{
 "cells": [
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# Strategy analysis example\n",
    "\n",
    "Debugging a strategy can be time-consuming. Freqtrade offers helper functions to visualize raw data.\n",
    "The following assumes you work with SampleStrategy, data for 5m timeframe from Binance and have downloaded them into the data directory in the default location."
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Setup"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 2,
   "metadata": {},
   "outputs": [
    {
     "ename": "OperationalException",
     "evalue": "Directory `/Users/surfer/Software/MMM/develop/freqtrade/freqtrade/templates/user_data` does not exist. Please use `freqtrade create-userdir` to create a user directory",
     "output_type": "error",
     "traceback": [
      "\u001b[0;31m---------------------------------------------------------------------------\u001b[0m",
      "\u001b[0;31mOperationalException\u001b[0m                      Traceback (most recent call last)",
      "Input \u001b[0;32mIn [2]\u001b[0m, in \u001b[0;36m<cell line: 7>\u001b[0;34m()\u001b[0m\n\u001b[1;32m      2\u001b[0m \u001b[38;5;28;01mfrom\u001b[39;00m \u001b[38;5;21;01mfreqtrade\u001b[39;00m\u001b[38;5;21;01m.\u001b[39;00m\u001b[38;5;21;01mconfiguration\u001b[39;00m \u001b[38;5;28;01mimport\u001b[39;00m Configuration\n\u001b[1;32m      4\u001b[0m \u001b[38;5;66;03m# Customize these according to your needs.\u001b[39;00m\n\u001b[1;32m      5\u001b[0m \n\u001b[1;32m      6\u001b[0m \u001b[38;5;66;03m# Initialize empty configuration object\u001b[39;00m\n\u001b[0;32m----> 7\u001b[0m config \u001b[38;5;241m=\u001b[39m \u001b[43mConfiguration\u001b[49m\u001b[38;5;241;43m.\u001b[39;49m\u001b[43mfrom_files\u001b[49m\u001b[43m(\u001b[49m\u001b[43m[\u001b[49m\u001b[43m]\u001b[49m\u001b[43m)\u001b[49m\n\u001b[1;32m      8\u001b[0m \u001b[38;5;66;03m# Optionally, use existing configuration file\u001b[39;00m\n\u001b[1;32m      9\u001b[0m \u001b[38;5;66;03m# config = Configuration.from_files([\"config.json\"])\u001b[39;00m\n\u001b[1;32m     10\u001b[0m \n\u001b[1;32m     11\u001b[0m \u001b[38;5;66;03m# Define some constants\u001b[39;00m\n\u001b[1;32m     12\u001b[0m config[\u001b[38;5;124m\"\u001b[39m\u001b[38;5;124mtimeframe\u001b[39m\u001b[38;5;124m\"\u001b[39m] \u001b[38;5;241m=\u001b[39m \u001b[38;5;124m\"\u001b[39m\u001b[38;5;124m1m\u001b[39m\u001b[38;5;124m\"\u001b[39m\n",
      "File \u001b[0;32m~/Software/MMM/develop/freqtrade/freqtrade/configuration/configuration.py:60\u001b[0m, in \u001b[0;36mConfiguration.from_files\u001b[0;34m(files)\u001b[0m\n\u001b[1;32m     58\u001b[0m \u001b[38;5;66;03m# Keep this method as staticmethod, so it can be used from interactive environments\u001b[39;00m\n\u001b[1;32m     59\u001b[0m c \u001b[38;5;241m=\u001b[39m Configuration({\u001b[38;5;124m'\u001b[39m\u001b[38;5;124mconfig\u001b[39m\u001b[38;5;124m'\u001b[39m: files}, RunMode\u001b[38;5;241m.\u001b[39mOTHER)\n\u001b[0;32m---> 60\u001b[0m \u001b[38;5;28;01mreturn\u001b[39;00m \u001b[43mc\u001b[49m\u001b[38;5;241;43m.\u001b[39;49m\u001b[43mget_config\u001b[49m\u001b[43m(\u001b[49m\u001b[43m)\u001b[49m\n",
