{ "cells": [ { "cell_type": "markdown", "metadata": {}, "source": [ "\n# Date tick labels\n\nMatplotlib date plotting is done by converting date instances into\ndays since an epoch (by default 1970-01-01T00:00:00). The\n:mod:`matplotlib.dates` module provides the converter functions `.date2num`\nand `.num2date` that convert `datetime.datetime` and `numpy.datetime64`\nobjects to and from Matplotlib's internal representation. These data\ntypes are registered with the unit conversion mechanism described in\n:mod:`matplotlib.units`, so the conversion happens automatically for the user.\nThe registration process also sets the default tick ``locator`` and\n``formatter`` for the axis to be `~.matplotlib.dates.AutoDateLocator` and\n`~.matplotlib.dates.AutoDateFormatter`.\n\nAn alternative formatter is the `~.dates.ConciseDateFormatter`,\nused in the second ``Axes`` below (see\n:doc:`/gallery/ticks/date_concise_formatter`), which often removes the need to\nrotate the tick labels. The last ``Axes`` formats the dates manually, using\n`~.dates.DateFormatter` to format the dates using the format strings documented\nat `datetime.date.strftime`.\n" ] }, { "cell_type": "code", "execution_count": null, "metadata": { "collapsed": false }, "outputs": [], "source": [ "import matplotlib.pyplot as plt\n\nimport matplotlib.cbook as cbook\nimport matplotlib.dates as mdates\n\n# Load a numpy record array from yahoo csv data with fields date, open, high,\n# low, close, volume, adj_close from the mpl-data/sample_data directory. The\n# record array stores the date as an np.datetime64 with a day unit ('D') in\n# the date column.\ndata = cbook.get_sample_data('goog.npz')['price_data']\n\nfig, axs = plt.subplots(3, 1, figsize=(6.4, 7), layout='constrained')\n# common to all three:\nfor ax in axs:\n ax.plot('date', 'adj_close', data=data)\n # Major ticks every half year, minor ticks every month,\n ax.xaxis.set_major_locator(mdates.MonthLocator(bymonth=(1, 7)))\n ax.xaxis.set_minor_locator(mdates.MonthLocator())\n ax.grid(True)\n ax.set_ylabel(r'Price [\\$]')\n\n# different formats:\nax = axs[0]\nax.set_title('DefaultFormatter', loc='left', y=0.85, x=0.02, fontsize='medium')\n\nax = axs[1]\nax.set_title('ConciseFormatter', loc='left', y=0.85, x=0.02, fontsize='medium')\nax.xaxis.set_major_formatter(\n mdates.ConciseDateFormatter(ax.xaxis.get_major_locator()))\n\nax = axs[2]\nax.set_title('Manual DateFormatter', loc='left', y=0.85, x=0.02,\n fontsize='medium')\n# Text in the x-axis will be displayed in 'YYYY-mm' format.\nax.xaxis.set_major_formatter(mdates.DateFormatter('%Y-%b'))\n# Rotates and right-aligns the x labels so they don't crowd each other.\nfor label in ax.get_xticklabels(which='major'):\n label.set(rotation=30, horizontalalignment='right')\n\nplt.show()" ] } ], "metadata": { "kernelspec": { "display_name": "Python 3", "language": "python", "name": "python3" }, "language_info": { "codemirror_mode": { "name": "ipython", "version": 3 }, "file_extension": ".py", "mimetype": "text/x-python", "name": "python", "nbconvert_exporter": "python", "pygments_lexer": "ipython3", "version": "3.13.2" } }, "nbformat": 4, "nbformat_minor": 0 }