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<!DOCTYPE html PUBLIC "-//W3C//DTD XHTML 1.0 Transitional//EN"

"http://www.w3.org/TR/xhtml1/DTD/xhtml1-transitional.dtd">

<head>

<title>Text in Matplotlib Plots — Matplotlib 2.2.3 documentation</title>

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<div id="unreleased-message"> You are reading an old version of the documentation (v2.2.3). For the latest version see <a href="https://matplotlib.org/stable/tutorials/text/text_intro.html">https://matplotlib.org/stable/tutorials/text/text_intro.html</a></div>

<div style="float: left; position: absolute; width: 496px; bottom: 0; padding-bottom: 24px">Version 2.2.3</div>

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<h3><a href="../../contents.html">Table Of Contents</a></h3>

<ul>

<li><a class="reference internal" href="#">Text in Matplotlib Plots</a><ul>

<li><a class="reference internal" href="#basic-text-commands">Basic text commands</a></li>

<li><a class="reference internal" href="#labels-for-x-and-y-axis">Labels for x- and y-axis</a></li>

<li><a class="reference internal" href="#titles">Titles</a></li>

<li><a class="reference internal" href="#ticks-and-ticklabels">Ticks and ticklabels</a><ul>

<li><a class="reference internal" href="#terminology">Terminology</a></li>

<li><a class="reference internal" href="#simple-ticks">Simple ticks</a></li>

<li><a class="reference internal" href="#tick-locators-and-formatters">Tick Locators and Formatters</a></li>

<li><a class="reference internal" href="#dateticks">Dateticks</a></li>

</ul>

</li>

<li><a class="reference internal" href="#legends-and-annotations">Legends and Annotations</a></li>

</ul>

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</ul>

<h3>Related Topics</h3>

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<li><a href="../index.html">Tutorials</a><ul>

<li>Previous: <a href="text_props.html" title="previous chapter">Text properties and layout</a></li>

<li>Next: <a href="../toolkits/mplot3d.html" title="next chapter">The mplot3d Toolkit</a></li>

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Click <a class="reference internal" href="#sphx-glr-download-tutorials-text-text-intro-py">here</a> to download the full example code

</div>

<h1>Text in Matplotlib Plots<a class="headerlink" href="#text-in-matplotlib-plots" title="Permalink to this headline">¶</a></h1>

Introduction to plotting and working with text in Matplotlib.

Matplotlib has extensive text support, including support for

mathematical expressions, truetype support for raster and

vector outputs, newline separated text with arbitrary

rotations, and unicode support.

Because it embeds fonts directly in output documents, e.g., for postscript

or PDF, what you see on the screen is what you get in the hardcopy.

<a class="reference external" href="https://www.freetype.org/">FreeType</a> support

produces very nice, antialiased fonts, that look good even at small

raster sizes. matplotlib includes its own

<a class="reference internal" href="../../api/font_manager_api.html#module-matplotlib.font_manager" title="matplotlib.font_manager"><code class="xref py py-mod docutils literal notranslate">matplotlib.font_manager</code></a> (thanks to Paul Barrett), which

implements a cross platform, <code class="xref py py-obj docutils literal notranslate">W3C</code>

compliant font finding algorithm.

The user has a great deal of control over text properties (font size, font

weight, text location and color, etc.) with sensible defaults set in

the <code class="xref py py-obj docutils literal notranslate">rc file</code>.

And significantly, for those interested in mathematical

or scientific figures, matplotlib implements a large number of TeX

math symbols and commands, supporting <a class="reference internal" href="mathtext.html#sphx-glr-tutorials-text-mathtext-py">mathematical expressions</a> anywhere in your figure.

