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<!DOCTYPE html>

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to download the full example code.</p>

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<span id="sphx-glr-tutorials-lifecycle-py"></span><h1>The Lifecycle of a Plot<a class="headerlink" href="#the-lifecycle-of-a-plot" title="Link to this heading">#</a></h1>

<p>This tutorial aims to show the beginning, middle, and end of a single

visualization using Matplotlib. We'll begin with some raw data and

end by saving a figure of a customized visualization. Along the way we try

to highlight some neat features and best-practices using Matplotlib.</p>

<p>This tutorial is based on

<a class="reference external" href="https://pbpython.com/effective-matplotlib.html">this excellent blog post</a>

by Chris Moffitt. It was transformed into this tutorial by Chris Holdgraf.</p>

</div>

<h2>A note on the explicit vs. implicit interfaces<a class="headerlink" href="#a-note-on-the-explicit-vs-implicit-interfaces" title="Link to this heading">#</a></h2>

<p>Matplotlib has two interfaces. For an explanation of the trade-offs between the

explicit and implicit interfaces see <a class="reference internal" href="../users/explain/figure/api_interfaces.html#api-interfaces"><span class="std std-ref">Matplotlib Application Interfaces (APIs)</span></a>.</p>

<p>In the explicit object-oriented (OO) interface we directly utilize instances of

<a class="reference internal" href="../api/_as_gen/matplotlib.axes.Axes.html#matplotlib.axes.Axes" title="matplotlib.axes.Axes"><code class="xref py py-class docutils literal notranslate"><span class="pre">axes.Axes</span></code></a> to build up the visualization in an instance of

<a class="reference internal" href="../api/_as_gen/matplotlib.figure.Figure.html#matplotlib.figure.Figure" title="matplotlib.figure.Figure"><code class="xref py py-class docutils literal notranslate"><span class="pre">figure.Figure</span></code></a>. In the implicit interface, inspired by and modeled on

MATLAB, we use a global state-based interface which is encapsulated in the

<a class="reference internal" href="../api/pyplot_summary.html#module-matplotlib.pyplot" title="matplotlib.pyplot"><code class="xref py py-mod docutils literal notranslate"><span class="pre">pyplot</span></code></a> module to plot to the "current Axes". See the <a class="reference internal" href="pyplot.html#pyplot-tutorial"><span class="std std-ref">pyplot

tutorials</span></a> for a more in-depth look at the

pyplot interface.</p>

<p>Most of the terms are straightforward but the main thing to remember

is that:</p>

<li><p>The <a class="reference internal" href="../api/_as_gen/matplotlib.figure.Figure.html#matplotlib.figure.Figure" title="matplotlib.figure.Figure"><code class="xref py py-obj docutils literal notranslate"><span class="pre">Figure</span></code></a> is the final image, and may contain one or more <a class="reference internal" href="../api/_as_gen/matplotlib.axes.Axes.html#matplotlib.axes.Axes" title="matplotlib.axes.Axes"><code class="xref py py-obj docutils literal notranslate"><span class="pre">Axes</span></code></a>.</p></li>

<dt>The <a class="reference internal" href="../api/_as_gen/matplotlib.axes.Axes.html#matplotlib.axes.Axes" title="matplotlib.axes.Axes"><code class="xref py py-obj docutils literal notranslate"><span class="pre">Axes</span></code></a> represents an individual plot (not to be confused with</dt><dd><p><a class="reference internal" href="../api/axis_api.html#matplotlib.axis.Axis" title="matplotlib.axis.Axis"><code class="xref py py-obj docutils literal notranslate"><span class="pre">Axis</span></code></a>, which refers to the x-, y-, or z-axis of a plot).</p>

</dd>

</dl>

</li>

</ul>

<p>We call methods that do the plotting directly from the Axes, which gives

us much more flexibility and power in customizing our plot.</p>

<p>In general, use the explicit interface over the implicit pyplot interface

for plotting.</p>

</div>

</section>

<p>We'll use the data from the post from which this tutorial was derived.