      "File \u001b[0;32m~/Software/MMM/develop/freqtrade/freqtrade/configuration/configuration.py:42\u001b[0m, in \u001b[0;36mConfiguration.get_config\u001b[0;34m(self)\u001b[0m\n\u001b[1;32m     37\u001b[0m \u001b[38;5;124;03m\"\"\"\u001b[39;00m\n\u001b[1;32m     38\u001b[0m \u001b[38;5;124;03mReturn the config. Use this method to get the bot config\u001b[39;00m\n\u001b[1;32m     39\u001b[0m \u001b[38;5;124;03m:return: Dict: Bot config\u001b[39;00m\n\u001b[1;32m     40\u001b[0m \u001b[38;5;124;03m\"\"\"\u001b[39;00m\n\u001b[1;32m     41\u001b[0m \u001b[38;5;28;01mif\u001b[39;00m \u001b[38;5;28mself\u001b[39m\u001b[38;5;241m.\u001b[39mconfig \u001b[38;5;129;01mis\u001b[39;00m \u001b[38;5;28;01mNone\u001b[39;00m:\n\u001b[0;32m---> 42\u001b[0m     \u001b[38;5;28mself\u001b[39m\u001b[38;5;241m.\u001b[39mconfig \u001b[38;5;241m=\u001b[39m \u001b[38;5;28;43mself\u001b[39;49m\u001b[38;5;241;43m.\u001b[39;49m\u001b[43mload_config\u001b[49m\u001b[43m(\u001b[49m\u001b[43m)\u001b[49m\n\u001b[1;32m     44\u001b[0m \u001b[38;5;28;01mreturn\u001b[39;00m \u001b[38;5;28mself\u001b[39m\u001b[38;5;241m.\u001b[39mconfig\n",
      "File \u001b[0;32m~/Software/MMM/develop/freqtrade/freqtrade/configuration/configuration.py:92\u001b[0m, in \u001b[0;36mConfiguration.load_config\u001b[0;34m(self)\u001b[0m\n\u001b[1;32m     88\u001b[0m \u001b[38;5;28mself\u001b[39m\u001b[38;5;241m.\u001b[39m_process_common_options(config)\n\u001b[1;32m     90\u001b[0m \u001b[38;5;28mself\u001b[39m\u001b[38;5;241m.\u001b[39m_process_trading_options(config)\n\u001b[0;32m---> 92\u001b[0m \u001b[38;5;28;43mself\u001b[39;49m\u001b[38;5;241;43m.\u001b[39;49m\u001b[43m_process_optimize_options\u001b[49m\u001b[43m(\u001b[49m\u001b[43mconfig\u001b[49m\u001b[43m)\u001b[49m\n\u001b[1;32m     94\u001b[0m \u001b[38;5;28mself\u001b[39m\u001b[38;5;241m.\u001b[39m_process_plot_options(config)\n\u001b[1;32m     96\u001b[0m \u001b[38;5;28mself\u001b[39m\u001b[38;5;241m.\u001b[39m_process_data_options(config)\n",
      "File \u001b[0;32m~/Software/MMM/develop/freqtrade/freqtrade/configuration/configuration.py:249\u001b[0m, in \u001b[0;36mConfiguration._process_optimize_options\u001b[0;34m(self, config)\u001b[0m\n\u001b[1;32m    242\u001b[0m \u001b[38;5;28mself\u001b[39m\u001b[38;5;241m.\u001b[39m_args_to_config(config, argname\u001b[38;5;241m=\u001b[39m\u001b[38;5;124m'\u001b[39m\u001b[38;5;124mfee\u001b[39m\u001b[38;5;124m'\u001b[39m,\n\u001b[1;32m    243\u001b[0m                      logstring\u001b[38;5;241m=\u001b[39m\u001b[38;5;124m'\u001b[39m\u001b[38;5;124mParameter --fee detected, \u001b[39m\u001b[38;5;124m'\u001b[39m\n\u001b[1;32m    244\u001b[0m                      \u001b[38;5;124m'\u001b[39m\u001b[38;5;124msetting fee to: \u001b[39m\u001b[38;5;132;01m{}\u001b[39;00m\u001b[38;5;124m ...