together.py

import pandas as pd
import matplotlib.pyplot as plt
import yfinance as yf
from datetime import datetime, date, timedelta

data = yf.download('QQQ', '2020-01-01', date.today().strftime('%Y-%m-%d'))
daily_df   = data['Close']

weekly_df  = daily_df.resample('W-Fri').last()
monthly_df = daily_df.resample('BME').last()

# Create the plot
plt.figure(figsize=(12, 6))

# Plot daily data with lower opacity
plt.plot(daily_df.index, daily_df.values, 
         alpha=0.3, label='Daily Values', color='blue')

# Plot weekly data with solid line
plt.plot(weekly_df.index, weekly_df.values, \
         linewidth=2, label='Weekly Average', color='green')

# Plot monthly data with solid line
plt.plot(monthly_df.index, monthly_df.values, \
         linewidth=2, label='Monthly Average', color='red')

# Customize the plot
plt.title('Daily Values vs Weekly and Monthly Average', pad=15)
plt.xlabel('Date')
plt.ylabel('Value')
plt.grid(True, alpha=0.3)
plt.legend()

# Rotate x-axis labels for better readability
plt.xticks(rotation=45)

# Adjust layout to prevent label cutoff
plt.tight_layout()

# Show the plot
plt.show()