It contains sales information for a number of companies.</p>

<div class="highlight-Python notranslate"><div class="highlight"><pre><span></span><span class="kn">import</span> <span class="nn">matplotlib.pyplot</span> <span class="k">as</span> <span class="nn">plt</span>

<span class="kn">import</span> <span class="nn">numpy</span> <span class="k">as</span> <span class="nn">np</span>

<a href="https://docs.python.org/3/library/stdtypes.html#dict" title="builtins.dict" class="sphx-glr-backref-module-builtins sphx-glr-backref-type-py-class sphx-glr-backref-instance"><span class="n">data</span></a> <span class="o">=</span> <span class="p">{</span><span class="s1">'Barton LLC'</span><span class="p">:</span> <span class="mf">109438.50</span><span class="p">,</span>

<span class="s1">'Frami, Hills and Schmidt'</span><span class="p">:</span> <span class="mf">103569.59</span><span class="p">,</span>

<span class="s1">'Fritsch, Russel and Anderson'</span><span class="p">:</span> <span class="mf">112214.71</span><span class="p">,</span>

<span class="s1">'Jerde-Hilpert'</span><span class="p">:</span> <span class="mf">112591.43</span><span class="p">,</span>

<span class="s1">'Keeling LLC'</span><span class="p">:</span> <span class="mf">100934.30</span><span class="p">,</span>

<span class="s1">'Koepp Ltd'</span><span class="p">:</span> <span class="mf">103660.54</span><span class="p">,</span>

<span class="s1">'Kulas Inc'</span><span class="p">:</span> <span class="mf">137351.96</span><span class="p">,</span>

<span class="s1">'Trantow-Barrows'</span><span class="p">:</span> <span class="mf">123381.38</span><span class="p">,</span>

<span class="s1">'White-Trantow'</span><span class="p">:</span> <span class="mf">135841.99</span><span class="p">,</span>

<a href="https://docs.python.org/3/library/stdtypes.html#list" title="builtins.list" class="sphx-glr-backref-module-builtins sphx-glr-backref-type-py-class sphx-glr-backref-instance"><span class="n">group_data</span></a> <span class="o">=</span> <span class="nb">list</span><span class="p">(</span><a href="https://docs.python.org/3/library/stdtypes.html#dict" title="builtins.dict" class="sphx-glr-backref-module-builtins sphx-glr-backref-type-py-class sphx-glr-backref-instance"><span class="n">data</span></a><span class="o">.</span><span class="n">values</span><span class="p">())</span>

<a href="https://docs.python.org/3/library/stdtypes.html#list" title="builtins.list" class="sphx-glr-backref-module-builtins sphx-glr-backref-type-py-class sphx-glr-backref-instance"><span class="n">group_names</span></a> <span class="o">=</span> <span class="nb">list</span><span class="p">(</span><a href="https://docs.python.org/3/library/stdtypes.html#dict" title="builtins.dict" class="sphx-glr-backref-module-builtins sphx-glr-backref-type-py-class sphx-glr-backref-instance"><span class="n">data</span></a><span class="o">.</span><span class="n">keys</span><span class="p">())</span>

<a href="https://numpy.org/doc/stable/reference/arrays.scalars.html#numpy.float64" title="numpy.float64" class="sphx-glr-backref-module-numpy sphx-glr-backref-type-py-attribute"><span class="n">group_mean</span></a> <span class="o">=</span> <a href="https://numpy.org/doc/stable/reference/generated/numpy.mean.html#numpy.mean" title="numpy.mean" class="sphx-glr-backref-module-numpy sphx-glr-backref-type-py-function"><span class="n">np</span><span class="o">.</span><span class="n">mean</span></a><span class="p">(</span><a href="https://docs.python.org/3/library/stdtypes.html#list" title="builtins.list" class="sphx-glr-backref-module-builtins sphx-glr-backref-type-py-class sphx-glr-backref-instance"><span class="n">group_data</span></a><span class="p">)</span>

</pre></div>

</div>

</section>

<h2>Getting started<a class="headerlink" href="#getting-started" title="Link to this heading">#</a></h2>

<p>This data is naturally visualized as a barplot, with one bar per

group. To do this with the object-oriented approach, we first generate

an instance of <a class="reference internal" href="../api/_as_gen/matplotlib.figure.Figure.html#matplotlib.figure.Figure" title="matplotlib.figure.Figure"><code class="xref py py-class docutils literal notranslate"><span class="pre">figure.Figure</span></code></a> and

is a part of that canvas on which we will make a particular visualization.</p>

<p>Figures can have multiple Axes on them. For information on how to do this,

see the <a class="reference internal" href="../users/explain/axes/tight_layout_guide.html#tight-layout-guide"><span class="std std-ref">Tight Layout tutorial</span></a>.</p>

