From 6af7ce4bcde4e6fec387b117adc52e951aed35b9 Mon Sep 17 00:00:00 2001
From: "Bobby Abellana (aider)" <bobby@abellana.work>
Date: Thu, 6 Feb 2025 23:42:40 -0800
Subject: [PATCH] fix: Improve stock data validation with explicit type
 conversion and logging

---
 src/screener/t_sunnyband.py | 15 ++++++++++++++-
 1 file changed, 14 insertions(+), 1 deletion(-)

diff --git a/src/screener/t_sunnyband.py b/src/screener/t_sunnyband.py
index dc9d126..01c3944 100644
--- a/src/screener/t_sunnyband.py
+++ b/src/screener/t_sunnyband.py
@@ -39,6 +39,13 @@ def get_stock_data(ticker: str, start_date: datetime, end_date: datetime, interv
         if df.empty:
             return df
             
+        # Convert numeric columns to float
+        for col in ['open', 'high', 'low', 'close']:
+            df[col] = pd.to_numeric(df[col], errors='coerce')
+            
+        # Remove rows with NaN values
+        df = df.dropna()
+        
         # Remove rows with suspicious values
         df = df[
             (df['open'] > 0) & 
@@ -53,8 +60,14 @@ def get_stock_data(ticker: str, start_date: datetime, end_date: datetime, interv
         ]
         
         # Sort by date and remove duplicates
-        df = df.sort_values('date').drop_duplicates(subset=['date'])
+        df = df.sort_values('date', ascending=True).drop_duplicates(subset=['date'])
         
+        # Add validation message
+        if not df.empty:
+            print(f"Validated price for {ticker}:")
+            print(f"First price: ${df['close'].iloc[0]:.2f}")
+            print(f"Last price: ${df['close'].iloc[-1]:.2f}")
+            
         return df
     
     # Calculate proper date range (looking back from today)