analysis.py

import pandas as pd

def percent_profitable(data):
    return len(data.loc[data.profit > 0]) / len(data)

def show_losers(data):
    return data.loc[data.profit <= 0]

def top_performers_per_trade(data):
    return data.sort_values(by=["avg_return"], ascending=False)[:5]

def best_returns_wrt_start_price(data):
    data["pct_return_start"] = data["profit"]/data["start_price"]
    return data.sort_values(by=["pct_return_start"], ascending=False)[:5]

if __name__ == '__main__':
    d1 = pd.read_csv('BollingerBot/results_1yr.dat')
    d5 = pd.read_csv('BollingerBot/results_5yr.dat')
    d10 = pd.read_csv('BollingerBot/results_10yr.dat')

    d1 = d1[d1.profit != 0]
    d5 = d5[d5.profit != 0]
    d10 = d10[d10.profit != 0]

    data = [d1, d5, d10]
    for d in data:
        print("% Profitable:", percent_profitable(d))
        print("Unprofitable:", show_losers(d))
        print("Top per trade:", top_performers_per_trade(d))
        print("Top w.r.t start:", best_returns_wrt_start_price(d))