freqtrade_origin/user_data/notebooks/analysis_example.ipynb

{
 "cells": [
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Strategy debugging example"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": [
    "# Change directory\n",
    "# Define all paths relative to the project root shown in the cell output\n",
    "import os\n",
    "from pathlib import Path\n",
    "try:\n",
    "\tos.chdir(Path(os.getcwd(), '../..'))\n",
    "\tprint(os.getcwd())\n",
    "except:\n",
    "\tpass"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### Import requirements and define variables used in the script"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": [
    "# Imports\n",
    "from pathlib import Path\n",
    "from freqtrade.data.history import load_pair_history\n",
    "from freqtrade.resolvers import StrategyResolver\n",
    "from freqtrade.data.btanalysis import load_backtest_data\n",
    "from freqtrade.data.btanalysis import load_trades_from_db\n",
    "\n",
    "# Define some constants\n",
    "ticker_interval = \"1m\"\n",
    "# Name of the strategy class\n",
    "strategy_name = 'NewStrategy'\n",
    "# Path to user data\n",
    "user_data_dir = 'user_data'\n",
    "# Location of the strategy\n",
    "strategy_location = Path(user_data_dir, 'strategies')\n",
    "# Location of the data\n",
    "data_location = Path(user_data_dir, 'data', 'binance')\n",
    "# Pair to analyze \n",
    "# Only use one pair here\n",
    "pair = \"BTC_USDT\""
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### Load exchange data"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": [
    "# Load data using values set above\n",
    "bt_data = load_pair_history(datadir=Path(data_location),\n",
    "                            ticker_interval=ticker_interval,\n",
    "                            pair=pair)\n",
    "\n",
    "# Confirm success\n",
    "print(\"Loaded \" + str(len(bt_data)) + f\" rows of data for {pair} from {data_location}\")"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### Load and run strategy  \n",
    "\n",
    "* Rerun each time the strategy file is changed\n",
    "* Display the trade details. Note that using `data.head()` would also work, however most indicators have some \"startup\" data at the top of the dataframe.\n",
    "\n",
    "Some possible problems:\n",
    "\n",
    "* Columns with NaN values at the end of the dataframe\n",
    "* Columns used in `crossed*()` functions with completely different units"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": [
    "# Load strategy using values set above\n",
    "strategy = StrategyResolver({'strategy': strategy_name,\n",
    "                            'user_data_dir': user_data_dir,\n",
    "                            'strategy_path': strategy_location}).strategy\n",
    "\n",
    "# Run strategy (just like in backtesting)\n",
    "df = strategy.analyze_ticker(bt_data, {'pair': pair})\n",
    "\n",
    "# Report results\n",
    "print(f\"Generated {df['buy'].sum()} buy signals\")\n",
    "data = df.set_index('date', drop=True)\n",
    "data.tail()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### Load backtest results into a pandas dataframe"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": [
    "# Load backtest results\n",
    "df = load_backtest_data(\"user_data/backtest_data/backtest-result.json\")\n",
    "\n",
    "# Show value-counts per pair\n",
    "df.groupby(\"pair\")[\"sell_reason\"].value_counts()\n"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### Load live trading results into a pandas dataframe"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": [
    "# Fetch trades from database\n",
    "df = load_trades_from_db(\"sqlite:///tradesv3.sqlite\")\n",
    "\n",
    "# Display results\n",
    "df.groupby(\"pair\")[\"sell_reason\"].value_counts()"
   ]
  }
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