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fix: Improve stock data validation with explicit type conversion and logging

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Bobby Abellana (aider) 2025-02-06 23:42:40 -08:00
parent f7d6d5d136
commit 6af7ce4bcd
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1 changed files with 14 additions and 1 deletions
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15
src/screener/t_sunnyband.py
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@ -39,6 +39,13 @@ def get_stock_data(ticker: str, start_date: datetime, end_date: datetime, interv
if df.empty: if df.empty:
return df 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 # Remove rows with suspicious values
df = df[ df = df[
(df['open'] > 0) & (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 # 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 return df
# Calculate proper date range (looking back from today) # Calculate proper date range (looking back from today)