diff --git a/hourlize/reeds_to_rev.py b/hourlize/reeds_to_rev.py
index 455d5a306..62e41eb61 100644
--- a/hourlize/reeds_to_rev.py
+++ b/hourlize/reeds_to_rev.py
@@ -650,7 +650,7 @@ def get_retirements_of_preexisting(df_cap_exog, years):
         )
         df_ret_exist = df_cap_exog.copy()
         df_ret_exist["MW"] = df_ret_exist.groupby(["tech", "region"])["MW"].diff()
-        df_ret_exist["MW"].fillna(0, inplace=True)
+        df_ret_exist["MW"] = df_ret_exist["MW"].fillna(0)
         df_ret_exist["MW"] = df_ret_exist["MW"] * -1
     else:
         df_ret_exist = pd.DataFrame()
@@ -2163,7 +2163,7 @@ def run(
             save_outputs(df_sc_out, out_dir_path, tech, reduced_only)
 
         except Exception as e:  # pylint: disable=broad-exception-caught
-            print(f"***Error for {rev_row.tech}...\n{traceback.format_exc()}")
+            print(f"***Error for {rev_row.tech}...")
             raise e
 
     print("Completed reeds_to_rev!")
diff --git a/postprocessing/retail_rate_module/ferc_distadmin.py b/postprocessing/retail_rate_module/ferc_distadmin.py
index e1018cd31..a4221d66c 100644
--- a/postprocessing/retail_rate_module/ferc_distadmin.py
+++ b/postprocessing/retail_rate_module/ferc_distadmin.py
@@ -380,7 +380,7 @@ def get_ferc_costs(
         (dfall.t == 1993) | (dfall.state.isin(['AK','HI']))
         ].index).reset_index(drop=True)
     ### Assign DC to MD (since that's how ReEDS treats it)
-    dfall.state.replace({'DC':'MD'}, inplace=True)
+    dfall['state'] = dfall['state'].replace({'DC':'MD'})
     ### Fill missing states
     dfall.state = dfall.apply(lambda row: missingstates.get(row['Utility Name'],row.state), axis=1)
     ### Add a column for region
@@ -446,7 +446,7 @@ def get_ferc_costs(
         df_extrapolate_dim['t'] = df_extrapolate_dim['index'] + df_loop['t'].max() + 1
 
         df_extrapolate_dim['index'] = numprojyears - df_extrapolate_dim['index']
-        df_extrapolate_dim['index'][df_extrapolate_dim['index'].values < 0] = 0
+        df_extrapolate_dim.loc[df_extrapolate_dim['index'] < 0, 'index'] = 0
 
         # List the years of historical data used for extrapolation
         slopeyears = np.array(df_loop['t'].tail(numslopeyears))
diff --git a/postprocessing/retail_rate_module/retail_rate_calculations.py b/postprocessing/retail_rate_module/retail_rate_calculations.py
index d944b36a5..3e4e45f36 100644
--- a/postprocessing/retail_rate_module/retail_rate_calculations.py
+++ b/postprocessing/retail_rate_module/retail_rate_calculations.py
@@ -876,13 +876,13 @@ def main(run_dir, inputpath='inputs.csv', write=True, verbose=0):
         on=['i', 't'], how='left')
     # Fill in any missing eval_period with the default 20 years
     # This should apply to upgrades only
-    df_gen_capex['eval_period'].fillna(20, inplace=True)
+    df_gen_capex['eval_period'] = df_gen_capex['eval_period'].fillna(20)
     df_gen_capex = df_gen_capex.merge(
         depreciation_sch[['i', 't', 'depreciation_sch']], 
         on=['i', 't'], how='left')
     # Fill in any missing eval_period with the default 20 years
     # This should also apply to upgrades only
-    df_gen_capex['depreciation_sch'].fillna('20', inplace=True)
+    df_gen_capex['depreciation_sch'] = df_gen_capex['depreciation_sch'].fillna('20')
     
 #%% # For historical capital expenditures, we use a pre-calculated result.
     #   The expenditures are based on a EIA-NEMS database of historical capacity 
@@ -919,11 +919,11 @@ def main(run_dir, inputpath='inputs.csv', write=True, verbose=0):
         eval_period_init[['i', 'region', 't', 'eval_period']], 
         on=['i', 'region', 't'], how='left')
     # Fill in any missing eval_period with the default 20 years
-    df_gen_capex_init['eval_period'].fillna(20, inplace=True)
+    df_gen_capex_init['eval_period'] = df_gen_capex_init['eval_period'].fillna(20)
     df_gen_capex_init = df_gen_capex_init.merge(
         dep_sch_init[['i', 'region', 't', 'depreciation_sch']], 
         on=['i', 'region', 't'], how='left')
-    df_gen_capex_init['depreciation_sch'].fillna('20', inplace=True)
+    df_gen_capex_init['depreciation_sch'] = df_gen_capex_init['depreciation_sch'].fillna('20')
 
 #%% # Combine both new and historical capital expenditures
     df_gen_capex = pd.concat(
diff --git a/reeds/input_processing/recf.py b/reeds/input_processing/recf.py
index 0d0fdbdaa..e1c768fcf 100644
--- a/reeds/input_processing/recf.py
+++ b/reeds/input_processing/recf.py
@@ -420,7 +420,7 @@ def main(reeds_path, inputs_case):
     recf = pd.concat(
         [df_windons, df_windofs, df_upv, df_distpv]
         + [df_pvb[pvb_type] for pvb_type in df_pvb],
-        sort=False, axis=1, copy=False)
+        sort=False, axis=1)
     
     ### Downselect RECF data to resource adequacy and weather years
     recf = recf.loc[recf.index.year.isin(resource_adequacy_years)]
@@ -444,7 +444,7 @@ def main(reeds_path, inputs_case):
     
     # Sorting profiles of resources to match the order of the rows in resources
     resources = resources.sort_values(['resource','area'])
-    recf = recf.reindex(labels=resources['resource'].drop_duplicates(), axis=1, copy=False)
+    recf = recf.reindex(labels=resources['resource'].drop_duplicates(), axis=1)
 
     ### Scale up distpv by 1/(1-distloss)
     recf.loc[
diff --git a/reeds/log.py b/reeds/log.py
index ea9a9130a..053511500 100755
--- a/reeds/log.py
+++ b/reeds/log.py
@@ -39,6 +39,10 @@ def flush(self):
         datefmt="%Y-%m-%d %H:%M:%S",
         handlers=[logging.FileHandler(logpath, mode='a'), sh, eh],
     )
+    ### Route warnings.warn() through the logging system at WARNING level.
+    ### Without this they reach the sys.stderr redirect below and get logged as ERROR.
+    logging.captureWarnings(True)
+
     log = logging.getLogger(__name__)
     sys.stdout = StreamToLogger(log, logging.INFO)
     sys.stderr = StreamToLogger(log, logging.ERROR)