From 4aa2ae37bd6eb8910153fa8ae6043d93340187b8 Mon Sep 17 00:00:00 2001
From: octaviusgus <86911628+octaviusgus@users.noreply.github.com>
Date: Sun, 4 Jul 2021 14:38:17 +0200
Subject: [PATCH] add daily_profit_list

added extra key daily_profit in return of optimize_reports.generate_daily_stats
this allows us to analyze and plot a daily profit chart / equity line using snippet below inside jupyter notebook

```
# Plotting equity line (starting with 0 on day 1 and adding daily profit for each backtested day)

from freqtrade.configuration import Configuration
from freqtrade.data.btanalysis import load_backtest_data, load_backtest_stats
import plotly.express as px
import pandas as pd

# strategy = 'Strat'
# config = Configuration.from_files(["user_data/config.json"])
# backtest_dir = config["user_data_dir"] / "backtest_results"

stats = load_backtest_stats(backtest_dir)
strategy_stats = stats['strategy'][strategy]

equity = 0
equity_daily = []
for dp in strategy_stats['daily_profit']:
    equity_daily.append(equity)
    equity += float(dp)

dates = pd.date_range(strategy_stats['backtest_start'], strategy_stats['backtest_end'])

df = pd.DataFrame({'dates':dates,'equity_daily':equity_daily})

fig = px.line(df, x="dates", y="equity_daily")
fig.show()

```
---
 freqtrade/optimize/optimize_reports.py | 3 +++
 1 file changed, 3 insertions(+)

diff --git a/freqtrade/optimize/optimize_reports.py b/freqtrade/optimize/optimize_reports.py
index 2a794859d..89cf70437 100644
--- a/freqtrade/optimize/optimize_reports.py
+++ b/freqtrade/optimize/optimize_reports.py
@@ -261,6 +261,7 @@ def generate_daily_stats(results: DataFrame) -> Dict[str, Any]:
             'winning_days': 0,
             'draw_days': 0,
             'losing_days': 0,
+            'daily_profit_list': [],
         }
     daily_profit_rel = results.resample('1d', on='close_date')['profit_ratio'].sum()
     daily_profit = results.resample('1d', on='close_date')['profit_abs'].sum().round(10)
@@ -271,6 +272,7 @@ def generate_daily_stats(results: DataFrame) -> Dict[str, Any]:
     winning_days = sum(daily_profit > 0)
     draw_days = sum(daily_profit == 0)
     losing_days = sum(daily_profit < 0)
+    daily_profit_list = daily_profit.tolist()
 
     return {
         'backtest_best_day': best_rel,
@@ -280,6 +282,7 @@ def generate_daily_stats(results: DataFrame) -> Dict[str, Any]:
         'winning_days': winning_days,
         'draw_days': draw_days,
         'losing_days': losing_days,
+        'daily_profit': daily_profit_list,
     }