Add documentation sample for parallel_trade_analysis

docs/strategy_analysis_example.md

@@ -107,6 +107,22 @@ trades = load_trades_from_db("sqlite:///tradesv3.sqlite")
 trades.groupby("pair")["sell_reason"].value_counts()
 ```
 
+## Analyze the loaded trades for trade parallelism
+This can be useful to find the best `max_open_trades` parameter, when used with backtesting in conjunction with `--disable-max-market-positions`.
+
+`parallel_trade_analysis()` returns a timeseries dataframe with an "open_trades" column, specifying the number of open trades for each candle.
+
+
+```python
+from freqtrade.data.btanalysis import parallel_trade_analysis
+
+# Analyze the above
+parallel_trades = parallel_trade_analysis(trades, '5m')
+
+
+parallel_trades.plot()
+```
+
 ## Plot results
 
 Freqtrade offers interactive plotting capabilities based on plotly.

user_data/notebooks/strategy_analysis_example.ipynb

@@ -68,9 +68,7 @@
   {
    "cell_type": "code",
    "execution_count": null,
-   "metadata": {
-    "scrolled": true
-   },
+   "metadata": {},
    "outputs": [],
    "source": [
     "# Load strategy using values set above\n",
@@ -169,6 +167,31 @@
     "trades.groupby(\"pair\")[\"sell_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",
+    "`parallel_trade_analysis()` 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 parallel_trade_analysis\n",
+    "\n",
+    "# Analyze the above\n",
+    "parallel_trades = parallel_trade_analysis(trades, '5m')\n",
+    "\n",
+    "\n",
+    "parallel_trades.plot()"
+   ]
+  },
   {
    "cell_type": "markdown",
    "metadata": {},