Avoid FutureWarnings from actual pandas version

Author: uvchik

windpowerlib/wake_losses.py

@@ -121,7 +121,7 @@ def get_wind_efficiency_curve(curve_name='all'):
         curve_names = curve_name
 
     efficiency_curve = pd.DataFrame(columns=pd.MultiIndex(levels=[[], []],
-                                                          labels=[[], []]))
+                                                          codes=[[], []]))
 
     for curve_name in curve_names:
         if curve_name.split('_')[0] not in ['dena', 'knorr']:

windpowerlib/wind_farm.py

@@ -264,13 +264,14 @@ def assign_power_curve(self, wake_losses_model='power_efficiency_curve',
                     power_curve = pd.concat(
                         [pd.DataFrame(data={
                             'value': [0.0], 'wind_speed': [0.0]}),
-                         power_curve])
+                         power_curve], sort=True)
                 if power_curve.iloc[-1]['value'] != 0.0:
                     power_curve = pd.concat(
                         [power_curve, pd.DataFrame(data={
                             'value': [0.0], 'wind_speed': [
                                 power_curve['wind_speed'].loc[
-                                    power_curve.index[-1]] + 0.5]})])
+                                    power_curve.index[-1]] + 0.5]})],
+                        sort=True)
             # Add power curves of all turbine types to data frame
             # (multiplied by turbine amount)
             df = pd.concat(