:00:00-0700', periods=2, freq='h')
     i = pd.DataFrame({'ghi': [372.103976116, 497.087579068],
                       'dhi': [356.543700, 465.44400],
                       'dni': [49.63565561689957, 62.10624908037814]},

pvlib/tests/test_location.py

@@ -74,7 +74,7 @@ def test_location_print_pytz():
 def times():
     return pd.date_range(start='20160101T0600-0700',
                          end='20160101T1800-0700',
-                         freq='3H')
+                         freq='3h')
 
 
 def test_get_clearsky(mocker, times):

pvlib/tests/test_modelchain.py

@@ -268,7 +268,7 @@ def location():
 
 @pytest.fixture
 def weather():
-    times = pd.date_range('20160101 1200-0700', periods=2, freq='6H')
+    times = pd.date_range('20160101 1200-0700', periods=2, freq='6h')
     weather = pd.DataFrame({'ghi': [500, 0], 'dni': [800, 0], 'dhi': [100, 0]},
                            index=times)
     return weather
@@ -350,7 +350,7 @@ def test_with_pvwatts(pvwatts_dc_pvwatts_ac_system, location, weather):
 
 def test_run_model_with_irradiance(sapm_dc_snl_ac_system, location):
     mc = ModelChain(sapm_dc_snl_ac_system, location)
-    times = pd.date_range('20160101 1200-0700', periods=2, freq='6H')
+    times = pd.date_range('20160101 1200-0700', periods=2, freq='6h')
     irradiance = pd.DataFrame({'dni': 900, 'ghi': 600, 'dhi': 150},
                               index=times)
     ac = mc.run_model(irradiance).results.ac
@@ -417,7 +417,7 @@ def test_run_model_from_irradiance_arrays_no_loss(
         spectral_model='no_loss',
         losses_model='no_loss'
     )
-    times = pd.date_range('20160101 1200-0700', periods=2, freq='6H')
+    times = pd.date_range('20160101 1200-0700', periods=2, freq='6h')
     irradiance = pd.DataFrame({'dni': 900, 'ghi': 600, 'dhi': 150},
                               index=times)
     mc_one.run_model(irradiance)
@@ -457,7 +457,7 @@ def test_run_model_from_irradiance_arrays_no_loss_input_type(
         spectral_model='no_loss',
         losses_model='no_loss'
     )
-    times = pd.date_range('20160101 1200-0700', periods=2, freq='6H')
+    times = pd.date_range('20160101 1200-0700', periods=2, freq='6h')
     irradiance = pd.DataFrame({'dni': 900, 'ghi': 600, 'dhi': 150},
                               index=times)
     mc_one.run_model(irradiance)
@@ -487,7 +487,7 @@ def test_ModelChain_invalid_inverter_params_arrays(
 def test_prepare_inputs_multi_weather(
         sapm_dc_snl_ac_system_Array, location, input_type):
     times = pd.date_range(start='20160101 1200-0700',
-                          end='20160101 1800-0700', freq='6H')
+                          end='20160101 1800-0700', freq='6h')
     mc = ModelChain(sapm_dc_snl_ac_system_Array, location)
     weather = pd.DataFrame({'ghi': 1, 'dhi': 1, 'dni': 1},
                            index=times)
@@ -502,7 +502,7 @@ def test_prepare_inputs_multi_weather(
 def test_prepare_inputs_albedo_in_weather(
         sapm_dc_snl_ac_system_Array, location, input_type):
     times = pd.date_range(start='20160101 1200-0700',
-                          end='20160101 1800-0700', freq='6H')
+                          end='20160101 1800-0700', freq='6h')
     mc = ModelChain(sapm_dc_snl_ac_system_Array, location)
     weather = pd.DataFrame({'ghi': 1, 'dhi': 1, 'dni': 1, 'albedo': 0.5},
                            index=times)
@@ -564,14 +564,14 @@ def test_ModelChain_times_error_arrays(sapm_dc_snl_ac_system_Array, location):
     error_str = r"Input DataFrames must have same index\."
     mc = ModelChain(sapm_dc_snl_ac_system_Array, location)
     irradiance = {'ghi': [1, 2], 'dhi': [1, 2], 'dni': [1, 2]}
-    times_one = pd.date_range(start='1/1/2020', freq='6H', periods=2)
-    times_two = pd.date_range(start='1/1/2020 00:15', freq='6H', periods=2)