\u001b[39m\u001b[38;5;124m'\u001b[39m)\n\u001b[1;32m    246\u001b[0m \u001b[38;5;28mself\u001b[39m\u001b[38;5;241m.\u001b[39m_args_to_config(config, argname\u001b[38;5;241m=\u001b[39m\u001b[38;5;124m'\u001b[39m\u001b[38;5;124mtimerange\u001b[39m\u001b[38;5;124m'\u001b[39m,\n\u001b[1;32m    247\u001b[0m                      logstring\u001b[38;5;241m=\u001b[39m\u001b[38;5;124m'\u001b[39m\u001b[38;5;124mParameter --timerange detected: \u001b[39m\u001b[38;5;132;01m{}\u001b[39;00m\u001b[38;5;124m ...\u001b[39m\u001b[38;5;124m'\u001b[39m)\n\u001b[0;32m--> 249\u001b[0m \u001b[38;5;28;43mself\u001b[39;49m\u001b[38;5;241;43m.\u001b[39;49m\u001b[43m_process_datadir_options\u001b[49m\u001b[43m(\u001b[49m\u001b[43mconfig\u001b[49m\u001b[43m)\u001b[49m\n\u001b[1;32m    251\u001b[0m \u001b[38;5;28mself\u001b[39m\u001b[38;5;241m.\u001b[39m_args_to_config(config, argname\u001b[38;5;241m=\u001b[39m\u001b[38;5;124m'\u001b[39m\u001b[38;5;124mstrategy_list\u001b[39m\u001b[38;5;124m'\u001b[39m,\n\u001b[1;32m    252\u001b[0m                      logstring\u001b[38;5;241m=\u001b[39m\u001b[38;5;124m'\u001b[39m\u001b[38;5;124mUsing strategy list of \u001b[39m\u001b[38;5;132;01m{}\u001b[39;00m\u001b[38;5;124m strategies\u001b[39m\u001b[38;5;124m'\u001b[39m, logfun\u001b[38;5;241m=\u001b[39m\u001b[38;5;28mlen\u001b[39m)\n\u001b[1;32m    254\u001b[0m \u001b[38;5;28mself\u001b[39m\u001b[38;5;241m.\u001b[39m_args_to_config(\n\u001b[1;32m    255\u001b[0m     config,\n\u001b[1;32m    256\u001b[0m     argname\u001b[38;5;241m=\u001b[39m\u001b[38;5;124m'\u001b[39m\u001b[38;5;124mrecursive_strategy_search\u001b[39m\u001b[38;5;124m'\u001b[39m,\n\u001b[1;32m    257\u001b[0m     logstring\u001b[38;5;241m=\u001b[39m\u001b[38;5;124m'\u001b[39m\u001b[38;5;124mRecursively searching for a strategy in the strategies folder.\u001b[39m\u001b[38;5;124m'\u001b[39m,\n\u001b[1;32m    258\u001b[0m )\n",
      "File \u001b[0;32m~/Software/MMM/develop/freqtrade/freqtrade/configuration/configuration.py:180\u001b[0m, in \u001b[0;36mConfiguration._process_datadir_options\u001b[0;34m(self, config)\u001b[0m\n\u001b[1;32m    177\u001b[0m     config\u001b[38;5;241m.\u001b[39mupdate({\u001b[38;5;124m'\u001b[39m\u001b[38;5;124muser_data_dir\u001b[39m\u001b[38;5;124m'\u001b[39m: \u001b[38;5;28mstr\u001b[39m(Path\u001b[38;5;241m.\u001b[39mcwd() \u001b[38;5;241m/\u001b[39m \u001b[38;5;124m'\u001b[39m\u001b[38;5;124muser_data\u001b[39m\u001b[38;5;124m'\u001b[39m)})\n\u001b[1;32m    179\u001b[0m \u001b[38;5;66;03m# reset to user_data_dir so this contains the absolute path.\u001b[39;00m\n\u001b[0;32m--> 180\u001b[0m config[\u001b[38;5;124m'\u001b[39m\u001b[38;5;124muser_data_dir\u001b[39m\u001b[38;5;124m'\u001b[39m] \u001b[38;5;241m=\u001b[39m \u001b[43mcreate_userdata_dir\u001b[49m\u001b[43m(\u001b[49m\u001b[43mconfig\u001b[49m\u001b[43m[\u001b[49m\u001b[38;5;124;43m'\u001b[39;49m\u001b[38;5;124;43muser_data_dir\u001b[39;49m\u001b[38;5;124;43m'\u001b[39;49m\u001b[43m]\u001b[49m\u001b[43m,\u001b[49m\u001b[43m \u001b[49m\u001b[43mcreate_dir\u001b[49m\u001b[38;5;241;43m=\u001b[39;49m\u001b[38;5;28;43;01mFalse\u001b[39;49;00m\u001b[43m)\u001b[49m\n\u001b[1;32m    181\u001b[0m logger\u001b[38;5;241m.