From 2500bf74f0c9f47afc9e62424fd869292745c221 Mon Sep 17 00:00:00 2001
From: =?UTF-8?q?Patrik=20Sch=C3=B6nfeldt?= <patrik@proxima.snft.de>
Date: Thu, 27 Jun 2024 13:27:03 +0200
Subject: [PATCH] Improve compatibility with Pandas 3.0

---
 examples/electricity_demand_example.py |  2 +-
 examples/heat_demand_example.py        |  2 +-
 src/demandlib/bdew/heat_building.py    |  4 ++--
 src/demandlib/particular_profiles.py   | 12 ++++--------
 src/demandlib/tools.py                 | 13 ++++++-------
 5 files changed, 14 insertions(+), 19 deletions(-)

diff --git a/examples/electricity_demand_example.py b/examples/electricity_demand_example.py
index a2555a1..38a2874 100644
--- a/examples/electricity_demand_example.py
+++ b/examples/electricity_demand_example.py
@@ -97,7 +97,7 @@
 print("Or resample the DataFrame to hourly values using the mean() " "method.")
 
 # Resample 15-minute values to hourly values.
-elec_demand_resampled = elec_demand.resample("H").mean()
+elec_demand_resampled = elec_demand.resample("h").mean()
 print(elec_demand_resampled.sum())
 
 # Plot demand
diff --git a/examples/heat_demand_example.py b/examples/heat_demand_example.py
index 768105c..ed76263 100644
--- a/examples/heat_demand_example.py
+++ b/examples/heat_demand_example.py
@@ -73,7 +73,7 @@
 # Create DataFrame for 2010
 demand = pd.DataFrame(
     index=pd.date_range(
-        datetime.datetime(2010, 1, 1, 0), periods=8760, freq="H"
+        datetime.datetime(2010, 1, 1, 0), periods=8760, freq="h"
     )
 )
 
diff --git a/src/demandlib/bdew/heat_building.py b/src/demandlib/bdew/heat_building.py
index f565021..0c47430 100644
--- a/src/demandlib/bdew/heat_building.py
+++ b/src/demandlib/bdew/heat_building.py
@@ -107,8 +107,8 @@ def weighted_temperature(self, how="geometric_series"):
             .resample("D")
             .mean()
             .reindex(self.df.index)
-            .fillna(method="ffill")
-            .fillna(method="bfill")
+            .ffill()
+            .bfill()
         )
 
         if how == "geometric_series":
diff --git a/src/demandlib/particular_profiles.py b/src/demandlib/particular_profiles.py
index bb64158..2fb0039 100644
--- a/src/demandlib/particular_profiles.py
+++ b/src/demandlib/particular_profiles.py
@@ -62,25 +62,21 @@ def simple_profile(self, annual_demand, **kwargs):
 
         self.dataframe["ind"] = 0
 
-        self.dataframe["ind"].mask(
+        self.dataframe["ind"] = self.dataframe["ind"].mask(
             cond=self.dataframe["weekday"].between_time(am, pm).isin(week),
             other=profile_factors["week"]["day"],
-            inplace=True,
         )
-        self.dataframe["ind"].mask(
+        self.dataframe["ind"] = self.dataframe["ind"].mask(
             cond=self.dataframe["weekday"].between_time(pm, am).isin(week),
             other=profile_factors["week"]["night"],
-            inplace=True,
         )
-        self.dataframe["ind"].mask(
+        self.dataframe["ind"] = self.dataframe["ind"].mask(
             cond=self.dataframe["weekday"].between_time(am, pm).isin(weekend),
             other=profile_factors["weekend"]["day"],
-            inplace=True,
         )
-        self.dataframe["ind"].mask(
+        self.dataframe["ind"] = self.dataframe["ind"].mask(
             cond=self.dataframe["weekday"].between_time(pm, am).isin(weekend),
             other=profile_factors["weekend"]["night"],
-            inplace=True,
         )
 
         if self.dataframe["ind"].isnull().any(axis=0):
diff --git a/src/demandlib/tools.py b/src/demandlib/tools.py
index 0521ac8..e2b565a 100644
--- a/src/demandlib/tools.py
+++ b/src/demandlib/tools.py
@@ -36,13 +36,12 @@ def add_weekdays2df(time_df, holidays=None, holiday_is_sunday=False):
     if holidays is not None:
         if isinstance(holidays, dict):
             holidays = list(holidays.keys())
-        time_df["weekday"].mask(
-            cond=pd.to_datetime(time_df["date"]).isin(
-                pd.to_datetime(holidays)
-            ),
-            other=0,
-            inplace=True,
-        )
+            time_df["weekday"] = time_df["weekday"].mask(
+                cond=pd.to_datetime(time_df["date"]).isin(
+                    pd.to_datetime(holidays)
+                ),
+                other=0,
+            )
 
     if holiday_is_sunday:
         time_df.weekday = time_df.weekday.mask(