</div>

<div class="highlight-Python notranslate"><div class="highlight"><pre><span></span><a href="../api/_as_gen/matplotlib.figure.Figure.html#matplotlib.figure.Figure" title="matplotlib.figure.Figure" class="sphx-glr-backref-module-matplotlib-figure sphx-glr-backref-type-py-class sphx-glr-backref-instance"><span class="n">fig</span></a><span class="p">,</span> <a href="../api/_as_gen/matplotlib.axes.Axes.html#matplotlib.axes.Axes" title="matplotlib.axes.Axes" class="sphx-glr-backref-module-matplotlib-axes sphx-glr-backref-type-py-class sphx-glr-backref-instance"><span class="n">ax</span></a> <span class="o">=</span> <a href="../api/_as_gen/matplotlib.pyplot.subplots.html#matplotlib.pyplot.subplots" title="matplotlib.pyplot.subplots" class="sphx-glr-backref-module-matplotlib-pyplot sphx-glr-backref-type-py-function"><span class="n">plt</span><span class="o">.</span><span class="n">subplots</span></a><span class="p">()</span>

</pre></div>

</div>

<img src="../_images/sphx_glr_lifecycle_001.png" srcset="../_images/sphx_glr_lifecycle_001.png, ../_images/sphx_glr_lifecycle_001_2_00x.png 2.00x" alt="lifecycle" class = "sphx-glr-single-img"/><p>Now that we have an Axes instance, we can plot on top of it.</p>

<a href="../api/_as_gen/matplotlib.axes.Axes.barh.html#matplotlib.axes.Axes.barh" title="matplotlib.axes.Axes.barh" class="sphx-glr-backref-module-matplotlib-axes sphx-glr-backref-type-py-method"><span class="n">ax</span><span class="o">.</span><span class="n">barh</span></a><span class="p">(</span><a href="https://docs.python.org/3/library/stdtypes.html#list" title="builtins.list" class="sphx-glr-backref-module-builtins sphx-glr-backref-type-py-class sphx-glr-backref-instance"><span class="n">group_names</span></a><span class="p">,</span> <a href="https://docs.python.org/3/library/stdtypes.html#list" title="builtins.list" class="sphx-glr-backref-module-builtins sphx-glr-backref-type-py-class sphx-glr-backref-instance"><span class="n">group_data</span></a><span class="p">)</span>

</pre></div>

</div>

<h2>Controlling the style<a class="headerlink" href="#controlling-the-style" title="Link to this heading">#</a></h2>

<p>There are many styles available in Matplotlib in order to let you tailor

your visualization to your needs. To see a list of styles, we can use

<a class="reference internal" href="../api/style_api.html#module-matplotlib.style" title="matplotlib.style"><code class="xref py py-mod docutils literal notranslate"><span class="pre">style</span></code></a>.</p>

<div class="highlight-Python notranslate"><div class="highlight"><pre><span></span><span class="nb">print</span><span class="p">(</span><a href="https://docs.python.org/3/library/stdtypes.html#list" title="builtins.list" class="sphx-glr-backref-module-builtins sphx-glr-backref-type-py-class sphx-glr-backref-instance"><span class="n">plt</span><span class="o">.</span><span class="n">style</span><span class="o">.</span><span class="n">available</span></a><span class="p">)</span>

</pre></div>

</div>

<div class="sphx-glr-script-out highlight-none notranslate"><div class="highlight"><pre><span></span>['Solarize_Light2', '_classic_test_patch', '_mpl-gallery', '_mpl-gallery-nogrid', 'bmh', 'classic', 'dark_background', 'fast', 'fivethirtyeight', 'ggplot', 'grayscale', 'seaborn-v0_8', 'seaborn-v0_8-bright', 'seaborn-v0_8-colorblind', 'seaborn-v0_8-dark', 'seaborn-v0_8-dark-palette', 'seaborn-v0_8-darkgrid', 'seaborn-v0_8-deep', 'seaborn-v0_8-muted', 'seaborn-v0_8-notebook', 'seaborn-v0_8-paper', 'seaborn-v0_8-pastel', 'seaborn-v0_8-poster', 'seaborn-v0_8-talk', 'seaborn-v0_8-ticks', 'seaborn-v0_8-white', 'seaborn-v0_8-whitegrid', 'tableau-colorblind10']

</pre></div>

</div>

<p>You can activate a style with the following:</p>

<div class="highlight-Python notranslate"><div class="highlight"><pre><span></span><span class="n">plt</span><span class="o">.</span><span class="n">style</span><span class="o">.</span><span class="n">use</span><span class="p">(</span><span class="s1">'fivethirtyeight'</span><span class="p">)</span>

</pre></div>

</div>

<p>Now let's remake the above plot to see how it looks:</p>

</pre></div>

</div>

<img src="../_images/sphx_glr_lifecycle_003.png" srcset="../_images/sphx_glr_lifecycle_003.png, ../_images/sphx_glr_lifecycle_003_2_00x.png 2.00x" alt="lifecycle" class = "sphx-glr-single-img"/><p>The style controls many things, such as color, linewidths, backgrounds,

etc.</p>

</section>

<h2>Customizing the plot<a class="headerlink" href="#customizing-the-plot" title="Link to this heading">#</a></h2>