\u001b[39minfo(\u001b[38;5;124m'\u001b[39m\u001b[38;5;124mUsing user-data directory: \u001b[39m\u001b[38;5;132;01m%s\u001b[39;00m\u001b[38;5;124m ...\u001b[39m\u001b[38;5;124m'\u001b[39m, config[\u001b[38;5;124m'\u001b[39m\u001b[38;5;124muser_data_dir\u001b[39m\u001b[38;5;124m'\u001b[39m])\n\u001b[1;32m    183\u001b[0m config\u001b[38;5;241m.\u001b[39mupdate({\u001b[38;5;124m'\u001b[39m\u001b[38;5;124mdatadir\u001b[39m\u001b[38;5;124m'\u001b[39m: create_datadir(config, \u001b[38;5;28mself\u001b[39m\u001b[38;5;241m.\u001b[39margs\u001b[38;5;241m.\u001b[39mget(\u001b[38;5;124m'\u001b[39m\u001b[38;5;124mdatadir\u001b[39m\u001b[38;5;124m'\u001b[39m, \u001b[38;5;28;01mNone\u001b[39;00m))})\n",
      "File \u001b[0;32m~/Software/MMM/develop/freqtrade/freqtrade/configuration/directory_operations.py:61\u001b[0m, in \u001b[0;36mcreate_userdata_dir\u001b[0;34m(directory, create_dir)\u001b[0m\n\u001b[1;32m     59\u001b[0m         logger\u001b[38;5;241m.\u001b[39minfo(\u001b[38;5;124mf\u001b[39m\u001b[38;5;124m'\u001b[39m\u001b[38;5;124mCreated user-data directory: \u001b[39m\u001b[38;5;132;01m{\u001b[39;00mfolder\u001b[38;5;132;01m}\u001b[39;00m\u001b[38;5;124m'\u001b[39m)\n\u001b[1;32m     60\u001b[0m     \u001b[38;5;28;01melse\u001b[39;00m:\n\u001b[0;32m---> 61\u001b[0m         \u001b[38;5;28;01mraise\u001b[39;00m OperationalException(\n\u001b[1;32m     62\u001b[0m             \u001b[38;5;124mf\u001b[39m\u001b[38;5;124m\"\u001b[39m\u001b[38;5;124mDirectory `\u001b[39m\u001b[38;5;132;01m{\u001b[39;00mfolder\u001b[38;5;132;01m}\u001b[39;00m\u001b[38;5;124m` does not exist. \u001b[39m\u001b[38;5;124m\"\u001b[39m\n\u001b[1;32m     63\u001b[0m             \u001b[38;5;124m\"\u001b[39m\u001b[38;5;124mPlease use `freqtrade create-userdir` to create a user directory\u001b[39m\u001b[38;5;124m\"\u001b[39m)\n\u001b[1;32m     65\u001b[0m \u001b[38;5;66;03m# Create required subdirectories\u001b[39;00m\n\u001b[1;32m     66\u001b[0m \u001b[38;5;28;01mfor\u001b[39;00m f \u001b[38;5;129;01min\u001b[39;00m sub_dirs:\n",
      "\u001b[0;31mOperationalException\u001b[0m: Directory `/Users/surfer/Software/MMM/develop/freqtrade/freqtrade/templates/user_data` does not exist. Please use `freqtrade create-userdir` to create a user directory"
     ]
    }
   ],
   "source": [
    "from pathlib import Path\n",
    "from freqtrade.configuration import Configuration\n",
    "\n",
    "# Customize these according to your needs.\n",
    "\n",
    "# Initialize empty configuration object\n",
    "config = Configuration.from_files([])\n",
    "# Optionally, use existing configuration file\n",
    "# config = Configuration.from_files([\"config.json\"])\n",
    "\n",
    "# Define some constants\n",
    "config[\"timeframe\"] = \"1m\"\n",
    "# Name of the strategy class\n",
    "config[\"strategy\"] = \"MMMOracle\"\n",
    "# Location of the data\n",
