diff --git a/docker/Dockerfile b/docker/Dockerfile
index 0a48c102f..52f63b001 100644
--- a/docker/Dockerfile
+++ b/docker/Dockerfile
@@ -29,7 +29,7 @@ trusted-host = mirrors.aliyun.com" > /etc/pip.conf && \
     pip install mysqlclient && \
     pip install requests && \
     pip install arrow && \
-    pip install numpy==1.26.4 && \
+    pip install numpy && \
     pip install SQLAlchemy && \
     pip install PyMySQL && \
     pip install Logbook && \
diff --git a/instock/core/crawling/stock_fund_em.py b/instock/core/crawling/stock_fund_em.py
index c194c5ff3..f043fe65c 100644
--- a/instock/core/crawling/stock_fund_em.py
+++ b/instock/core/crawling/stock_fund_em.py
@@ -312,6 +312,17 @@ def stock_sector_fund_flow_rank(
                 "今日主力净流入最大股",
             ]
         ]
+        # temp_df['今日涨跌幅'] = pd.to_numeric(temp_df['今日涨跌幅'])
+        # temp_df['今日主力净流入-净额'] = pd.to_numeric(temp_df['今日主力净流入-净额'])
+        # temp_df['今日主力净流入-净占比'] = pd.to_numeric(temp_df['今日主力净流入-净占比'])
+        # temp_df['今日超大单净流入-净额'] = pd.to_numeric(temp_df['今日超大单净流入-净额'])
+        # temp_df['今日超大单净流入-净占比'] = pd.to_numeric(temp_df['今日超大单净流入-净占比'])
+        # temp_df['今日大单净流入-净额'] = pd.to_numeric(temp_df['今日大单净流入-净额'])
+        # temp_df['今日大单净流入-净占比'] = pd.to_numeric(temp_df['今日大单净流入-净占比'])
+        # temp_df['今日中单净流入-净额'] = pd.to_numeric(temp_df['今日中单净流入-净额'])
+        # temp_df['今日中单净流入-净占比'] = pd.to_numeric(temp_df['今日中单净流入-净占比'])
+        # temp_df['今日小单净流入-净额'] = pd.to_numeric(temp_df['今日小单净流入-净额'])
+        # temp_df['今日小单净流入-净占比'] = pd.to_numeric(temp_df['今日小单净流入-净占比'])
     elif indicator == "5日":
         temp_df.columns = [
             "-",
@@ -351,6 +362,17 @@ def stock_sector_fund_flow_rank(
                 "5日主力净流入最大股",
             ]
         ]
+        # temp_df['5日涨跌幅'] = pd.to_numeric(temp_df['5日涨跌幅'])
+        # temp_df['5日主力净流入-净额'] = pd.to_numeric(temp_df['5日主力净流入-净额'])
+        # temp_df['5日主力净流入-净占比'] = pd.to_numeric(temp_df['5日主力净流入-净占比'])
+        # temp_df['5日超大单净流入-净额'] = pd.to_numeric(temp_df['5日超大单净流入-净额'])
+        # temp_df['5日超大单净流入-净占比'] = pd.to_numeric(temp_df['5日超大单净流入-净占比'])
+        # temp_df['5日大单净流入-净额'] = pd.to_numeric(temp_df['5日大单净流入-净额'])
+        # temp_df['5日大单净流入-净占比'] = pd.to_numeric(temp_df['5日大单净流入-净占比'])
+        # temp_df['5日中单净流入-净额'] = pd.to_numeric(temp_df['5日中单净流入-净额'])
+        # temp_df['5日中单净流入-净占比'] = pd.to_numeric(temp_df['5日中单净流入-净占比'])
+        # temp_df['5日小单净流入-净额'] = pd.to_numeric(temp_df['5日小单净流入-净额'])
+        # temp_df['5日小单净流入-净占比'] = pd.to_numeric(temp_df['5日小单净流入-净占比'])
     elif indicator == "10日":
         temp_df.columns = [
             "-",
@@ -390,6 +412,18 @@ def stock_sector_fund_flow_rank(
                 "10日主力净流入最大股",
             ]
         ]
+        # temp_df['10日涨跌幅'] = pd.to_numeric(temp_df['10日涨跌幅'])
+        # temp_df['10日主力净流入-净额'] = pd.to_numeric(temp_df['10日主力净流入-净额'])
+        # temp_df['10日主力净流入-净占比'] = pd.to_numeric(temp_df['10日主力净流入-净占比'])
+        # temp_df['10日超大单净流入-净额'] = pd.to_numeric(temp_df['10日超大单净流入-净额'])
+        # temp_df['10日超大单净流入-净占比'] = pd.to_numeric(temp_df['10日超大单净流入-净占比'])
+        # temp_df['10日大单净流入-净额'] = pd.to_numeric(temp_df['10日大单净流入-净额'])
+        # temp_df['10日大单净流入-净占比'] = pd.to_numeric(temp_df['10日大单净流入-净占比'])
+        # temp_df['10日中单净流入-净额'] = pd.to_numeric(temp_df['10日中单净流入-净额'])
+        # temp_df['10日中单净流入-净占比'] = pd.to_numeric(temp_df['10日中单净流入-净占比'])
+        # temp_df['10日小单净流入-净额'] = pd.to_numeric(temp_df['10日小单净流入-净额'])
+        # temp_df['10日小单净流入-净占比'] = pd.to_numeric(temp_df['10日小单净流入-净占比'])
+
     return temp_df
 
 
diff --git a/requirements.txt b/requirements.txt
index 919034bc2..7da59878f 100644
--- a/requirements.txt
+++ b/requirements.txt
@@ -1,7 +1,7 @@
-numpy==1.26.4
+numpy==2.1.3
 pandas==2.2.3
 py_mini_racer==0.6.0
-TA_Lib==0.4.32
+TA_Lib==0.5.0
 arrow==1.3.0
 bokeh==3.6.0
 PyMySQL==1.1.1