

.. _sphx_glr_gallery_lines_bars_and_markers_scatter_demo2.py:


=============
Scatter Demo2
=============

Demo of scatter plot with varying marker colors and sizes.




.. image:: /gallery/lines_bars_and_markers/images/sphx_glr_scatter_demo2_001.png
    :align: center





.. code-block:: python

    import numpy as np
    import matplotlib.pyplot as plt
    import matplotlib.cbook as cbook

    # Load a numpy record array from yahoo csv data with fields date, open, close,
    # volume, adj_close from the mpl-data/example directory. The record array
    # stores the date as an np.datetime64 with a day unit ('D') in the date column.
    with cbook.get_sample_data('goog.npz') as datafile:
        price_data = np.load(datafile)['price_data'].view(np.recarray)
    price_data = price_data[-250:]  # get the most recent 250 trading days

    delta1 = np.diff(price_data.adj_close) / price_data.adj_close[:-1]

    # Marker size in units of points^2
    volume = (15 * price_data.volume[:-2] / price_data.volume[0])**2
    close = 0.003 * price_data.close[:-2] / 0.003 * price_data.open[:-2]

    fig, ax = plt.subplots()
    ax.scatter(delta1[:-1], delta1[1:], c=close, s=volume, alpha=0.5)

    ax.set_xlabel(r'$\Delta_i$', fontsize=15)
    ax.set_ylabel(r'$\Delta_{i+1}$', fontsize=15)
    ax.set_title('Volume and percent change')

    ax.grid(True)
    fig.tight_layout()

    plt.show()

**Total running time of the script:** ( 0 minutes  0.471 seconds)



.. container:: sphx-glr-footer


  .. container:: sphx-glr-download

     :download:`Download Python source code: scatter_demo2.py <scatter_demo2.py>`



  .. container:: sphx-glr-download

     :download:`Download Jupyter notebook: scatter_demo2.ipynb <scatter_demo2.ipynb>`

.. rst-class:: sphx-glr-signature

    `Generated by Sphinx-Gallery <https://sphinx-gallery.readthedocs.io>`_
