102 lines
2.5 KiB
Markdown
102 lines
2.5 KiB
Markdown
# Plotting
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This page explains how to plot prices, indicators and profits.
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## Installation
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Plotting scripts use Plotly library. Install/upgrade it with:
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``` bash
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pip install -U -r requirements-plot.txt
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```
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## Plot price and indicators
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Usage for the price plotter:
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``` bash
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python3 script/plot_dataframe.py [-h] [-p pairs]
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```
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Example
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``` bash
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python3 scripts/plot_dataframe.py -p BTC/ETH
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```
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The `-p` pairs argument can be used to specify pairs you would like to plot.
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Specify custom indicators.
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Use `--indicators1` for the main plot and `--indicators2` for the subplot below (if values are in a different range than prices).
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``` bash
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python3 scripts/plot_dataframe.py -p BTC/ETH --indicators1 sma,ema --indicators2 macd
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```
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### Advanced use
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To plot multiple pairs, separate them with a comma:
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``` bash
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python3 scripts/plot_dataframe.py -p BTC/ETH,XRP/ETH
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```
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To plot a timerange (to zoom in):
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``` bash
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python3 scripts/plot_dataframe.py -p BTC/ETH --timerange=20180801-20180805
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```
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To plot trades stored in a database use `--db-url` argument:
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``` bash
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python3 scripts/plot_dataframe.py --db-url sqlite:///tradesv3.dry_run.sqlite -p BTC/ETH --trade-source DB
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```
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To plot trades from a backtesting result, use `--export-filename <filename>`
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``` bash
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python3 scripts/plot_dataframe.py --export-filename user_data/backtest_results/backtest-result.json -p BTC/ETH
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```
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To plot a custom strategy the strategy should have first be backtested.
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The results may then be plotted with the -s argument:
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``` bash
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python3 scripts/plot_dataframe.py -s Strategy_Name -p BTC/ETH --datadir user_data/data/<exchange_name>/
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```
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## Plot profit
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The profit plotter shows a picture with three plots:
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1) Average closing price for all pairs
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2) The summarized profit made by backtesting.
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Note that this is not the real-world profit, but
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more of an estimate.
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3) Each pair individually profit
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The first graph is good to get a grip of how the overall market
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progresses.
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The second graph will show how your algorithm works or doesn't.
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Perhaps you want an algorithm that steadily makes small profits,
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or one that acts less seldom, but makes big swings.
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The third graph can be useful to spot outliers, events in pairs
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that makes profit spikes.
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Usage for the profit plotter:
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``` bash
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python3 script/plot_profit.py [-h] [-p pair] [--datadir directory] [--ticker_interval num]
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```
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The `-p` pair argument, can be used to plot a single pair
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Example
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``` bash
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python3 scripts/plot_profit.py --datadir ../freqtrade/freqtrade/tests/testdata-20171221/ -p LTC/BTC
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```
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