Update app.py

app.py

@@ -10,6 +10,7 @@ from datetime import datetime, timedelta
 import joblib
 import os
 import re
+import matplotlib.dates as mdates
 
 # Define stock tickers
 STOCK_TICKERS = [
@@ -228,8 +229,8 @@ def stock_prediction_app(ticker: str, start_date: str, end_date: str):
     decision = buy_or_sell(current_price, predicted_price)
 
     # Plotting historical prices and predicted tomorrow's price
-    plt.figure(figsize=(10,5))
-    plt.plot(data['Close'], label='Historical Close Price')
+    plt.figure(figsize=(12, 6))
+    plt.plot(data.index, data['Close'], label='Historical Close Price', color='blue')
 
     # Add predicted price for tomorrow
     tomorrow_date = data.index[-1] + timedelta(days=1)
@@ -237,12 +238,21 @@ def stock_prediction_app(ticker: str, start_date: str, end_date: str):
     while tomorrow_date.weekday() >= 5:  # Saturday=5, Sunday=6
         tomorrow_date += timedelta(days=1)
 
-    plt.scatter(tomorrow_date, predicted_price, color='red', label='Predicted Close Price (Tomorrow)')
+    plt.scatter(tomorrow_date, predicted_price, color='red', label='Predicted Close Price (Tomorrow)', zorder=5)
+
+    # Formatting the x-axis with better date formatting
+    plt.gca().xaxis.set_major_locator(mdates.AutoDateLocator())
+    plt.gca().xaxis.set_major_formatter(mdates.DateFormatter('%Y-%m-%d'))
+    plt.xticks(rotation=45)
+
     plt.title(f'{ticker} Price Prediction for Tomorrow')
     plt.xlabel('Date')
     plt.ylabel('Price ($)')
     plt.legend()
+    plt.grid(True, linestyle='--', alpha=0.5)
     plt.tight_layout()
+
+    # Create the figure
     fig = plt.gcf()
     plt.close()