diff --git a/scripts/data_collector/contrib/fill_cn_1min_data/fill_cn_1min_data.py b/scripts/data_collector/contrib/fill_cn_1min_data/fill_cn_1min_data.py
index 4abca3361..0a721298d 100644
--- a/scripts/data_collector/contrib/fill_cn_1min_data/fill_cn_1min_data.py
+++ b/scripts/data_collector/contrib/fill_cn_1min_data/fill_cn_1min_data.py
@@ -28,10 +28,9 @@ def get_date_range(data_1min_dir: Path, max_workers: int = 16, date_field_name:
                     _dates = pd.to_datetime(_result[date_field_name])
 
                     _tmp_min = _dates.min()
-                    min_date = min_date(min_date, _tmp_min) if min_date is not None else _tmp_min
-
+                    min_date = min(min_date, _tmp_min) if min_date is not None else _tmp_min
                     _tmp_max = _dates.max()
-                    max_date = min_date(max_date, _tmp_max) if max_date is not None else _tmp_max
+                    max_date = max(max_date, _tmp_max) if max_date is not None else _tmp_max
                 p_bar.update()
     return min_date, max_date
 
@@ -81,7 +80,7 @@ def fill_1min_using_1d(
     tmp_df = pd.read_csv(list(data_1min_dir.glob("*.csv"))[0])
     columns = tmp_df.columns
     _si = tmp_df[symbol_field_name].first_valid_index()
-    is_lower = tmp_df.loc[tmp_df][symbol_field_name].islower()
+    is_lower = tmp_df.loc[_si][symbol_field_name].islower()
     for symbol in tqdm(miss_symbols):
         if is_lower:
             symbol = symbol.lower()
@@ -89,8 +88,11 @@ def fill_1min_using_1d(
         index_1min = generate_minutes_calendar_from_daily(index_1d)
         index_1min.name = date_field_name
         _df = pd.DataFrame(columns=columns, index=index_1min)
+        if date_field_name in _df.columns:
+            del _df[date_field_name]
         _df.reset_index(inplace=True)
         _df[symbol_field_name] = symbol
+        _df["paused_num"] = 0
         _df.to_csv(data_1min_dir.joinpath(f"{symbol}.csv"), index=False)
 
 
diff --git a/scripts/data_collector/yahoo/collector.py b/scripts/data_collector/yahoo/collector.py
index 16b0a32ba..58e1d3009 100644
--- a/scripts/data_collector/yahoo/collector.py
+++ b/scripts/data_collector/yahoo/collector.py
@@ -473,21 +473,6 @@ class YahooNormalize1min(YahooNormalize, ABC):
     CONSISTENT_1d = False
     CALC_PAUSED_NUM = False
 
-    def __init__(self, date_field_name: str = "date", symbol_field_name: str = "symbol", **kwargs):
-        """
-
-        Parameters
-        ----------
-        date_field_name: str
-            date field name, default is date
-        symbol_field_name: str
-            symbol field name, default is symbol
-        """
-        super(YahooNormalize1min, self).__init__(date_field_name, symbol_field_name)
-        _class_name = self.__class__.__name__.replace("min", "d")
-        _class = getattr(importlib.import_module("collector"), _class_name)  # type: Type[YahooNormalize]
-        self.data_1d_obj = _class(self._date_field_name, self._symbol_field_name)
-
     @property
     def calendar_list_1d(self):
         calendar_list_1d = getattr(self, "_calendar_list_1d", None)
@@ -512,7 +497,10 @@ class YahooNormalize1min(YahooNormalize, ABC):
         """
         data_1d = YahooCollector.get_data_from_remote(self.symbol_to_yahoo(symbol), interval="1d", start=start, end=end)
         if not (data_1d is None or data_1d.empty):
-            data_1d = self.data_1d_obj.normalize(data_1d)
+            _class_name = self.__class__.__name__.replace("min", "d")
+            _class: type(YahooNormalize) = getattr(importlib.import_module("collector"), _class_name)
+            data_1d_obj = _class(self._date_field_name, self._symbol_field_name)
+            data_1d = data_1d_obj.normalize(data_1d)
         return data_1d
 
     def adjusted_price(self, df: pd.DataFrame) -> pd.DataFrame:
@@ -525,6 +513,7 @@ class YahooNormalize1min(YahooNormalize, ABC):
         _start = pd.Timestamp(df[self._date_field_name].min()).strftime(self.DAILY_FORMAT)
         _end = (pd.Timestamp(df[self._date_field_name].max()) + pd.Timedelta(days=1)).strftime(self.DAILY_FORMAT)
         data_1d: pd.DataFrame = self.get_1d_data(symbol, _start, _end)
+        data_1d = data_1d.copy()
         if data_1d is None or data_1d.empty:
             df["factor"] = 1
             # TODO: np.nan or 1 or 0
@@ -700,8 +689,8 @@ class YahooNormalizeCN1minOffline(YahooNormalizeCN1min):
         symbol_field_name: str
             symbol field name, default is symbol
         """
-        super(YahooNormalizeCN1minOffline, self).__init__(date_field_name, symbol_field_name)
         self.qlib_data_1d_dir = qlib_data_1d_dir
+        super(YahooNormalizeCN1minOffline, self).__init__(date_field_name, symbol_field_name)
         self._all_1d_data = self._get_all_1d_data()
 
     def _get_1d_calendar_list(self) -> Iterable[pd.Timestamp]: