.. DO NOT EDIT. .. THIS FILE WAS AUTOMATICALLY GENERATED BY SPHINX-GALLERY. .. TO MAKE CHANGES, EDIT THE SOURCE PYTHON FILE: .. "gallery/misc/keyword_plotting.py" .. LINE NUMBERS ARE GIVEN BELOW. .. only:: html .. meta:: :keywords: codex .. note:: :class: sphx-glr-download-link-note :ref:`Go to the end ` to download the full example code .. rst-class:: sphx-glr-example-title .. _sphx_glr_gallery_misc_keyword_plotting.py: ====================== Plotting with keywords ====================== Some data structures, like dict, `structured numpy array `_ or `pandas.DataFrame` provide access to labelled data via string index access ``data[key]``. For these data types, Matplotlib supports passing the whole datastructure via the ``data`` keyword argument, and using the string names as plot function parameters, where you'd normally pass in your data. .. GENERATED FROM PYTHON SOURCE LINES 15-31 .. image-sg:: /gallery/misc/images/sphx_glr_keyword_plotting_001.png :alt: keyword plotting :srcset: /gallery/misc/images/sphx_glr_keyword_plotting_001.png, /gallery/misc/images/sphx_glr_keyword_plotting_001_2_00x.png 2.00x :class: sphx-glr-single-img .. code-block:: Python import matplotlib.pyplot as plt import numpy as np np.random.seed(19680801) data = {'a': np.arange(50), 'c': np.random.randint(0, 50, 50), 'd': np.random.randn(50)} data['b'] = data['a'] + 10 * np.random.randn(50) data['d'] = np.abs(data['d']) * 100 fig, ax = plt.subplots() ax.scatter('a', 'b', c='c', s='d', data=data) ax.set(xlabel='entry a', ylabel='entry b') plt.show() .. _sphx_glr_download_gallery_misc_keyword_plotting.py: .. only:: html .. container:: sphx-glr-footer sphx-glr-footer-example .. container:: sphx-glr-download sphx-glr-download-jupyter :download:`Download Jupyter notebook: keyword_plotting.ipynb ` .. container:: sphx-glr-download sphx-glr-download-python :download:`Download Python source code: keyword_plotting.py ` .. only:: html .. rst-class:: sphx-glr-signature `Gallery generated by Sphinx-Gallery `_