8000 DOC: more improve date example · matplotlib/matplotlib@865b09d · GitHub
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DOC: more improve date example
Co-authored-by: Tim Hoffmann <2836374+timhoffm@users.noreply.github.com> Co-authored-by: Elliott Sales de Andrade <quantum.analyst@gmail.com>
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‎examples/text_labels_and_annotations/date.py

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Date tick labels
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================
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Show how to make date plots in Matplotlib using date tick locators and
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formatters. See :doc:`/gallery/ticks_and_spines/major_minor_demo` for more
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information on controlling major and minor ticks.
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Matplotlib date plotting is done by converting date instances into
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days since an epoch (by default 1970-01-01T00:00:00). The
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:mod:`matplotlib.dates` module provides the converter functions `.date2num`
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and `.num2date`, which convert `datetime.datetime` and `numpy.datetime64`
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and `.num2date` that convert `datetime.datetime` and `numpy.datetime64`
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objects to and from Matplotlib's internal representation. These data
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types are registered with with the unit conversion mechanism described in
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types are registered with the unit conversion mechanism described in
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:mod:`matplotlib.units`, so the conversion happens automatically for the user.
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The registration process also sets the default tick ``locator`` and
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``formatter`` for the axis to be `~.matplotlib.dates.AutoDateLocator` and
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`~.matplotlib.dates.AutoDateFormatter`. These can be changed manually with
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`.Axis.set_major_locator` and `.Axis.set_major_formatter`; see for example
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:doc:`/gallery/ticks_and_spines/date_demo_convert`.
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`~.matplotlib.dates.AutoDateFormatter`.
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An alternative formatter is the `~.matplotlib.dates.ConciseDateFormatter`
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as described at :doc:`/gallery/ticks_and_spines/date_concise_formatter`,
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which often removes the need to rotate the tick labels.
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An alternative formatter is the `~.dates.ConciseDateFormatter`,
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used in the second ``Axes`` below (see
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:doc:`/gallery/ticks_and_spines/date_concise_formatter`), which often
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removes the need to rotate the tick labels. The last ``Axes``
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formats the dates manually, using `~.dates.DateFormatter` to
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format the dates using the format strings documented at
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`datetime.date.strftime`.
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"""
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import numpy as np
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import matplotlib.pyplot as plt
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import matplotlib.dates as mdates
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import matplotlib.cbook as cbook
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# column.
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data = cbook.get_sample_data('goog.npz', np_load=True)['price_data']
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fig, ax = plt.subplots()
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ax.plot('date', 'adj_close', data=data)
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fig, axs = plt.subplots(3, 1, figsize=(6.4, 7), constrained_layout=True)
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# common to all three:
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for ax in axs:
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ax.plot('date', 'adj_close', data=data)
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# Major ticks every half year, minor ticks every month,
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ax.xaxis.set_major_locator(mdates.MonthLocator(bymonth=(1, 7)))
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ax.xaxis.set_minor_locator(mdates.MonthLocator())
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ax.grid(True)
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ax.set_ylabel(r'Price [\$]')
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# Major ticks every 6 months.
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fmt_half_year = mdates.MonthLocator(interval=6)
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ax.xaxis.set_major_locator(fmt_half_year)
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# different formats:
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ax = axs[0]
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ax.set_title('DefaultFormatter', loc='left', y=0.85, x=0.02, fontsize='medium')
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# Minor ticks every month.
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fmt_month = mdates.MonthLocator()
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ax.xaxis.set_minor_locator(fmt_month)
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ax = axs[1]
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ax.set_title('ConciseFormatter', loc='left', y=0.85, x=0.02, fontsize='medium')
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ax.xaxis.set_major_formatter(
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mdates.ConciseDateFormatter(ax.xaxis.get_major_locator()))
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ax = axs[2]
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ax.set_title('Manual DateFormatter', loc='left', y=0.85, x=0.02,
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fontsize='medium')
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# Text in the x axis will be displayed in 'YYYY-mm' format.
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ax.xaxis.set_major_formatter(mdates.DateFormatter('%Y-%m'))
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# Round to nearest years.
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datemin = np.datetime64(data['date'][0], 'Y')
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datemax = np.datetime64(data['date'][-1], 'Y') + np.timedelta64(1, 'Y')
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ax.set_xlim(datemin, datemax)
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# Format the coords message box, i.e. the numbers displayed as the cursor moves
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# across the axes within the interactive GUI.
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ax.format_xdata = mdates.DateFormatter('%Y-%m')
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ax.format_ydata = lambda x: f'${x:.2f}' # Format the price.
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ax.grid(True)
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# Rotates and right aligns the x labels, and moves the bottom of the
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# axes up to make room for them.
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fig.autofmt_xdate()
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ax.xaxis.set_major_formatter(mdates.DateFormatter('%Y-%b'))
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# Rotates and right-aligns the x labels so they don't crowd each other.
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for label in ax.get_xticklabels(which='major'):
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label.set(rotation=30, horizontalalignment='right')
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plt.show()

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