    "data_location = Path(config['user_data_dir'], 'data', 'binance')\n",
    "# Pair to analyze - Only use one pair here\n",
    "pair = \"BTC/USDT\""
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": [
    "# Load data using values set above\n",
    "from freqtrade.data.history import load_pair_history\n",
    "\n",
    "candles = load_pair_history(datadir=data_location,\n",
    "                            timeframe=config[\"timeframe\"],\n",
    "                            pair=pair,\n",
    "                            data_format = \"hdf5\",\n",
    "                            )\n",
    "\n",
    "# Confirm success\n",
    "print(\"Loaded \" + str(len(candles)) + f\" rows of data for {pair} from {data_location}\")\n",
    "candles.head()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Load and run strategy\n",
    "* Rerun each time the strategy file is changed"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": [
    "# Load strategy using values set above\n",
    "from freqtrade.resolvers import StrategyResolver\n",
    "from freqtrade.data.dataprovider import DataProvider\n",
    "strategy = StrategyResolver.load_strategy(config)\n",
    "strategy.dp = DataProvider(config, None, None)\n",
    "\n",
    "# Generate buy/sell signals using strategy\n",
    "df = strategy.analyze_ticker(candles, {'pair': pair})\n",
    "df.tail()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### Display the trade details\n",
    "\n",
    "* Note that using `data.head()` would also work, however most indicators have some \"startup\" data at the top of the dataframe.\n",
    "* Some possible problems\n",
    "    * Columns with NaN values at the end of the dataframe\n",
    "    * Columns used in `crossed*()` functions with completely different units\n",
    "* Comparison with full backtest\n",
    "    * having 200 buy signals as output for one pair from `analyze_ticker()` does not necessarily mean that 200 trades will be made during backtesting.\n",
    "    * Assuming you use only one condition such as, `df['rsi'] < 30` as buy condition, this will generate multiple \"buy\" signals for each pair in sequence (until rsi returns > 29). The bot will only buy on the first of these signals (and also only if a trade-slot (\"max_open_trades\") is still available), or on one of the middle signals, as soon as a \"slot\" becomes available.  \n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": [
    "# Report results\n",
    "print(f\"Generated {df['enter_long'].sum()} entry signals\")\n",
    "data = df.set_index('date', drop=False)\n",
    "data.tail()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Load existing objects into a Jupyter notebook\n",
    "\n",
    "The following cells assume that you have already generated data using the cli.  \n",
    "They will allow you to drill deeper into your results, and perform analysis which otherwise would make the output very difficult to digest due to information overload."