<p>Now we've got a plot with the general look that we want, so let's fine-tune

it so that it's ready for print. First let's rotate the labels on the x-axis

so that they show up more clearly. We can gain access to these labels

with the <a class="reference internal" href="../api/_as_gen/matplotlib.axes.Axes.get_xticklabels.html#matplotlib.axes.Axes.get_xticklabels" title="matplotlib.axes.Axes.get_xticklabels"><code class="xref py py-meth docutils literal notranslate"><span class="pre">axes.Axes.get_xticklabels()</span></code></a> method:</p>

<a href="https://docs.python.org/3/library/stdtypes.html#list" title="builtins.list" class="sphx-glr-backref-module-builtins sphx-glr-backref-type-py-class sphx-glr-backref-instance"><span class="n">labels</span></a> <span class="o">=</span> <a href="../api/_as_gen/matplotlib.axes.Axes.get_xticklabels.html#matplotlib.axes.Axes.get_xticklabels" title="matplotlib.axes.Axes.get_xticklabels" class="sphx-glr-backref-module-matplotlib-axes sphx-glr-backref-type-py-method"><span class="n">ax</span><span class="o">.</span><span class="n">get_xticklabels</span></a><span class="p">()</span>

</pre></div>

</div>

<img src="../_images/sphx_glr_lifecycle_004.png" srcset="../_images/sphx_glr_lifecycle_004.png, ../_images/sphx_glr_lifecycle_004_2_00x.png 2.00x" alt="lifecycle" class = "sphx-glr-single-img"/><p>If we'd like to set the property of many items at once, it's useful to use

the <a class="reference internal" href="../api/_as_gen/matplotlib.pyplot.setp.html#matplotlib.pyplot.setp" title="matplotlib.pyplot.setp"><code class="xref py py-func docutils literal notranslate"><span class="pre">pyplot.setp()</span></code></a> function. This will take a list (or many lists) of

Matplotlib objects, and attempt to set some style element of each one.</p>

<a href="https://docs.python.org/3/library/stdtypes.html#list" title="builtins.list" class="sphx-glr-backref-module-builtins sphx-glr-backref-type-py-class sphx-glr-backref-instance"><span class="n">labels</span></a> <span class="o">=</span> <a href="../api/_as_gen/matplotlib.axes.Axes.get_xticklabels.html#matplotlib.axes.Axes.get_xticklabels" title="matplotlib.axes.Axes.get_xticklabels" class="sphx-glr-backref-module-matplotlib-axes sphx-glr-backref-type-py-method"><span class="n">ax</span><span class="o">.</span><span class="n">get_xticklabels</span></a><span class="p">()</span>

<a href="../api/_as_gen/matplotlib.pyplot.setp.html#matplotlib.pyplot.setp" title="matplotlib.pyplot.setp" class="sphx-glr-backref-module-matplotlib-pyplot sphx-glr-backref-type-py-function"><span class="n">plt</span><span class="o">.</span><span class="n">setp</span></a><span class="p">(</span><a href="https://docs.python.org/3/library/stdtypes.html#list" title="builtins.list" class="sphx-glr-backref-module-builtins sphx-glr-backref-type-py-class sphx-glr-backref-instance"><span class="n">labels</span></a><span class="p">,</span> <span class="n">rotation</span><span class="o">=</span><span class="mi">45</span><span class="p">,</span> <span class="n">horizontalalignment</span><span class="o">=</span><span class="s1">'right'</span><span class="p">)</span>

</pre></div>

</div>

<img src="../_images/sphx_glr_lifecycle_005.png" srcset="../_images/sphx_glr_lifecycle_005.png, ../_images/sphx_glr_lifecycle_005_2_00x.png 2.00x" alt="lifecycle" class = "sphx-glr-single-img"/><p>It looks like this cut off some of the labels on the bottom. We can

tell Matplotlib to automatically make room for elements in the figures

that we create. To do this we set the <code class="docutils literal notranslate"><span class="pre">autolayout</span></code> value of our

rcParams. For more information on controlling the style, layout, and

other features of plots with rcParams, see

<a class="reference internal" href="../users/explain/customizing.html#customizing"><span class="std std-ref">Customizing Matplotlib with style sheets and rcParams</span></a>.</p>

<div class="highlight-Python notranslate"><div class="highlight"><pre><span></span><a href="https://docs.python.org/3/library/stdtypes.html#dict.update" title="builtins.dict.update" class="sphx-glr-backref-module-builtins sphx-glr-backref-type-py-method"><span class="n">plt</span><span class="o">.</span><span class="n">rcParams</span><span class="o">.</span><span class="n">update</span></a><span class="p">({</span><span class="s1">'figure.autolayout'</span><span class="p">:</span> <span class="kc">True</span><span class="p">})</span>

<a href="../api/_as_gen/matplotlib.figure.Figure.html#matplotlib.figure.Figure" title="matplotlib.figure.Figure" class="sphx-glr-backref-module-matplotlib-figure sphx-glr-backref-type-py-class sphx-glr-backref-instance"><span class="n">fig</span></a><span class="p">,</span> <a href="../api/_as_gen/matplotlib.axes.Axes.html#matplotlib.axes.Axes" title="matplotlib.axes.Axes" class="sphx-glr-backref-module-matplotlib-axes sphx-glr-backref-type-py-class sphx-glr-backref-instance"><span class="n">ax</span></a> <span class="o">=</span> <a href="../api/_as_gen/matplotlib.pyplot.subplots.html#matplotlib.pyplot.subplots" title="matplotlib.pyplot.subplots" class="sphx-glr-backref-module-matplotlib-pyplot sphx-glr-backref-type-py-function"><span class="n">plt</span><span class="o">.</span><span class="n">subplots</span></a><span class="p">()</span>

<a href="https://docs.python.org/3/library/stdtypes.html#list" title="builtins.list" class="sphx-glr-backref-module-builtins sphx-glr-backref-type-py-class sphx-glr-backref-instance"><span class="n">labels</span></a> <span class="o">=</span> <a href="../api/_as_gen/matplotlib.axes.Axes.get_xticklabels.html#matplotlib.axes.Axes.get_xticklabels" title="matplotlib.axes.Axes.get_xticklabels" class="sphx-glr-backref-module-matplotlib-axes sphx-glr-backref-type-py-method"><span class="n">ax</span><span class="o">.</span><span class="n">get_xticklabels</span></a><span class="p">()</span>

</pre></div>

</div>

<img src="../_images/sphx_glr_lifecycle_006.png" srcset="../_images/sphx_glr_lifecycle_006.png, ../_images/sphx_glr_lifecycle_006_2_00x.png 2.00x" alt="lifecycle" class = "sphx-glr-single-img"/><p>Next, we add labels to the plot. To do this with the OO interface,

we can use the <a class="reference internal" href="../api/_as_gen/matplotlib.artist.Artist.set.html#matplotlib.artist.Artist.set" title="matplotlib.artist.Artist.set"><code class="xref py py-meth docutils literal notranslate"><span class="pre">Artist.set()</span></code></a> method to set properties of this

Axes object.</p>

<a href="https://docs.python.org/3/library/stdtypes.html#list" title="builtins.list" class="sphx-glr-backref-module-builtins sphx-glr-backref-type-py-class sphx-glr-backref-instance"><span class="n">labels</span></a> <span class="o">=</span> <a href="../api/_as_gen/matplotlib.axes.Axes.get_xticklabels.html#matplotlib.axes.Axes.get_xticklabels" title="matplotlib.axes.Axes.get_xticklabels" class="sphx-glr-backref-module-matplotlib-axes sphx-glr-backref-type-py-method"><span class="n">ax</span><span class="o">.</span><span class="n">get_xticklabels</span></a><span class="p">()</span>

<a href="../api/_as_gen/matplotlib.axes.Axes.set.html#matplotlib.axes.Axes.set" title="matplotlib.axes.Axes.set" class="sphx-glr-backref-module-matplotlib-axes sphx-glr-backref-type-py-method"><span class="n">ax</span><span class="o">.</span><span class="n">set</span></a><span class="p">(</span><span class="n">xlim</span><span class="o">=</span><span class="p">[</span><span class="o">-</span><span class="mi">10000</span><span class="p">,</span> <span class="mi">140000</span><span class="p">],</span> <span class="n">xlabel</span><span class="o">=</span><span class="s1">'Total Revenue'</span><span class="p">,</span> <span class="n">ylabel</span><span class="o">=</span><span class="s1">'Company'</span><span class="p">,</span>

<span class="n">title</span><span class="o">=</span><span class="s1">'Company Revenue'</span><span class="p">)</span>