<h2>Basic text commands<a class="headerlink" href="#basic-text-commands" title="Permalink to this headline">¶</a></h2>

The following commands are used to create text in the pyplot

interface and the object-oriented API:

</colgroup>

<tr class="row-odd"><th class="head"><a class="reference internal" href="../../api/_as_gen/matplotlib.pyplot.html#module-matplotlib.pyplot" title="matplotlib.pyplot"><code class="xref py py-obj docutils literal notranslate">pyplot</code></a> API</th>

<th class="head">description</th>

</tr>

</thead>

<td>Add text at an arbitrary location of

the <a class="reference internal" href="../../api/axes_api.html#matplotlib.axes.Axes" title="matplotlib.axes.Axes"><code class="xref py py-obj docutils literal notranslate">Axes</code></a>.</td>

</tr>

<tr class="row-odd"><td><a class="reference internal" href="../../api/_as_gen/matplotlib.pyplot.annotate.html#matplotlib.pyplot.annotate" title="matplotlib.pyplot.annotate"><code class="xref py py-obj docutils literal notranslate">annotate</code></a></td>

<td><a class="reference internal" href="../../api/_as_gen/matplotlib.axes.Axes.annotate.html#matplotlib.axes.Axes.annotate" title="matplotlib.axes.Axes.annotate"><code class="xref py py-obj docutils literal notranslate">annotate</code></a></td>

<td>Add an annotation, with an optional

arrow, at an arbitrary location of the

</tr>

<tr class="row-even"><td><a class="reference internal" href="../../api/_as_gen/matplotlib.pyplot.xlabel.html#matplotlib.pyplot.xlabel" title="matplotlib.pyplot.xlabel"><code class="xref py py-obj docutils literal notranslate">xlabel</code></a></td>

<td><a class="reference internal" href="../../api/_as_gen/matplotlib.axes.Axes.set_xlabel.html#matplotlib.axes.Axes.set_xlabel" title="matplotlib.axes.Axes.set_xlabel"><code class="xref py py-obj docutils literal notranslate">set_xlabel</code></a></td>

<td>Add a label to the

</tr>

<tr class="row-odd"><td><a class="reference internal" href="../../api/_as_gen/matplotlib.pyplot.ylabel.html#matplotlib.pyplot.ylabel" title="matplotlib.pyplot.ylabel"><code class="xref py py-obj docutils literal notranslate">ylabel</code></a></td>

<td><a class="reference internal" href="../../api/_as_gen/matplotlib.axes.Axes.set_ylabel.html#matplotlib.axes.Axes.set_ylabel" title="matplotlib.axes.Axes.set_ylabel"><code class="xref py py-obj docutils literal notranslate">set_ylabel</code></a></td>

<td>Add a label to the

</tr>

<tr class="row-even"><td><a class="reference internal" href="../../api/_as_gen/matplotlib.pyplot.title.html#matplotlib.pyplot.title" title="matplotlib.pyplot.title"><code class="xref py py-obj docutils literal notranslate">title</code></a></td>

<td><a class="reference internal" href="../../api/_as_gen/matplotlib.axes.Axes.set_title.html#matplotlib.axes.Axes.set_title" title="matplotlib.axes.Axes.set_title"><code class="xref py py-obj docutils literal notranslate">set_title</code></a></td>

<td>Add a title to the

</tr>

<tr class="row-odd"><td><a class="reference internal" href="../../api/_as_gen/matplotlib.pyplot.figtext.html#matplotlib.pyplot.figtext" title="matplotlib.pyplot.figtext"><code class="xref py py-obj docutils literal notranslate">figtext</code></a></td>

<td>Add text at an arbitrary location of

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">Figure</code></a>.</td>

</tr>

<tr class="row-even"><td><a class="reference internal" href="../../api/_as_gen/matplotlib.pyplot.suptitle.html#matplotlib.pyplot.suptitle" title="matplotlib.pyplot.suptitle"><code class="xref py py-obj docutils literal notranslate">suptitle</code></a></td>

<td><a class="reference internal" href="../../api/_as_gen/matplotlib.figure.Figure.html#matplotlib.figure.Figure.suptitle" title="matplotlib.figure.Figure.suptitle"><code class="xref py py-obj docutils literal notranslate">suptitle</code></a></td>

<td>Add a title to 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">Figure</code></a>.</td>

</tr>

</tbody>

</table>

All of these functions create and return a <a class="reference internal" href="../../api/text_api.html#matplotlib.text.Text" title="matplotlib.text.Text"><code class="xref py py-obj docutils literal notranslate">Text</code></a> instance, which can be

configured with a variety of font and other properties. The example below

shows all of these commands in action, and more detail is provided in the

sections that follow.