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### Load backtest results to pandas dataframe\n",
    "\n",
    "Analyze a trades dataframe (also used below for plotting)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 3,
   "metadata": {},
   "outputs": [
    {
     "ename": "NameError",
     "evalue": "name 'config' is not defined",
     "output_type": "error",
     "traceback": [
      "\u001b[0;31m---------------------------------------------------------------------------\u001b[0m",
      "\u001b[0;31mNameError\u001b[0m                                 Traceback (most recent call last)",
      "Input \u001b[0;32mIn [3]\u001b[0m, in \u001b[0;36m<cell line: 4>\u001b[0;34m()\u001b[0m\n\u001b[1;32m      1\u001b[0m \u001b[38;5;28;01mfrom\u001b[39;00m \u001b[38;5;21;01mfreqtrade\u001b[39;00m\u001b[38;5;21;01m.\u001b[39;00m\u001b[38;5;21;01mdata\u001b[39;00m\u001b[38;5;21;01m.\u001b[39;00m\u001b[38;5;21;01mbtanalysis\u001b[39;00m \u001b[38;5;28;01mimport\u001b[39;00m load_backtest_data, load_backtest_stats\n\u001b[1;32m      3\u001b[0m \u001b[38;5;66;03m# if backtest_dir points to a directory, it'll automatically load the last backtest file.\u001b[39;00m\n\u001b[0;32m----> 4\u001b[0m backtest_dir \u001b[38;5;241m=\u001b[39m \u001b[43mconfig\u001b[49m[\u001b[38;5;124m\"\u001b[39m\u001b[38;5;124muser_data_dir\u001b[39m\u001b[38;5;124m\"\u001b[39m] \u001b[38;5;241m/\u001b[39m \u001b[38;5;124m\"\u001b[39m\u001b[38;5;124mbacktest_results\u001b[39m\u001b[38;5;124m\"\u001b[39m\n",
      "\u001b[0;31mNameError\u001b[0m: name 'config' is not defined"
     ]
    }
   ],
   "source": [
    "from freqtrade.data.btanalysis import load_backtest_data, load_backtest_stats\n",
    "\n",
    "# if backtest_dir points to a directory, it'll automatically load the last backtest file.\n",
    "backtest_dir = config[\"user_data_dir\"] / \"backtest_results\"\n",
    "# backtest_dir can also point to a specific file \n",
    "# backtest_dir = config[\"user_data_dir\"] / \"backtest_results/backtest-result-2020-07-01_20-04-22.json\""
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": [
    "# You can get the full backtest statistics by using the following command.\n",
    "# This contains all information used to generate the backtest result.\n",
    "stats = load_backtest_stats(backtest_dir)\n",
    "\n",
    "strategy = 'SampleStrategy'\n",
    "# All statistics are available per strategy, so if `--strategy-list` was used during backtest, this will be reflected here as well.\n",
    "# Example usages:\n",
    "print(stats['strategy'][strategy]['results_per_pair'])\n",
    "# Get pairlist used for this backtest\n",
    "print(stats['strategy'][strategy]['pairlist'])\n",
    "# Get market change (average change of all pairs from start to end of the backtest period)\n",
    "print(stats['strategy'][strategy]['market_change'])\n",
    "# Maximum drawdown ()\n",
    "print(stats['strategy'][strategy]['max_drawdown'])\n",
    "# Maximum drawdown start and end\n",
    "print(stats['strategy'][strategy]['drawdown_start'])\n",
    "print(stats['strategy'][strategy]['drawdown_end'])\n",
    "\n",
    "\n",
    "# Get strategy comparison (only relevant if multiple strategies were compared)\n",
    "print(stats['strategy_comparison'])\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": [
    "# Load backtested trades as dataframe\n",
    "trades = load_backtest_data(backtest_dir)\n",
    "\n",
    "# Show value-counts per pair\n",
    "trades.groupby(\"pair\")[\"exit_reason\"].value_counts()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Plotting daily profit / equity line"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": [
    "# Plotting equity line (starting with 0 on day 1 and adding daily profit for each backtested day)\n",
    "\n",
    "from freqtrade.configuration import Configuration\n",
    "from freqtrade.data.btanalysis import load_backtest_data, load_backtest_stats\n",
    "import plotly.express as px\n",
    "import pandas as pd\n",
    "\n",
    "# strategy = 'SampleStrategy'\n",