</pre></div>

</div>

<img src="../_images/sphx_glr_lifecycle_007.png" srcset="../_images/sphx_glr_lifecycle_007.png, ../_images/sphx_glr_lifecycle_007_2_00x.png 2.00x" alt="Company Revenue" class = "sphx-glr-single-img"/><p>We can also adjust the size of this plot using the <a class="reference internal" href="../api/_as_gen/matplotlib.pyplot.subplots.html#matplotlib.pyplot.subplots" title="matplotlib.pyplot.subplots"><code class="xref py py-func docutils literal notranslate"><span class="pre">pyplot.subplots()</span></code></a>

function. We can do this with the <em>figsize</em> keyword argument.</p>

<p>While indexing in NumPy follows the form (row, column), the <em>figsize</em>

keyword argument follows the form (width, height). This follows

conventions in visualization, which unfortunately are different from those

of linear algebra.</p>

</div>

<a href="https://docs.python.org/3/library/stdtypes.html#list" title="builtins.list" class="sphx-glr-backref-module-builtins sphx-glr-backref-type-py-class sphx-glr-backref-instance"><span class="n">labels</span></a> <span class="o">=</span> <a href="../api/_as_gen/matplotlib.axes.Axes.get_xticklabels.html#matplotlib.axes.Axes.get_xticklabels" title="matplotlib.axes.Axes.get_xticklabels" class="sphx-glr-backref-module-matplotlib-axes sphx-glr-backref-type-py-method"><span class="n">ax</span><span class="o">.</span><span class="n">get_xticklabels</span></a><span class="p">()</span>

<span class="n">title</span><span class="o">=</span><span class="s1">'Company Revenue'</span><span class="p">)</span>

</pre></div>

</div>

<img src="../_images/sphx_glr_lifecycle_008.png" srcset="../_images/sphx_glr_lifecycle_008.png, ../_images/sphx_glr_lifecycle_008_2_00x.png 2.00x" alt="Company Revenue" class = "sphx-glr-single-img"/><p>For labels, we can specify custom formatting guidelines in the form of

functions. Below we define a function that takes an integer as input, and

returns a string as an output. When used with <a class="reference internal" href="../api/_as_gen/matplotlib.axis.Axis.set_major_formatter.html#matplotlib.axis.Axis.set_major_formatter" title="matplotlib.axis.Axis.set_major_formatter"><code class="xref py py-obj docutils literal notranslate"><span class="pre">Axis.set_major_formatter</span></code></a> or

<a class="reference internal" href="../api/_as_gen/matplotlib.axis.Axis.set_minor_formatter.html#matplotlib.axis.Axis.set_minor_formatter" title="matplotlib.axis.Axis.set_minor_formatter"><code class="xref py py-obj docutils literal notranslate"><span class="pre">Axis.set_minor_formatter</span></code></a>, they will automatically create and use a

<a class="reference internal" href="../api/ticker_api.html#matplotlib.ticker.FuncFormatter" title="matplotlib.ticker.FuncFormatter"><code class="xref py py-class docutils literal notranslate"><span class="pre">ticker.FuncFormatter</span></code></a> class.</p>

<p>For this function, the <code class="docutils literal notranslate"><span class="pre">x</span></code> argument is the original tick label and <code class="docutils literal notranslate"><span class="pre">pos</span></code>

is the tick position. We will only use <code class="docutils literal notranslate"><span class="pre">x</span></code> here but both arguments are

needed.</p>

<div class="highlight-Python notranslate"><div class="highlight"><pre><span></span><span class="k">def</span> <span class="nf">currency</span><span class="p">(</span><span class="n">x</span><span class="p">,</span> <span class="n">pos</span><span class="p">):</span>

<span class="w"> </span><span class="sd">"""The two arguments are the value and tick position"""</span>

<span class="k">return</span> <span class="n">s</span>

</pre></div>

</div>

<p>We can then apply this function to the labels on our plot. To do this,

we use the <code class="docutils literal notranslate"><span class="pre">xaxis</span></code> attribute of our Axes. This lets you perform

actions on a specific axis on our plot.</p>

<a href="https://docs.python.org/3/library/stdtypes.html#list" title="builtins.list" class="sphx-glr-backref-module-builtins sphx-glr-backref-type-py-class sphx-glr-backref-instance"><span class="n">labels</span></a> <span class="o">=</span> <a href="../api/_as_gen/matplotlib.axes.Axes.get_xticklabels.html#matplotlib.axes.Axes.get_xticklabels" title="matplotlib.axes.Axes.get_xticklabels" class="sphx-glr-backref-module-matplotlib-axes sphx-glr-backref-type-py-method"><span class="n">ax</span><span class="o">.</span><span class="n">get_xticklabels</span></a><span class="p">()</span>

<span class="n">title</span><span class="o">=</span><span class="s1">'Company Revenue'</span><span class="p">)</span>

