diff --git a/chart.py b/chart.py
index cffd920..c7f94c1 100644
--- a/chart.py
+++ b/chart.py
@@ -7,6 +7,7 @@ from lightweight_charts import Chart
 
 
 import random
+from datetime import datetime
 
 horizontal_lines = {}
 
@@ -331,24 +332,59 @@ def on_range_change_poc(chart, bars_before, bars_after):
     horizontal_lines[poc_line_name] = poc_line
 
 
-def plot_chart(df, symbol: str, name: str, timeframe: str):
-    """
-    df: DataFrame
-    time, open, high, low, close, volume, [buy, sell]可选 buy=1 买入信号, sell=1 卖出信号
+def check_df(df: pd.DataFrame):
+    # basic type check
+    if not isinstance(df, pd.DataFrame):
+        raise TypeError("df must be a pandas DataFrame")
+
+    required_cols = ["time", "open", "high", "low", "close", "volume"]
+    missing = [c for c in required_cols if c not in df.columns]
+    if missing:
+        raise ValueError(
+            f"Missing required columns: {missing}. Required: {required_cols}"
+        )
+
+    # time column must be datetime.datetime or pd.Timestamp (or a datetime64 dtype)
+    time_series = df["time"]
+    if not (
+        pd.api.types.is_datetime64_any_dtype(time_series)
+        or time_series.apply(lambda x: isinstance(x, (pd.Timestamp, datetime))).all()
+    ):
+        raise TypeError(
+            "Column 'time' must contain datetime values (python datetime.datetime or pandas.Timestamp) "
+            "or be a datetime64 dtype."
+        )
+
+    # other columns must be numeric (int or float)
+    for col in ["open", "high", "low", "close", "volume"]:
+        if not pd.api.types.is_numeric_dtype(df[col]):
+            raise TypeError(f"Column '{col}' must be numeric (int or float)")
+
+
+def plot_chart(
+    df, symbol: str, name: str, timeframe: str, init_visible_num_bars: int = 90
+):
+    # 校验数据是否满足
+    check_df(df)
 
-    """
     chart = Chart(toolbox=True, inner_height=0.8, maximize=True)
-
     chart.topbar.textbox("symbol", symbol)
     chart.topbar.textbox("name", name)
     chart.topbar.textbox("timeframe", timeframe)
-
     chart.legend(
         visible=True, font_size=14, color="#FFFFFF", font_family="Times New Roman"
     )
-
     chart.set(df)
+
+    # 设置刚进入chart时的可见k线数量范围
+    end_time = df["time"].iloc[-1]
+    start_time = df["time"].iloc[-init_visible_num_bars]
+    chart.set_visible_range(start_time, end_time)
+
+    # 设置每次放缩k线范围时的回调函数计算实时计算poc
     chart.events.range_change += on_range_change_poc
+
+    # 添加技术指标
     # add_ema(df, chart, period=10)
     # add_ema(df, chart, period=20)
     add_ema(df, chart, period=30)