Build a Stock Screener in Python

Filter UK stocks by P/E ratio, dividend yield, and market cap — all in Python.

Install Dependencies

pip install yfinance pandas

Fetch Stock Data

We'll screen 10 FTSE 100 stocks, pulling key metrics from Yahoo Finance:

import yfinance as yf
import pandas as pd

# Define a list of UK stocks to screen
tickers = ["SHEL.L", "AZN.L", "HSBA.L", "BP.L", "GSK.L",
           "RIO.L", "ULVR.L", "DGE.L", "LLOY.L", "VOD.L"]

results = []
for ticker in tickers:
    try:
        stock = yf.Ticker(ticker)
        info = stock.info
        results.append({
            "Ticker": ticker,
            "Name": info.get("shortName", "N/A"),
            "Price": info.get("currentPrice", 0),
            "PE Ratio": info.get("trailingPE", None),
            "Market Cap (B)": round(info.get("marketCap", 0) / 1e9, 1),
            "Dividend Yield %": round((info.get("dividendYield", 0) or 0) * 100, 2),
        })
    except:
        pass

df = pd.DataFrame(results)
print(df.to_string(index=False))

Apply Filters

Now screen for value stocks — low P/E ratio and high dividend yield:

# Filter: PE < 15 and Dividend Yield > 3%
screened = df[(df["PE Ratio"] < 15) & (df["Dividend Yield %"] > 3)]
print("\nScreened Results (PE < 15, Div > 3%):")
print(screened.to_string(index=False))

Rank Results

# Sort by dividend yield descending
ranked = df.sort_values("Dividend Yield %", ascending=False)
print("\nRanked by Dividend Yield:")
print(ranked.to_string(index=False))

Next Steps

• Add more tickers — screen the entire FTSE 350
• Add technical filters — RSI, moving averages
• Schedule daily scans with a cron job
• Export results to CSV or email alerts