<a href="../api/_as_gen/matplotlib.axis.Axis.set_major_formatter.html#matplotlib.axis.Axis.set_major_formatter" title="matplotlib.axis.Axis.set_major_formatter" class="sphx-glr-backref-module-matplotlib-axis sphx-glr-backref-type-py-method"><span class="n">ax</span><span class="o">.</span><span class="n">xaxis</span><span class="o">.</span><span class="n">set_major_formatter</span></a><span class="p">(</span><span class="n">currency</span><span class="p">)</span>

</pre></div>

</div>

<h2>Combining multiple visualizations<a class="headerlink" href="#combining-multiple-visualizations" title="Link to this heading">#</a></h2>

<p>It is possible to draw multiple plot elements on the same instance of

the plot methods on that Axes object.</p>

<a href="https://docs.python.org/3/library/stdtypes.html#list" title="builtins.list" class="sphx-glr-backref-module-builtins sphx-glr-backref-type-py-class sphx-glr-backref-instance"><span class="n">labels</span></a> <span class="o">=</span> <a href="../api/_as_gen/matplotlib.axes.Axes.get_xticklabels.html#matplotlib.axes.Axes.get_xticklabels" title="matplotlib.axes.Axes.get_xticklabels" class="sphx-glr-backref-module-matplotlib-axes sphx-glr-backref-type-py-method"><span class="n">ax</span><span class="o">.</span><span class="n">get_xticklabels</span></a><span class="p">()</span>

<span class="c1"># Add a vertical line, here we set the style in the function call</span>

<a href="../api/_as_gen/matplotlib.axes.Axes.axvline.html#matplotlib.axes.Axes.axvline" title="matplotlib.axes.Axes.axvline" class="sphx-glr-backref-module-matplotlib-axes sphx-glr-backref-type-py-method"><span class="n">ax</span><span class="o">.</span><span class="n">axvline</span></a><span class="p">(</span><a href="https://numpy.org/doc/stable/reference/arrays.scalars.html#numpy.float64" title="numpy.float64" class="sphx-glr-backref-module-numpy sphx-glr-backref-type-py-attribute"><span class="n">group_mean</span></a><span class="p">,</span> <span class="n">ls</span><span class="o">=</span><span class="s1">'--'</span><span class="p">,</span> <span class="n">color</span><span class="o">=</span><span class="s1">'r'</span><span class="p">)</span>

<span class="c1"># Annotate new companies</span>

<span class="k">for</span> <a href="https://docs.python.org/3/library/functions.html#int" title="builtins.int" class="sphx-glr-backref-module-builtins sphx-glr-backref-type-py-class sphx-glr-backref-instance"><span class="n">group</span></a> <span class="ow">in</span> <span class="p">[</span><span class="mi">3</span><span class="p">,</span> <span class="mi">5</span><span class="p">,</span> <span class="mi">8</span><span class="p">]:</span>

<a href="../api/_as_gen/matplotlib.axes.Axes.text.html#matplotlib.axes.Axes.text" title="matplotlib.axes.Axes.text" class="sphx-glr-backref-module-matplotlib-axes sphx-glr-backref-type-py-method"><span class="n">ax</span><span class="o">.</span><span class="n">text</span></a><span class="p">(</span><span class="mi">145000</span><span class="p">,</span> <a href="https://docs.python.org/3/library/functions.html#int" title="builtins.int" class="sphx-glr-backref-module-builtins sphx-glr-backref-type-py-class sphx-glr-backref-instance"><span class="n">group</span></a><span class="p">,</span> <span class="s2">"New Company"</span><span class="p">,</span> <span class="n">fontsize</span><span class="o">=</span><span class="mi">10</span><span class="p">,</span>

<span class="n">verticalalignment</span><span class="o">=</span><span class="s2">"center"</span><span class="p">)</span>

<span class="c1"># Now we move our title up since it's getting a little cramped</span>

<a href="../api/text_api.html#matplotlib.text.Text.set" title="matplotlib.text.Text.set" class="sphx-glr-backref-module-matplotlib-text sphx-glr-backref-type-py-method"><span class="n">ax</span><span class="o">.</span><span class="n">title</span><span class="o">.</span><span class="n">set</span></a><span class="p">(</span><span class="n">y</span><span class="o">=</span><span class="mf">1.05</span><span class="p">)</span>

<span class="n">title</span><span class="o">=</span><span class="s1">'Company Revenue'</span><span class="p">)</span>

