Update requirements.txt

CHANGELOG.md

@@ -36,7 +36,8 @@ Here is a template for new release sections
 - Moved `main()` from `Offgridders.py` to new file `src/cli.py` (#150)
 - Enable benchmark tests for Offgridders: Add optional argument `input_file` to `main()` (#150)
 - Added `GENSET_HOURS_OF_OPERATION` in `C1.overall_results_title` (#153)
-
+- Updated 'requirements.txt' (#164, #167)
+- Fix deprecation warnings for pandas (#167)
 ### Removed
 -
 

requirements.txt

@@ -1,10 +1,10 @@
-matplotlib==3.0.0
 oemof.network==0.4.0rc0
 oemof.solph==0.4.1
 oemof.tools==0.4.0
-pandas==0.23.4
-pip==21.1
+pandas>=1.4.1
 Pyomo==5.7.0
 scipy==1.4.1
 xlrd==1.2.0
 xlsxwriter==1.2.7
+matplotlib
+numpy==1.19.4

src/A1_general_functions.py

@@ -3,6 +3,7 @@
 """
 
 import pandas as pd
+import numpy as np
 from src.constants import (
     CAPACITY_PV_KWP,
     CAPACITY_WIND_KW,
@@ -103,39 +104,33 @@ def store_result_matrix(overall_results, experiment, oemof_results):
 
     """
     round_to_comma = 5
-    result_series = pd.Series()
+    result_series = pd.Series(dtype=np.float64)
 
     for key in overall_results.columns.values:
         # Check if called value is in oemof results -> Remember: check if pandas index has certain index: pd.object.index.contains(key)
         if key in oemof_results:
             if isinstance(oemof_results[key], str):
-                result_series = result_series.append(
-                    pd.Series([oemof_results[key]], index=[key])
-                )
+                result_series = pd.concat([result_series, pd.Series([oemof_results[key]], index=[key])])
             else:
-                result_series = result_series.append(
-                    pd.Series([round(oemof_results[key], round_to_comma)], index=[key])
-                )
+                result_series = pd.concat([result_series, pd.Series([round(oemof_results[key], round_to_comma)], index=[key])])
         # extend by item of demand profile
         elif key == DEMAND_PROFILE:
-            result_series = result_series.append(
+            result_series = pd.concat([result_series,
                 pd.Series([experiment[key]], index=[key])
-            )
+            ])
         # Check if called value is a parameter of sensitivity_experiment_s
         elif key in experiment:
             if isinstance(experiment[key], str):
-                result_series = result_series.append(
+                result_series = pd.concat([result_series,
                     pd.Series([experiment[key]], index=[key])
-                )
+                ])
             else:
-                result_series = result_series.append(
+                result_series = pd.concat([result_series,
                     pd.Series([round(experiment[key], round_to_comma)], index=[key])
-                )
+                ])
 
     result_series = result_series.reindex(overall_results.columns, fill_value=None)
 
-    overall_results = overall_results.append(
-        pd.Series(result_series), ignore_index=True
-    )
+    overall_results = pd.concat([overall_results, result_series.to_frame().T], ignore_index=True)
 
     return overall_results

src/D0_process_input.py

@@ -615,4 +615,4 @@ def randomized(white_noise_percentage, data_subframe):
     for i in range(0, len(data_subframe)):
         if data_subframe[i] != 0:
             data_subframe[i] = data_subframe[i] * (1 - noise[i])
-    return data_subframe.clip_lower(0)  # do not allow values <0
+    return data_subframe.clip(lower=0)  # do not allow values <0

src/G2b_constraints_custom.py

@@ -233,7 +233,7 @@ def backup_test(case_dict, oemof_results, experiment, e_flows_df):
                 ],
                 index=demand_profile.index,
             )
-            ratio_below_zero = ratio.clip_upper(0)
+            ratio_below_zero = ratio.clip(upper=0)
             test_warning(ratio_below_zero, oemof_results, boolean_test)
     else:
         pass
@@ -419,7 +419,7 @@ def hybrid_test(case_dict, oemof_results, experiment, e_flows_df):
                 ],
                 index=demand_profile.index,
             )
-            ratio_below_zero = ratio.clip_upper(0)
+            ratio_below_zero = ratio.clip(upper=0)
             test_warning(ratio_below_zero, oemof_results, boolean_test)
 
     else:
@@ -534,7 +534,7 @@ def usage_test(case_dict, oemof_results, experiment, e_flows_df):
                 ],
                 index=demand_profile.index,
             )
-            ratio_below_zero = ratio.clip_upper(0)
+            ratio_below_zero = ratio.clip(upper=0)
             test_warning(ratio_below_zero, oemof_results, boolean_test)
     else:
         pass