Build a Stock Price Chart with yFinance and Matplotlib

📋 What You'll Need

Python 3.8+
pip install yfinance matplotlib pandas

Fetch stock data

Use yFinance to download 12 months of price history.

import yfinance as yf

ticker = 'AAPL'
df = yf.download(ticker, period='1y', auto_adjust=True)
print(df.tail())

Open    High     Low   Close    Volume
Date
2024-08-05  198.23  199.10  196.04  196.35  57285400
...

Add a moving average

Calculate the 50-day rolling mean on the Close column.

df['MA50'] = df['Close'].rolling(window=50).mean()
print(df[['Close','MA50']].tail())

Plot price and volume

Create a two-panel chart: price on top, volume on the bottom.

import matplotlib.pyplot as plt

fig, (ax1, ax2) = plt.subplots(2, 1, figsize=(12, 7), gridspec_kw={'height_ratios': [3, 1]}, sharex=True)

ax1.plot(df.index, df['Close'], label='Close', linewidth=1.5, color='#4f46e5')
ax1.plot(df.index, df['MA50'],  label='50-day MA', linewidth=1.2, color='#f59e0b', linestyle='--')
ax1.set_title(f'{ticker} — 12-Month Price Chart')
ax1.set_ylabel('Price (USD)')
ax1.legend()
ax1.grid(alpha=0.3)

ax2.bar(df.index, df['Volume'], color='#64748b', alpha=0.5)
ax2.set_ylabel('Volume')
ax2.grid(alpha=0.3)

plt.tight_layout()
plt.savefig(f'{ticker}_chart.png', dpi=150)
print("Chart saved!")

Chart saved!

💡 Tip: Use plt.show() instead of savefig() when running in Jupyter — you get an interactive zoom-and-pan widget.

🎉 You Did It!

You can now pull and chart live stock data with three lines of code. Try comparing two tickers on the same axis using twin axes.

Browse More Tutorials

📈 Build a Stock Price Chart with yFinance and Matplotlib

🎯 What You'll Build

📋 What You'll Need

Fetch stock data

Add a moving average

Plot price and volume

🎉 You Did It!

📈 Build a Stock Price Chart with yFinance and Matplotlib

🎯 What You'll Build

📋 What You'll Need

Fetch stock data

Add a moving average

Plot price and volume

🎉 You Did It!

Found something wrong?

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