<a href="../api/_as_gen/matplotlib.axes.Axes.set_xticks.html#matplotlib.axes.Axes.set_xticks" title="matplotlib.axes.Axes.set_xticks" class="sphx-glr-backref-module-matplotlib-axes sphx-glr-backref-type-py-method"><span class="n">ax</span><span class="o">.</span><span class="n">set_xticks</span></a><span class="p">([</span><span class="mi">0</span><span class="p">,</span> <span class="mf">25e3</span><span class="p">,</span> <span class="mf">50e3</span><span class="p">,</span> <span class="mf">75e3</span><span class="p">,</span> <span class="mf">100e3</span><span class="p">,</span> <span class="mf">125e3</span><span class="p">])</span>

<a href="../api/_as_gen/matplotlib.figure.Figure.subplots_adjust.html#matplotlib.figure.Figure.subplots_adjust" title="matplotlib.figure.Figure.subplots_adjust" class="sphx-glr-backref-module-matplotlib-figure sphx-glr-backref-type-py-method"><span class="n">fig</span><span class="o">.</span><span class="n">subplots_adjust</span></a><span class="p">(</span><span class="n">right</span><span class="o">=</span><span class="mf">.1</span><span class="p">)</span>

</pre></div>

</div>

<h2>Saving our plot<a class="headerlink" href="#saving-our-plot" title="Link to this heading">#</a></h2>

<p>Now that we're happy with the outcome of our plot, we want to save it to

disk. There are many file formats we can save to in Matplotlib. To see

a list of available options, use:</p>

<div class="highlight-Python notranslate"><div class="highlight"><pre><span></span><span class="nb">print</span><span class="p">(</span><a href="../api/backend_bases_api.html#matplotlib.backend_bases.FigureCanvasBase.get_supported_filetypes" title="matplotlib.backend_bases.FigureCanvasBase.get_supported_filetypes" class="sphx-glr-backref-module-matplotlib-backend_bases sphx-glr-backref-type-py-method"><span class="n">fig</span><span class="o">.</span><span class="n">canvas</span><span class="o">.</span><span class="n">get_supported_filetypes</span></a><span class="p">())</span>

</pre></div>

</div>

<div class="sphx-glr-script-out highlight-none notranslate"><div class="highlight"><pre><span></span>{'eps': 'Encapsulated Postscript', 'jpg': 'Joint Photographic Experts Group', 'jpeg': 'Joint Photographic Experts Group', 'pdf': 'Portable Document Format', 'pgf': 'PGF code for LaTeX', 'png': 'Portable Network Graphics', 'ps': 'Postscript', 'raw': 'Raw RGBA bitmap', 'rgba': 'Raw RGBA bitmap', 'svg': 'Scalable Vector Graphics', 'svgz': 'Scalable Vector Graphics', 'tif': 'Tagged Image File Format', 'tiff': 'Tagged Image File Format', 'webp': 'WebP Image Format'}

</pre></div>

</div>

<p>We can then use the <a class="reference internal" href="../api/_as_gen/matplotlib.figure.Figure.savefig.html#matplotlib.figure.Figure.savefig" title="matplotlib.figure.Figure.savefig"><code class="xref py py-meth docutils literal notranslate"><span class="pre">figure.Figure.savefig()</span></code></a> in order to save the figure

to disk. Note that there are several useful flags we show below:</p>

<li><p><code class="docutils literal notranslate"><span class="pre">transparent=True</span></code> makes the background of the saved figure transparent

if the format supports it.</p></li>

<li><p><code class="docutils literal notranslate"><span class="pre">dpi=80</span></code> controls the resolution (dots per square inch) of the output.</p></li>

<li><p><code class="docutils literal notranslate"><span class="pre">bbox_inches="tight"</span></code> fits the bounds of the figure to our plot.</p></li>

</ul>

<div class="highlight-Python notranslate"><div class="highlight"><pre><span></span><span class="c1"># Uncomment this line to save the figure.</span>

<span class="c1"># fig.savefig('sales.png', transparent=False, dpi=80, bbox_inches="tight")</span>

</pre></div>

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<li class="toc-h2 nav-item toc-entry"><a class="reference internal nav-link" href="#a-note-on-the-explicit-vs-implicit-interfaces">A note on the explicit vs. implicit interfaces</a></li>

<li class="toc-h2 nav-item toc-entry"><a class="reference internal nav-link" href="#getting-started">Getting started</a></li>

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<li class="toc-h2 nav-item toc-entry"><a class="reference internal nav-link" href="#combining-multiple-visualizations">Combining multiple visualizations</a></li>

<li class="toc-h2 nav-item toc-entry"><a class="reference internal nav-link" href="#saving-our-plot">Saving our plot</a></li>

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