    "# config = Configuration.from_files([\"user_data/config.json\"])\n",
    "# backtest_dir = config[\"user_data_dir\"] / \"backtest_results\"\n",
    "\n",
    "stats = load_backtest_stats(backtest_dir)\n",
    "strategy_stats = stats['strategy'][strategy]\n",
    "\n",
    "dates = []\n",
    "profits = []\n",
    "for date_profit in strategy_stats['daily_profit']:\n",
    "    dates.append(date_profit[0])\n",
    "    profits.append(date_profit[1])\n",
    "\n",
    "equity = 0\n",
    "equity_daily = []\n",
    "for daily_profit in profits:\n",
    "    equity_daily.append(equity)\n",
    "    equity += float(daily_profit)\n",
    "\n",
    "\n",
    "df = pd.DataFrame({'dates': dates,'equity_daily': equity_daily})\n",
    "\n",
    "fig = px.line(df, x=\"dates\", y=\"equity_daily\")\n",
    "fig.show()\n"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### Load live trading results into a pandas dataframe\n",
    "\n",
    "In case you did already some trading and want to analyze your performance"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 4,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "Series([], Name: exit_reason, dtype: int64)"
      ]
     },
     "execution_count": 4,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "from freqtrade.data.btanalysis import load_trades_from_db\n",
    "\n",
    "# Fetch trades from database\n",
    "trades = load_trades_from_db(\"sqlite:///tradesv3.sqlite\")\n",
    "\n",
    "# Display results\n",
    "trades.groupby(\"pair\")[\"exit_reason\"].value_counts()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Analyze the loaded trades for trade parallelism\n",
    "This can be useful to find the best `max_open_trades` parameter, when used with backtesting in conjunction with `--disable-max-market-positions`.\n",
    "\n",
    "`analyze_trade_parallelism()` returns a timeseries dataframe with an \"open_trades\" column, specifying the number of open trades for each candle."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": [
    "from freqtrade.data.btanalysis import analyze_trade_parallelism\n",
    "\n",
    "# Analyze the above\n",
    "parallel_trades = analyze_trade_parallelism(trades, '5m')\n",
    "\n",
    "parallel_trades.plot()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Plot results\n",
    "\n",
    "Freqtrade offers interactive plotting capabilities based on plotly."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": [
    "from freqtrade.plot.plotting import  generate_candlestick_graph\n",
    "# Limit graph period to keep plotly quick and reactive\n",
    "\n",
    "# Filter trades to one pair\n",
    "trades_red = trades.loc[trades['pair'] == pair]\n",
    "\n",
    "data_red = data['2019-06-01':'2019-06-10']\n",
    "# Generate candlestick graph\n",
    "graph = generate_candlestick_graph(pair=pair,\n",
    "                                   data=data_red,\n",
    "                                   trades=trades_red,\n",
    "                                   indicators1=['sma20', 'ema50', 'ema55'],\n",
    "                                   indicators2=['rsi', 'macd', 'macdsignal', 'macdhist']\n",
    "                                  )\n",
    "\n",
    "\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": [
    "# Show graph inline\n",
    "# graph.show()\n",
    "\n",
    "# Render graph in a seperate window\n",
    "graph.show(renderer=\"browser\")\n"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Plot average profit per trade as distribution graph"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": [
    "import plotly.figure_factory as ff\n",
    "\n",
    "hist_data = [trades.profit_ratio]\n",
    "group_labels = ['profit_ratio']  # name of the dataset\n",
    "\n",
    "fig = ff.create_distplot(hist_data, group_labels, bin_size=0.01)\n",
    "fig.show()\n"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Feel free to submit an issue or Pull Request enhancing this document if you would like to share ideas on how to best analyze the data."
   ]
  }
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