Plotting

This page explains how to plot prices, indicators and profits.

Installation

Plotting scripts use Plotly library. Install/upgrade it with:

pip install -U -r requirements-plot.txt

Plot price and indicators

Usage for the price plotter:

python3 script/plot_dataframe.py [-h] [-p pairs] [--live]

Example

python3 scripts/plot_dataframe.py -p BTC/ETH

The -p pairs argument can be used to specify pairs you would like to plot.

Specify custom indicators. Use --indicators1 for the main plot and --indicators2 for the subplot below (if values are in a different range than prices).

python3 scripts/plot_dataframe.py -p BTC/ETH --indicators1 sma,ema --indicators2 macd

Advanced use

To plot multiple pairs, separate them with a comma:

python3 scripts/plot_dataframe.py -p BTC/ETH,XRP/ETH

To plot the current live price use the --live flag:

python3 scripts/plot_dataframe.py -p BTC/ETH --live

To plot a timerange (to zoom in):

python3 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:

python3 scripts/plot_dataframe.py --db-url sqlite:///tradesv3.dry_run.sqlite -p BTC/ETH --trade-source DB

To plot trades from a backtesting result, use --export-filename <filename>

python3 scripts/plot_dataframe.py --export-filename user_data/backtest_data/backtest-result.json -p BTC/ETH

To plot a custom strategy the strategy should have first be backtested. The results may then be plotted with the -s argument:

python3 scripts/plot_dataframe.py -s Strategy_Name -p BTC/ETH --datadir user_data/data/<exchange_name>/

Plot profit

The profit plotter shows 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 your algorithm works or doesn't. 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:

python3 script/plot_profit.py [-h] [-p pair] [--datadir directory] [--ticker_interval num]

The -p pair argument, can be used to plot a single pair