This page explains how to plot prices, indicator, profits.
Plotting scripts use Plotly library. Install/upgrade it with:
pip install --upgrade plotly
At least version 2.3.0 is required.
Usage for the price plotter:
script/plot_dataframe.py [-h] [-p pair] [--live]
Example
python scripts/plot_dataframe.py -p BTC_ETH
The -p pair argument, can be used to specify what
pair you would like to plot.
Advanced use
To plot the current live price use the --live flag:
python scripts/plot_dataframe.py -p BTC_ETH --live
To plot a timerange (to zoom in):
python scripts/plot_dataframe.py -p BTC_ETH --timerange=100-200
Timerange doesn't work with live data.
To plot trades stored in a database use --db-url argument:
python scripts/plot_dataframe.py --db-url tradesv3.dry_run.sqlite -p BTC_ETH
To plot a test strategy the strategy should have first be backtested. The results may then be plotted with the -s argument:
python scripts/plot_dataframe.py -s Strategy_Name -p BTC/ETH --datadir user_data/data/<exchange_name>/
The profit plotter show a picture with three plots:
- Average closing price for all pairs
- The summarized profit made by backtesting. Note that this is not the real-world profit, but more of an estimate.
- Each pair individually profit
The first graph is good to get a grip of how the overall market progresses.
The second graph will show how you algorithm works or doesnt. Perhaps you want an algorithm that steadily makes small profits, or one that acts less seldom, but makes big swings.
The third graph can be useful to spot outliers, events in pairs that makes profit spikes.
Usage for the profit plotter:
script/plot_profit.py [-h] [-p pair] [--datadir directory] [--ticker_interval num]
The -p pair argument, can be used to plot a single pair
Example
python3 scripts/plot_profit.py --datadir ../freqtrade/freqtrade/tests/testdata-20171221/ -p BTC_LTC