<div class="highlight-python notranslate"><div class="highlight"><pre>import matplotlib

import matplotlib.pyplot as plt

fig = <a href="../../api/_as_gen/matplotlib.pyplot.figure.html#matplotlib.pyplot.figure" title="View documentation for matplotlib.pyplot.figure">plt.figure</a>()

fig.suptitle('bold figure suptitle', fontsize=14, fontweight='bold')

ax = fig.add_subplot(111)

fig.subplots_adjust(top=0.85)

ax.set_title('axes title')

ax.set_xlabel('xlabel')

ax.set_ylabel('ylabel')

ax.text(3, 8, 'boxed italics text in data coords', style='italic',

bbox={'facecolor': 'red', 'alpha': 0.5, 'pad': 10})

ax.text(2, 6, r'an equation: $E=mc^2$', fontsize=15)

ax.text(3, 2, u'unicode: Institut für Festkörperphysik')

ax.text(0.95, 0.01, 'colored text in axes coords',

verticalalignment='bottom', horizontalalignment='right',

transform=ax.transAxes,

color='green', fontsize=15)

ax.plot([2], [1], 'o')

ax.annotate('annotate', xy=(2, 1), xytext=(3, 4),

arrowprops=dict(facecolor='black', shrink=0.05))

ax.axis([0, 10, 0, 10])

<a href="../../api/_as_gen/matplotlib.pyplot.show.html#matplotlib.pyplot.show" title="View documentation for matplotlib.pyplot.show">plt.show</a>()

</pre></div>

</div>

</div>

<h2>Labels for x- and y-axis<a class="headerlink" href="#labels-for-x-and-y-axis" title="Permalink to this headline">¶</a></h2>

Specifying the labels for the x- and y-axis is strightforward, via the

<a class="reference internal" href="../../api/_as_gen/matplotlib.axes.Axes.set_xlabel.html#matplotlib.axes.Axes.set_xlabel" title="matplotlib.axes.Axes.set_xlabel"><code class="xref py py-obj docutils literal notranslate">set_xlabel</code></a> and

<a class="reference internal" href="../../api/_as_gen/matplotlib.axes.Axes.set_ylabel.html#matplotlib.axes.Axes.set_ylabel" title="matplotlib.axes.Axes.set_ylabel"><code class="xref py py-obj docutils literal notranslate">set_ylabel</code></a> methods.

<div class="highlight-python notranslate"><div class="highlight"><pre>import matplotlib.pyplot as plt

import numpy as np

x1 = <a href="https://docs.scipy.org/doc/numpy/reference/generated/numpy.linspace.html#numpy.linspace" title="View documentation for numpy.linspace">np.linspace</a>(0.0, 5.0, 100)

y1 = <a href="https://docs.scipy.org/doc/numpy/reference/generated/numpy.cos.html#numpy.cos" title="View documentation for numpy.cos">np.cos</a>(2 * <a href="https://docs.scipy.org/doc/numpy/reference/constants.html#numpy.pi" title="View documentation for numpy.pi">np.pi</a> * x1) * <a href="https://docs.scipy.org/doc/numpy/reference/generated/numpy.exp.html#numpy.exp" title="View documentation for numpy.exp">np.exp</a>(-x1)

fig, ax = <a href="../../api/_as_gen/matplotlib.pyplot.subplots.html#matplotlib.pyplot.subplots" title="View documentation for matplotlib.pyplot.subplots">plt.subplots</a>(figsize=(5, 3))

fig.subplots_adjust(bottom=0.15, left=0.2)

ax.plot(x1, y1)

ax.set_xlabel('time [s]')

ax.set_ylabel('Damped oscillation [V]')

</pre></div>

</div>

The x- and y-labels are automatically placed so that they clear the x- and

y-ticklabels. Compare the plot below with that above, and note the y-label

is to the left of the one above.

