fix: replace deprecated pandas fillna(method=) with ffill()/bfill()

pyproject.toml

@@ -27,7 +27,10 @@ license = { text = "MIT" }
 dependencies = [
   "pyyaml",
   "numpy",
-  "pandas>=0.24",
+  # Since version 1.1.0, pandas supports the ffill and bfill methods.
+  # Since version 2.1.0, pandas has deprecated the method parameter of the fillna method. 
+  # qlib has updated the fillna method in PR 1987 and limited the minimum version of pandas.
+  "pandas>=1.1",
   # I encoutered an Error that the set_uri does not work when downloading artifacts in mlflow 3.1.1;
   # But earlier versions of mlflow does not have this problem.
   # But when I switch to 2.*.* version, another error occurs, which is even more strange...

qlib/backtest/profit_attribution.py

@@ -281,13 +281,13 @@ def brinson_pa(
 
     stock_group_field = stock_df[group_field].unstack().T
     # FIXME: some attributes of some suspend stock is NAN.
-    stock_group_field = stock_group_field.fillna(method="ffill")
+    stock_group_field = stock_group_field.ffill()
     stock_group_field = stock_group_field.loc[start_date:end_date]
 
     stock_group = get_stock_group(stock_group_field, bench_stock_weight, group_method, group_n)
 
     deal_price_df = stock_df["deal_price"].unstack().T
-    deal_price_df = deal_price_df.fillna(method="ffill")
+    deal_price_df = deal_price_df.ffill()
 
     # NOTE:
     # The return will be slightly different from the of the return in the report.

qlib/contrib/ops/high_freq.py

@@ -135,7 +135,7 @@ class FFillNan(ElemOperator):
 
     def _load_internal(self, instrument, start_index, end_index, freq):
         series = self.feature.load(instrument, start_index, end_index, freq)
-        return series.fillna(method="ffill")
+        return series.ffill()
 
 
 class BFillNan(ElemOperator):
@@ -154,7 +154,7 @@ class BFillNan(ElemOperator):
 
     def _load_internal(self, instrument, start_index, end_index, freq):
         series = self.feature.load(instrument, start_index, end_index, freq)
-        return series.fillna(method="bfill")
+        return series.bfill()
 
 
 class Date(ElemOperator):

qlib/contrib/report/analysis_position/parse_position.py

@@ -33,7 +33,7 @@ def parse_position(position: dict = None) -> pd.DataFrame:
 
     position_weight_df = get_stock_weight_df(position)
     # If the day does not exist, use the last weight
-    position_weight_df.fillna(method="ffill", inplace=True)
+    position_weight_df.ffill(inplace=True)
 
     previous_data = {"date": None, "code_list": []}
 

qlib/data/dataset/storage.py

@@ -67,7 +67,6 @@ def fetch(
         col_set: Union[str, List[str]] = DataHandler.CS_ALL,
         fetch_orig: bool = True,
     ) -> pd.DataFrame:
-
         # Following conflicts may occur
         # - Does [20200101", "20210101"] mean selecting this slice or these two days?
         # To solve this issue

qlib/utils/mod.py

@@ -161,7 +161,6 @@ def init_instance_by_config(
             # path like 'file:///<path to pickle file>/obj.pkl'
             pr = urlparse(config)
             if pr.scheme == "file":
-
                 # To enable relative path like file://data/a/b/c.pkl.  pr.netloc will be data
                 path = pr.path
                 if pr.netloc != "":

qlib/utils/resam.py

@@ -222,7 +222,7 @@ def get_valid_value(series, last=True):
     Nan | float
         the first/last valid value
     """
-    return series.fillna(method="ffill").iloc[-1] if last else series.fillna(method="bfill").iloc[0]
+    return series.ffill().iloc[-1] if last else series.bfill().iloc[0]
 
 
 def _ts_data_valid(ts_feature, last=False):

scripts/data_collector/baostock_5min/collector.py

@@ -172,7 +172,7 @@ def __init__(
     @staticmethod
     def calc_change(df: pd.DataFrame, last_close: float) -> pd.Series:
         df = df.copy()
-        _tmp_series = df["close"].fillna(method="ffill")
+        _tmp_series = df["close"].ffill()
         _tmp_shift_series = _tmp_series.shift(1)
         if last_close is not None:
             _tmp_shift_series.iloc[0] = float(last_close)

scripts/data_collector/yahoo/collector.py

@@ -371,7 +371,7 @@ class YahooNormalize(BaseNormalize):
     @staticmethod
     def calc_change(df: pd.DataFrame, last_close: float) -> pd.Series:
         df = df.copy()
-        _tmp_series = df["close"].fillna(method="ffill")
+        _tmp_series = df["close"].ffill()
         _tmp_shift_series = _tmp_series.shift(1)
         if last_close is not None:
             _tmp_shift_series.iloc[0] = float(last_close)
@@ -459,7 +459,7 @@ def adjusted_price(self, df: pd.DataFrame) -> pd.DataFrame:
         df.set_index(self._date_field_name, inplace=True)
         if "adjclose" in df:
             df["factor"] = df["adjclose"] / df["close"]
-            df["factor"] = df["factor"].fillna(method="ffill")
+            df["factor"] = df["factor"].ffill()
         else:
             df["factor"] = 1
         for _col in self.COLUMNS: