.. _sphx_glr_auto_examples_utils_example_tsdisplay.py:


====================================
Displaying key timeseries statistics
====================================


Visualizing characteristics of a time series is a key component to effective
forecasting. In this example, we'll look at a very simple method to examine
critical statistics of a time series object.

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   <br/>




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    *

      .. image:: /auto_examples/utils/images/sphx_glr_example_tsdisplay_001.png
            :scale: 47

    *

      .. image:: /auto_examples/utils/images/sphx_glr_example_tsdisplay_002.png
            :scale: 47


.. rst-class:: sphx-glr-script-out

 Out::

    Data shape: 2820
    Data head:
    Jan 1749    58.0
    Feb 1749    62.6
    Mar 1749    70.0
    Apr 1749    55.7
    May 1749    85.0
    dtype: float64

    As evidenced by the more normally distributed values in the transformed series,
    using a Box-Cox transformation may prove useful prior to fitting your model.




|


.. code-block:: python

    print(__doc__)

    # Author: Taylor Smith <taylor.smith@alkaline-ml.com>

    import pmdarima as pm
    from pmdarima import datasets
    from pmdarima import preprocessing

    # We'll use the sunspots dataset for this example
    y = datasets.load_sunspots(True)
    print("Data shape: {}".format(y.shape[0]))
    print("Data head:")
    print(y.head())

    # Let's look at the series, its ACF plot, and a histogram of its values
    pm.tsdisplay(y, lag_max=90, title="Sunspots", show=True)

    # Notice that the histogram is very skewed. This is a prime candidate for
    # box-cox transformation
    y_bc, _ = preprocessing.BoxCoxEndogTransformer(lmbda2=1e-6).fit_transform(y)
    pm.tsdisplay(
        y_bc, lag_max=90, title="Sunspots (BoxCox-transformed)", show=True)

    print("""
    As evidenced by the more normally distributed values in the transformed series,
    using a Box-Cox transformation may prove useful prior to fitting your model.
    """)

**Total running time of the script:** ( 0 minutes  0.275 seconds)



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  .. container:: sphx-glr-download

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



  .. container:: sphx-glr-download

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


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

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