<div class="highlight-python notranslate"><div class="highlight"><pre>fig, ax = <a href="../../api/_as_gen/matplotlib.pyplot.subplots.html#matplotlib.pyplot.subplots" title="View documentation for matplotlib.pyplot.subplots">plt.subplots</a>(figsize=(5, 3))

ax.plot(x1, y1*10000)

ax.set_xlabel('time [s]')

ax.set_ylabel('Damped oscillation [V]')

</pre></div>

</div>

If you want to move the labels, you can specify the labelpad kyeword

argument, where the value is points (1/72", the same unit used to specify

fontsizes).

ax.set_xlabel('time [s]')

ax.set_ylabel('Damped oscillation [V]', labelpad=18)

</pre></div>

</div>

Or, the labels accept all the <a class="reference internal" href="../../api/text_api.html#matplotlib.text.Text" title="matplotlib.text.Text"><code class="xref py py-obj docutils literal notranslate">Text</code></a> keyword arguments, including

position, via which we can manually specify the label positions. Here we

put the xlabel to the far left of the axis. Note, that the y-coordinate of

this position has no effect - to adjust the y-position we need to use the

labelpad kwarg.

ax.plot(x1, y1)

ax.set_xlabel('time [s]', position=(0., 1e6),

horizontalalignment='left')

ax.set_ylabel('Damped oscillation [V]')

</pre></div>

</div>

All the labelling in this tutorial can be changed by manipulating the

<a class="reference internal" href="../../api/font_manager_api.html#matplotlib.font_manager.FontProperties" title="matplotlib.font_manager.FontProperties"><code class="xref py py-obj docutils literal notranslate">matplotlib.font_manager.FontProperties</code></a> method, or by named kwargs to

<div class="highlight-python notranslate"><div class="highlight"><pre>from matplotlib.font_manager import <a href="../../api/font_manager_api.html#matplotlib.font_manager.FontProperties" title="View documentation for matplotlib.font_manager.FontProperties">FontProperties</a>

font = <a href="../../api/font_manager_api.html#matplotlib.font_manager.FontProperties" title="View documentation for matplotlib.font_manager.FontProperties">FontProperties</a>()

font.set_family('serif')

font.set_name('Times New Roman')

font.set_style('italic')

ax.plot(x1, y1)

ax.set_xlabel('time [s]', fontsize='large', fontweight='bold')

ax.set_ylabel('Damped oscillation [V]', fontproperties=font)

</pre></div>

</div>

Finally, we can use native TeX rendering in all text objects and have

multiple lines:

fig.subplots_adjust(bottom=0.2, left=0.2)

ax.plot(x1, <a href="https://docs.scipy.org/doc/numpy/reference/generated/numpy.cumsum.html#numpy.cumsum" title="View documentation for numpy.cumsum">np.cumsum</a>(y1**2))

ax.set_xlabel('time [s] \n This was a long experiment')

ax.set_ylabel(r'$\int\ Y^2\ dt\ \ [V^2 s]$')

</pre></div>

</div>

</div>

<h2>Titles<a class="headerlink" href="#titles" title="Permalink to this headline">¶</a></h2>

Subplot titles are set in much the same way as labels, but there is

the loc keyword arguments that can change the position and justification

from the default value of <code class="docutils literal notranslate">loc=center</code>.

<div class="highlight-python notranslate"><div class="highlight"><pre>fig, axs = <a href="../../api/_as_gen/matplotlib.pyplot.subplots.html#matplotlib.pyplot.subplots" title="View documentation for matplotlib.pyplot.subplots">plt.subplots</a>(3, 1, figsize=(5, 6), tight_layout=True)

locs = ['center', 'left', 'right']

for ax, loc in zip(axs, locs):

ax.plot(x1, y1)

ax.set_title('Title with loc at '+loc, loc=loc)

</pre></div>

</div>

Vertical spacing for titles is controlled via <code class="docutils literal notranslate">rcParams[axes.titlepad]</code>,

which defaults to 5 points. Setting to a different value moves the title.

ax.plot(x1, y1)

ax.set_title('Vertically offset title', pad=30)

</pre></div>

</div>

</div>

<h2>Ticks and ticklabels<a class="headerlink" href="#ticks-and-ticklabels" title="Permalink to this headline">¶</a></h2>

Placing ticks and ticklabels is a very tricky aspect of making a figure.

Matplotlib does the best it can automatically, but it also offers a very

flexible framework for determining the choices for tick locations, and

how they are labelled.

<h3>Terminology<a class="headerlink" href="#terminology" title="Permalink to this headline">¶</a></h3>

Axes have an <a class="reference internal" href="../../api/axis_api.html#module-matplotlib.axis" title="matplotlib.axis"><code class="xref py py-obj docutils literal notranslate">matplotlib.axis</code></a> object for the <code class="docutils literal notranslate">ax.xaxis</code>

and <code class="docutils literal notranslate">ax.yaxis</code> that

contain the information about how the labels in the axis are laid out.

The axis API is explained in detail in the documentation to

<a class="reference internal" href="../../api/axis_api.html#module-matplotlib.axis" title="matplotlib.axis"><code class="xref py py-obj docutils literal notranslate">axis</code></a>.

An Axis object has major and minor ticks. The Axis has a

<code class="xref py py-obj docutils literal notranslate">matplotlib.xaxis.set_major_locator</code> and

<code class="xref py py-obj docutils literal notranslate">matplotlib.xaxis.set_minor_locator</code> methods that use the data being plotted

to determine

the location of major and minor ticks. There are also

<code class="xref py py-obj docutils literal notranslate">matplotlib.xaxis.set_major_formatter</code> and

<code class="xref py py-obj docutils literal notranslate">matplotlib.xaxis.set_minor_formatters</code> methods that format the tick labels.

</div>

<h3>Simple ticks<a class="headerlink" href="#simple-ticks" title="Permalink to this headline">¶</a></h3>

It often is convenient to simply define the

tick values, and sometimes the tick labels, overriding the default

locators and formatters. This is discouraged because it breaks itneractive

navigation of the plot. It also can reset the axis limits: note that

the second plot has the ticks we asked for, including ones that are

well outside the automatic view limits.

<div class="highlight-python notranslate"><div class="highlight"><pre>fig, axs = <a href="../../api/_as_gen/matplotlib.pyplot.subplots.html#matplotlib.pyplot.subplots" title="View documentation for matplotlib.pyplot.subplots">plt.subplots</a>(2, 1, figsize=(5, 3), tight_layout=True)

axs[0].plot(x1, y1)

axs[1].plot(x1, y1)

axs[1].xaxis.set_ticks(<a href="https://docs.scipy.org/doc/numpy/reference/generated/numpy.arange.html#numpy.arange" title="View documentation for numpy.arange">np.arange</a>(0., 8.1, 2.))

</pre></div>

</div>

We can of course fix this after the fact, but it does highlight a

weakness of hard-coding the ticks. This example also changes the format

of the ticks:

<div class="highlight-python notranslate"><div class="highlight"><pre>fig, axs = <a href="../../api/_as_gen/matplotlib.pyplot.subplots.html#matplotlib.pyplot.subplots" title="View documentation for matplotlib.pyplot.subplots">plt.subplots</a>(2, 1, figsize=(5, 3), tight_layout=True)

ticks = <a href="https://docs.scipy.org/doc/numpy/reference/generated/numpy.arange.html#numpy.arange" title="View documentation for numpy.arange">np.arange</a>(0., 8.1, 2.)

# list comprehension to get all tick labels...

tickla = ['%1.2f' % tick for tick in ticks]

axs[1].set_xlim(axs[0].get_xlim())

</pre></div>

</div>

</div>

<h3>Tick Locators and Formatters<a class="headerlink" href="#tick-locators-and-formatters" title="Permalink to this headline">¶</a></h3>

Instead of making a list of all the tickalbels, we could have

used a <a class="reference internal" href="../../api/ticker_api.html#matplotlib.ticker.FormatStrFormatter" title="matplotlib.ticker.FormatStrFormatter"><code class="xref py py-obj docutils literal notranslate">matplotlib.ticker.FormatStrFormatter</code></a> and passed it to the

<code class="docutils literal notranslate">ax.xaxis</code>

<div class="highlight-python notranslate"><div class="highlight"><pre>fig, axs = <a href="../../api/_as_gen/matplotlib.pyplot.subplots.html#matplotlib.pyplot.subplots" title="View documentation for matplotlib.pyplot.subplots">plt.subplots</a>(2, 1, figsize=(5, 3), tight_layout=True)

# list comprehension to get all tick labels...

formatter = <a href="../../api/ticker_api.html#matplotlib.ticker.StrMethodFormatter" title="View documentation for matplotlib.ticker.StrMethodFormatter">matplotlib.ticker.StrMethodFormatter</a>('{x:1.1f}')

axs[1].xaxis.set_major_formatter(formatter)

</pre></div>

</div>

And of course we could have used a non-default locator to set the

tick locations. Note we still pass in the tick values, but the

x-limit fix used above is not needed.

