Check anual increment of stocks

stonks.py

import yfinance as yf
import pandas as pd


def calculate(symbol: str) -> dict:
    stocks = yf.Ticker(symbol)
    data = stocks.history(period="5y")

    data = data[["Close"]]
    data.reset_index(inplace=True)

    data['month'] = data["Date"].dt.month
    data['year'] = data["Date"].dt.year

    data.rename(columns = {'Close' : 'Price', 'day' : 'Day', 'month' : 'Month', 'year' : 'Year'}, inplace = True)
    data.drop(columns=["Date"], inplace=True)
    data = data[data["Year"] != 2021]

    per_year = data.groupby('Year')['Price'].agg(lambda x: x.pct_change().mean() * 365)
    per_month = data.groupby('Month')['Price'].agg(lambda x: x.pct_change().mean() * (365 / 12))
    per_year_month = data.groupby(['Year', 'Month'])['Price'].agg(lambda x: x.pct_change().mean() * (365 / 12))

    per_year_avg = per_year.mean()
    per_month_avg = per_month.mean()
    per_year_month_avg = per_year_month.mean()

    per_year["avg"] = per_year_avg
    per_month["avg"] = per_month_avg
    per_year_month["avg"] = per_year_month_avg

    return {
        "per_year": per_year, "per_month": per_month, "per_year_month": per_year_month,
    }


def main():
    symbols = [
      "COST",
    ]
    results = {}
    for symbol in symbols:
        data = calculate(symbol)
        print(symbol)
        results[symbol] = data

    tables = ["per_year", "per_month", "per_year_month"]
    for row in tables:
        data = {}
        for symbol in symbols:
            data[symbol] = results[symbol][row]
        print(data)
        df = pd.DataFrame(data)
        df = df.transpose()
        df.to_csv(f"stocks_{row}.csv")


if __name__ == "__main__":
    main()