MarketStack_Stock_Comparision.py

import requests
import pandas as pd
from datetime import datetime, timedelta

# API Key and URL
API_KEY = '0d25bd311d7d68b831ea2c0e952e6a6a'
url = "https://api.marketstack.com/v1/eod"

# Calculate date range (last 30 days)
today = datetime.today().strftime('%Y-%m-%d')
last_30_days = (datetime.today() - timedelta(days=30)).strftime('%Y-%m-%d')

# Stocks to compare
symbols = ["AAPL", "MSFT"]

# Store results
all_data = []

# Fetch data for both stocks
for symbol in symbols:
    params = {
        "access_key": API_KEY,
        "symbols": symbol,
        "date_from": last_30_days,
        "date_to": today,
        "limit": 30
    }

    response = requests.get(url, params=params)
    
    if response.status_code == 200:
        data = response.json().get("data", [])
        
        # Extract required fields
        for item in data:
            formatted_date = datetime.strptime(item["date"][:10], "%Y-%m-%d").strftime("%d-%b-%Y")  # Format: Day-Month-Year
            
            all_data.append({
                "Date": formatted_date,
                "Stock": symbol,
                "Open": item["open"],
                "Close": item["close"],
                "Change (%)": round(((item["close"] - item["open"]) / item["open"]) * 100, 2)
            })
    else:
        print(f"❌ API request failed for {symbol} with status code {response.status_code}")

# Create DataFrame
df = pd.DataFrame(all_data)

# Convert Date column to datetime for sorting
df["Date"] = pd.to_datetime(df["Date"], format="%d-%b-%Y")
df = df.sort_values(by=["Date", "Stock"], ascending=[False, True]).reset_index(drop=True)

# Convert Date back to string in required format
df["Date"] = df["Date"].dt.strftime("%d-%b-%Y")

# Assign alternating colors based on unique date values
unique_dates = df["Date"].unique()
date_color_map = {date: "#e0f7fa" if i % 2 == 0 else "#ffffff" for i, date in enumerate(unique_dates)}

def highlight_changes(val):
    """Color positive change green, negative red"""
    color = 'green' if val > 0 else 'red' if val < 0 else 'black'
    return f'color: {color}'

def apply_date_based_colors(row):
    """Apply background color based on date"""
    return [f'background-color: {date_color_map[row["Date"]]}' for _ in row]

styled_df = df.style \
    .set_properties(**{'border': '1px solid black', 'text-align': 'center'}) \
    .set_caption("📊 AAPL vs MSFT: 30-Day Performance") \
    .applymap(highlight_changes, subset=['Change (%)']) \
    .apply(apply_date_based_colors, axis=1) \
    .format({"Change (%)": "{:.2f}%"})

# Display styled DataFrame
styled_df