<div class="highlight-python notranslate"><div class="highlight"><pre>fig, axs = <a href="../../api/_as_gen/matplotlib.pyplot.subplots.html#matplotlib.pyplot.subplots" title="View documentation for matplotlib.pyplot.subplots">plt.subplots</a>(2, 1, figsize=(5, 3), tight_layout=True)

formatter = <a href="../../api/ticker_api.html#matplotlib.ticker.FormatStrFormatter" title="View documentation for matplotlib.ticker.FormatStrFormatter">matplotlib.ticker.FormatStrFormatter</a>('%1.1f')

locator = <a href="../../api/ticker_api.html#matplotlib.ticker.FixedLocator" title="View documentation for matplotlib.ticker.FixedLocator">matplotlib.ticker.FixedLocator</a>(ticks)

axs[1].xaxis.set_major_locator(locator)

axs[1].xaxis.set_major_formatter(formatter)

</pre></div>

</div>

The default formatter is the <a class="reference internal" href="../../api/ticker_api.html#matplotlib.ticker.MaxNLocator" title="matplotlib.ticker.MaxNLocator"><code class="xref py py-obj docutils literal notranslate">matplotlib.ticker.MaxNLocator</code></a> called as

<code class="docutils literal notranslate">ticker.MaxNLocator(self, nbins='auto', steps=[1, 2, 2.5, 5, 10])</code>

The steps keyword contains a list of multiples that can be used for

tick values. i.e. in this case, 2, 4, 6 would be acceptable ticks,

as would 20, 40, 60 or 0.2, 0.4, 0.6. However, 3, 6, 9 would not be

acceptable because 3 doesn't appear in the list of steps.

<code class="docutils literal notranslate">nbins=auto</code> uses an algorithm to determine how many ticks will

be acceptable based on how long the axis is. The fontsize of the

ticklabel is taken into account, but the length of the tick string

is not (because its not yet known.) In the bottom row, the

ticklabels are quite large, so we set <code class="docutils literal notranslate">nbins=4</code> to make the

labels fit in the right-hand plot.

<div class="highlight-python notranslate"><div class="highlight"><pre>fig, axs = <a href="../../api/_as_gen/matplotlib.pyplot.subplots.html#matplotlib.pyplot.subplots" title="View documentation for matplotlib.pyplot.subplots">plt.subplots</a>(2, 2, figsize=(8, 5), tight_layout=True)

axs = axs.flatten()

for n, ax in enumerate(axs):

ax.plot(x1*10., y1)

locator = <a href="../../api/ticker_api.html#matplotlib.ticker.MaxNLocator" title="View documentation for matplotlib.ticker.MaxNLocator">matplotlib.ticker.MaxNLocator</a>(nbins='auto', steps=[1, 4, 10])

axs[1].xaxis.set_major_locator(locator)

axs[1].xaxis.set_major_formatter(formatter)

formatter = <a href="../../api/ticker_api.html#matplotlib.ticker.FormatStrFormatter" title="View documentation for matplotlib.ticker.FormatStrFormatter">matplotlib.ticker.FormatStrFormatter</a>('%1.5f')

locator = <a href="../../api/ticker_api.html#matplotlib.ticker.AutoLocator" title="View documentation for matplotlib.ticker.AutoLocator">matplotlib.ticker.AutoLocator</a>()

axs[2].xaxis.set_major_formatter(formatter)

axs[2].xaxis.set_major_locator(locator)

formatter = <a href="../../api/ticker_api.html#matplotlib.ticker.FormatStrFormatter" title="View documentation for matplotlib.ticker.FormatStrFormatter">matplotlib.ticker.FormatStrFormatter</a>('%1.5f')

axs[3].xaxis.set_major_formatter(formatter)

axs[3].xaxis.set_major_locator(locator)

</pre></div>

</div>

Finally, we can specify functions for the formatter using

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

<div class="highlight-python notranslate"><div class="highlight"><pre>def formatoddticks(x, pos):

"""Format odd tick positions

"""

if x % 2:

return '%1.2f' % x

else:

return ''

ax.plot(x1, y1)

formatter = <a href="../../api/ticker_api.html#matplotlib.ticker.FuncFormatter" title="View documentation for matplotlib.ticker.FuncFormatter">matplotlib.ticker.FuncFormatter</a>(formatoddticks)

ax.xaxis.set_major_formatter(formatter)

ax.xaxis.set_major_locator(locator)

