.. DO NOT EDIT.
.. THIS FILE WAS AUTOMATICALLY GENERATED BY SPHINX-GALLERY.
.. TO MAKE CHANGES, EDIT THE SOURCE PYTHON FILE:
.. "auto_examples/plot_multivariate_timeseries.py"
.. LINE NUMBERS ARE GIVEN BELOW.

.. only:: html

    .. note::
        :class: sphx-glr-download-link-note

        :ref:`Go to the end <sphx_glr_download_auto_examples_plot_multivariate_timeseries.py>`
        to download the full example code.

.. rst-class:: sphx-glr-example-title

.. _sphx_glr_auto_examples_plot_multivariate_timeseries.py:


Multivariate and time series
============================

Principal components and clustering (via scikit-learn), and a seasonal
decomposition (via statsmodels), all redrawn in the depictr theme.

.. GENERATED FROM PYTHON SOURCE LINES 8-16

.. code-block:: Python


    import numpy as np
    import pandas as pd

    import depictr as dp

    wb = dp.wellbeing_survey()








.. GENERATED FROM PYTHON SOURCE LINES 17-18

A PCA biplot, coloured by group, with the variable loadings.

.. GENERATED FROM PYTHON SOURCE LINES 18-21

.. code-block:: Python

    p = dp.pca_plot(wb, group="region")
    p




.. image-sg:: /auto_examples/images/sphx_glr_plot_multivariate_timeseries_001.png
   :alt: plot multivariate timeseries
   :srcset: /auto_examples/images/sphx_glr_plot_multivariate_timeseries_001.png
   :class: sphx-glr-single-img





.. GENERATED FROM PYTHON SOURCE LINES 22-23

k-means clusters on the first two principal components.

.. GENERATED FROM PYTHON SOURCE LINES 23-26

.. code-block:: Python

    p = dp.cluster_plot(wb, k=3)
    p




.. image-sg:: /auto_examples/images/sphx_glr_plot_multivariate_timeseries_002.png
   :alt: plot multivariate timeseries
   :srcset: /auto_examples/images/sphx_glr_plot_multivariate_timeseries_002.png
   :class: sphx-glr-single-img





.. GENERATED FROM PYTHON SOURCE LINES 27-28

A monthly series with a trend, a 12-period season and noise.

.. GENERATED FROM PYTHON SOURCE LINES 28-35

.. code-block:: Python

    rng = np.random.default_rng(0)
    t = np.arange(120)
    series = pd.Series(
        50 + 0.3 * t + 10 * np.sin(2 * np.pi * t / 12) + rng.normal(0, 3, 120),
        index=pd.period_range("2016-01", periods=120, freq="M"),
    )








.. GENERATED FROM PYTHON SOURCE LINES 36-37

Its seasonal decomposition (observed, trend, seasonal, residual).

.. GENERATED FROM PYTHON SOURCE LINES 37-39

.. code-block:: Python

    p = dp.decompose_plot(series, period=12)
    p



.. image-sg:: /auto_examples/images/sphx_glr_plot_multivariate_timeseries_003.png
   :alt: plot multivariate timeseries
   :srcset: /auto_examples/images/sphx_glr_plot_multivariate_timeseries_003.png
   :class: sphx-glr-single-img






.. rst-class:: sphx-glr-timing

   **Total running time of the script:** (0 minutes 0.823 seconds)


.. _sphx_glr_download_auto_examples_plot_multivariate_timeseries.py:

.. only:: html

  .. container:: sphx-glr-footer sphx-glr-footer-example

    .. container:: sphx-glr-download sphx-glr-download-jupyter

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

    .. container:: sphx-glr-download sphx-glr-download-python

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

    .. container:: sphx-glr-download sphx-glr-download-zip

      :download:`Download zipped: plot_multivariate_timeseries.zip <plot_multivariate_timeseries.zip>`


.. only:: html

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

    `Gallery generated by Sphinx-Gallery <https://sphinx-gallery.github.io>`_