+    times_one = pd.date_range(start='1/1/2020', freq='6h', periods=2)
+    times_two = pd.date_range(start='1/1/2020 00:15', freq='6h', periods=2)
     weather_one = pd.DataFrame(irradiance, index=times_one)
     weather_two = pd.DataFrame(irradiance, index=times_two)
     with pytest.raises(ValueError, match=error_str):
         mc.prepare_inputs((weather_one, weather_two))
     # test with overlapping, but differently sized indices.
-    times_three = pd.date_range(start='1/1/2020', freq='6H', periods=3)
+    times_three = pd.date_range(start='1/1/2020', freq='6h', periods=3)
     irradiance_three = irradiance
     irradiance_three['ghi'].append(3)
     irradiance_three['dhi'].append(3)
@@ -588,7 +588,7 @@ def test_ModelChain_times_arrays(sapm_dc_snl_ac_system_Array, location):
     mc = ModelChain(sapm_dc_snl_ac_system_Array, location)
     irradiance_one = {'ghi': [1, 2], 'dhi': [1, 2], 'dni': [1, 2]}
     irradiance_two = {'ghi': [2, 1], 'dhi': [2, 1], 'dni': [2, 1]}
-    times = pd.date_range(start='1/1/2020', freq='6H', periods=2)
+    times = pd.date_range(start='1/1/2020', freq='6h', periods=2)
     weather_one = pd.DataFrame(irradiance_one, index=times)
     weather_two = pd.DataFrame(irradiance_two, index=times)
     mc.prepare_inputs((weather_one, weather_two))
@@ -617,7 +617,7 @@ def test_run_model_arrays_weather(sapm_dc_snl_ac_system_same_arrays,
               'pvwatts': pvwatts_dc_pvwatts_ac_system_arrays}
     mc = ModelChain(system[ac_model], location, aoi_model='no_loss',
                     spectral_model='no_loss')
-    times = pd.date_range('20200101 1200-0700', periods=2, freq='2H')
+    times = pd.date_range('20200101 1200-0700', periods=2, freq='2h')
     weather_one = pd.DataFrame({'dni': [900, 800],
                                 'ghi': [600, 500],
                                 'dhi': [150, 100]},
@@ -634,7 +634,7 @@ def test_run_model_arrays_weather(sapm_dc_snl_ac_system_same_arrays,
 def test_run_model_perez(sapm_dc_snl_ac_system, location):
     mc = ModelChain(sapm_dc_snl_ac_system, location,
                     transposition_model='perez')
-    times = pd.date_range('20160101 1200-0700', periods=2, freq='6H')
+    times = pd.date_range('20160101 1200-0700', periods=2, freq='6h')
     irradiance = pd.DataFrame({'dni': 900, 'ghi': 600, 'dhi': 150},
                               index=times)
     ac = mc.run_model(irradiance).results.ac
@@ -648,7 +648,7 @@ def test_run_model_gueymard_perez(sapm_dc_snl_ac_system, location):
     mc = ModelChain(sapm_dc_snl_ac_system, location,
                     airmass_model='gueymard1993',
                     transposition_model='perez')
-    times = pd.date_range('20160101 1200-0700', periods=2, freq='6H')
+    times = pd.date_range('20160101 1200-0700', periods=2, freq='6h')
     irradiance = pd.DataFrame({'dni': 900, 'ghi': 600, 'dhi': 150},
                               index=times)
     ac = mc.run_model(irradiance).results.ac
@@ -812,7 +812,7 @@ def test_prepare_inputs_from_poa_arrays_different_indices(
     mc = ModelChain(sapm_dc_snl_ac_system_Array, location)
     poa = pd.concat([weather, total_irrad], axis=1)
     with pytest.raises(ValueError, match=error_str):
-        mc.prepare_inputs_from_poa((poa, poa.shift(periods=1, freq='6H')))
+        mc.prepare_inputs_from_poa((poa, poa.shift(periods=1, freq='6h')))
 
 
 def test_prepare_inputs_from_poa_arrays_missing_column(
@@ -1078,7 +1078,7 @@ def test_run_model_from_effective_irradiance_arrays_error(
     with pytest.raises(ValueError,
                        match=r"Input DataFrames must have same index\."):
         mc.run_model_from_effective_irradiance(
-            (data, data.shift(periods=1, freq='6H'))
+            (data, data.shift(periods=1, freq='6h'))
         )
 