</pre></div>

</div>

</div>

<h3>Dateticks<a class="headerlink" href="#dateticks" title="Permalink to this headline">¶</a></h3>

Matplotlib can accept <a class="reference external" href="https://docs.python.org/3/library/datetime.html#datetime.datetime" title="(in Python v3.7)"><code class="xref py py-obj docutils literal notranslate">datetime.datetime</code></a> and <code class="xref py py-obj docutils literal notranslate">numpy.datetime64</code>

objects as plotting arguments. Dates and times require special

formatting, which can often benefit from manual intervention. In

order to help, dates have spectial Locators and Formatters,

defined in the <a class="reference internal" href="../../api/dates_api.html#module-matplotlib.dates" title="matplotlib.dates"><code class="xref py py-obj docutils literal notranslate">matplotlib.dates</code></a> module.

A simple example is as follows. Note how we have to rotate the

tick labels so that they don't over-run each other.

<div class="highlight-python notranslate"><div class="highlight"><pre>import datetime

base = datetime.datetime(2017, 1, 1, 0, 0, 1)

time = [base + datetime.timedelta(days=x) for x in range(len(y1))]

ax.plot(time, y1)

ax.tick_params(axis='x', rotation=70)

</pre></div>

</div>

Maybe the format of the labels above is acceptable, but the choices is

rather idiosyncratic. We can make the ticks fall on the start of the month

by modifying <a class="reference internal" href="../../api/dates_api.html#matplotlib.dates.AutoDateLocator" title="matplotlib.dates.AutoDateLocator"><code class="xref py py-obj docutils literal notranslate">matplotlib.dates.AutoDateLocator</code></a>

<div class="highlight-python notranslate"><div class="highlight"><pre>import matplotlib.dates as mdates

locator = <a href="../../api/dates_api.html#matplotlib.dates.AutoDateLocator" title="View documentation for matplotlib.dates.AutoDateLocator">mdates.AutoDateLocator</a>(interval_multiples=True)

</pre></div>

</div>

However, this changes the tick labels. The easiest fix is to pass a format

to <a class="reference internal" href="../../api/dates_api.html#matplotlib.dates.DateFormatter" title="matplotlib.dates.DateFormatter"><code class="xref py py-obj docutils literal notranslate">matplotlib.dates.DateFormatter</code></a>. Also note that the 29th and the

next month are very close together. We can fix this by using the

<code class="xref py py-obj docutils literal notranslate">dates.DayLocator</code> class, which allows us to specify a list of days of the

month to use. Similar formatters are listed in the <a class="reference internal" href="../../api/dates_api.html#module-matplotlib.dates" title="matplotlib.dates"><code class="xref py py-obj docutils literal notranslate">matplotlib.dates</code></a> module.

<div class="highlight-python notranslate"><div class="highlight"><pre>locator = <a href="../../api/dates_api.html#matplotlib.dates.DayLocator" title="View documentation for matplotlib.dates.DayLocator">mdates.DayLocator</a>(bymonthday=[1, 15])

formatter = <a href="../../api/dates_api.html#matplotlib.dates.DateFormatter" title="View documentation for matplotlib.dates.DateFormatter">mdates.DateFormatter</a>('%b %d')

</pre></div>

</div>

</div>

<h2>Legends and Annotations<a class="headerlink" href="#legends-and-annotations" title="Permalink to this headline">¶</a></h2>

<li>Legends: <a class="reference internal" href="../intermediate/legend_guide.html">Legend guide</a></li>

<li>Annotations: <a class="reference internal" href="annotations.html">Annotations</a></li>

</ul>

</div></blockquote>

<a class="reference download internal" href="../../_downloads/text_intro.py" download=""><code class="xref download docutils literal notranslate">Download Python source code: text_intro.py</code></a></div>

<a class="reference download internal" href="../../_downloads/text_intro.ipynb" download=""><code class="xref download docutils literal notranslate">Download Jupyter notebook: text_intro.ipynb</code></a></div>

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Keywords: matplotlib code example, codex, python plot, pyplot

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Last updated on Aug 11, 2018.

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