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<h1 id="plotting">Plotting<a class="headerlink" href="#plotting" title="Permanent link">&para;</a></h1>
<p>This page explains how to plot prices, indicators and profits.</p>
<h2 id="installation">Installation<a class="headerlink" href="#installation" title="Permanent link">&para;</a></h2>
<p>Plotting scripts use Plotly library. Install/upgrade it with:</p>
<div class="highlight"><pre><span></span><code>pip<span class="w"> </span>install<span class="w"> </span>-U<span class="w"> </span>-r<span class="w"> </span>requirements-plot.txt
</code></pre></div>
<h2 id="plot-price-and-indicators">Plot price and indicators<a class="headerlink" href="#plot-price-and-indicators" title="Permanent link">&para;</a></h2>
<p>Usage for the price plotter:</p>
<div class="highlight"><pre><span></span><code>python3<span class="w"> </span>script/plot_dataframe.py<span class="w"> </span><span class="o">[</span>-h<span class="o">]</span><span class="w"> </span><span class="o">[</span>-p<span class="w"> </span>pairs<span class="o">]</span>
</code></pre></div>
<p>Example</p>
<div class="highlight"><pre><span></span><code>python3<span class="w"> </span>scripts/plot_dataframe.py<span class="w"> </span>-p<span class="w"> </span>BTC/ETH
</code></pre></div>
<p>The <code>-p</code> pairs argument can be used to specify pairs you would like to plot.</p>
<p>Specify custom indicators.
Use <code>--indicators1</code> for the main plot and <code>--indicators2</code> for the subplot below (if values are in a different range than prices).</p>
<div class="highlight"><pre><span></span><code>python3<span class="w"> </span>scripts/plot_dataframe.py<span class="w"> </span>-p<span class="w"> </span>BTC/ETH<span class="w"> </span>--indicators1<span class="w"> </span>sma,ema<span class="w"> </span>--indicators2<span class="w"> </span>macd
</code></pre></div>
<h3 id="advanced-use">Advanced use<a class="headerlink" href="#advanced-use" title="Permanent link">&para;</a></h3>
<p>To plot multiple pairs, separate them with a comma:</p>
<div class="highlight"><pre><span></span><code>python3<span class="w"> </span>scripts/plot_dataframe.py<span class="w"> </span>-p<span class="w"> </span>BTC/ETH,XRP/ETH
</code></pre></div>
<p>To plot a timerange (to zoom in):</p>
<div class="highlight"><pre><span></span><code>python3<span class="w"> </span>scripts/plot_dataframe.py<span class="w"> </span>-p<span class="w"> </span>BTC/ETH<span class="w"> </span>--timerange<span class="o">=</span><span class="m">20180801</span>-20180805
</code></pre></div>
<p>To plot trades stored in a database use <code>--db-url</code> argument:</p>
<div class="highlight"><pre><span></span><code>python3<span class="w"> </span>scripts/plot_dataframe.py<span class="w"> </span>--db-url<span class="w"> </span>sqlite:///tradesv3.dry_run.sqlite<span class="w"> </span>-p<span class="w"> </span>BTC/ETH<span class="w"> </span>--trade-source<span class="w"> </span>DB
</code></pre></div>
<p>To plot trades from a backtesting result, use <code>--export-filename &lt;filename&gt;</code></p>
<div class="highlight"><pre><span></span><code>python3<span class="w"> </span>scripts/plot_dataframe.py<span class="w"> </span>--export-filename<span class="w"> </span>user_data/backtest_results/backtest-result.json<span class="w"> </span>-p<span class="w"> </span>BTC/ETH
</code></pre></div>
<p>To plot a custom strategy the strategy should have first be backtested.
The results may then be plotted with the -s argument:</p>
<div class="highlight"><pre><span></span><code>python3<span class="w"> </span>scripts/plot_dataframe.py<span class="w"> </span>-s<span class="w"> </span>Strategy_Name<span class="w"> </span>-p<span class="w"> </span>BTC/ETH<span class="w"> </span>--datadir<span class="w"> </span>user_data/data/&lt;exchange_name&gt;/
</code></pre></div>
<h2 id="plot-profit">Plot profit<a class="headerlink" href="#plot-profit" title="Permanent link">&para;</a></h2>
<p>The profit plotter shows a picture with three plots:</p>
<p>1) Average closing price for all pairs
2) The summarized profit made by backtesting.
Note that this is not the real-world profit, but
more of an estimate.
3) Each pair individually profit</p>
<p>The first graph is good to get a grip of how the overall market
progresses.</p>
<p>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.</p>
<p>The third graph can be useful to spot outliers, events in pairs
that makes profit spikes.</p>
<p>Usage for the profit plotter:</p>
<div class="highlight"><pre><span></span><code>python3<span class="w"> </span>script/plot_profit.py<span class="w"> </span><span class="o">[</span>-h<span class="o">]</span><span class="w"> </span><span class="o">[</span>-p<span class="w"> </span>pair<span class="o">]</span><span class="w"> </span><span class="o">[</span>--datadir<span class="w"> </span>directory<span class="o">]</span><span class="w"> </span><span class="o">[</span>--ticker_interval<span class="w"> </span>num<span class="o">]</span>
</code></pre></div>
<p>The <code>-p</code> pair argument, can be used to plot a single pair</p>
<p>Example</p>
<div class="highlight"><pre><span></span><code>python3<span class="w"> </span>scripts/plot_profit.py<span class="w"> </span>--datadir<span class="w"> </span>../freqtrade/freqtrade/tests/testdata-20171221/<span class="w"> </span>-p<span class="w"> </span>LTC/BTC
</code></pre></div>
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