 
@@ -1790,7 +1790,7 @@ def test_ModelChain_no_extra_kwargs(sapm_dc_snl_ac_system, location):
 def test_basic_chain_alt_az(sam_data, cec_inverter_parameters,
                             sapm_temperature_cs5p_220m):
     times = pd.date_range(start='20160101 1200-0700',
-                          end='20160101 1800-0700', freq='6H')
+                          end='20160101 1800-0700', freq='6h')
     latitude = 32.2
     longitude = -111
     surface_tilt = 0
@@ -1812,7 +1812,7 @@ def test_basic_chain_alt_az(sam_data, cec_inverter_parameters,
 def test_basic_chain_altitude_pressure(sam_data, cec_inverter_parameters,
                                        sapm_temperature_cs5p_220m):
     times = pd.date_range(start='20160101 1200-0700',
-                          end='20160101 1800-0700', freq='6H')
+                          end='20160101 1800-0700', freq='6h')
     latitude = 32.2
     longitude = -111
     altitude = 700
@@ -1847,7 +1847,7 @@ def test_basic_chain_altitude_pressure(sam_data, cec_inverter_parameters,
 def test_complete_irradiance_clean_run(sapm_dc_snl_ac_system, location):
     """The DataFrame should not change if all columns are passed"""
     mc = ModelChain(sapm_dc_snl_ac_system, location)
-    times = pd.date_range('2010-07-05 9:00:00', periods=2, freq='H')
+    times = pd.date_range('2010-07-05 9:00:00', periods=2, freq='h')
     i = pd.DataFrame(
         {'dni': [2, 3], 'dhi': [4, 6], 'ghi': [9, 5]}, index=times)
 
@@ -1864,7 +1864,7 @@ def test_complete_irradiance_clean_run(sapm_dc_snl_ac_system, location):
 def test_complete_irradiance(sapm_dc_snl_ac_system, location, mocker):
     """Check calculations"""
     mc = ModelChain(sapm_dc_snl_ac_system, location)
-    times = pd.date_range('2010-07-05 7:00:00-0700', periods=2, freq='H')
+    times = pd.date_range('2010-07-05 7:00:00-0700', periods=2, freq='h')
     i = pd.DataFrame({'dni': [49.756966, 62.153947],
                       'ghi': [372.103976116, 497.087579068],
                       'dhi': [356.543700, 465.44400]}, index=times)
@@ -1897,7 +1897,7 @@ def test_complete_irradiance_arrays(
         sapm_dc_snl_ac_system_same_arrays, location, input_type):
     """ModelChain.complete_irradiance can accept a tuple of weather
     DataFrames."""
-    times = pd.date_range(start='2020-01-01 0700-0700', periods=2, freq='H')
+    times = pd.date_range(start='2020-01-01 0700-0700', periods=2, freq='h')
     weather = pd.DataFrame({'dni': [2, 3],
                             'dhi': [4, 6],
                             'ghi': [9, 5]}, index=times)
@@ -1932,7 +1932,7 @@ def test_complete_irradiance_arrays(
 def test_complete_irradiance_arrays_wrong_length(
         sapm_dc_snl_ac_system_same_arrays, location, input_type):
     mc = ModelChain(sapm_dc_snl_ac_system_same_arrays, location)
-    times = pd.date_range(start='2020-01-01 0700-0700', periods=2, freq='H')
+    times = pd.date_range(start='2020-01-01 0700-0700', periods=2, freq='h')
     weather = pd.DataFrame({'dni': [2, 3],
                             'dhi': [4, 6],
                             'ghi': [9, 5]}, index=times)