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

    Click :ref:`here <sphx_glr_download_intro_numpy_auto_examples_plot_polyfit.py>` to download the full example code
.. rst-class:: sphx-glr-example-title

.. _sphx_glr_intro_numpy_auto_examples_plot_polyfit.py:


Fitting to polynomial
=====================

Plot noisy data and their polynomial fit





.. image:: /intro/numpy/auto_examples/images/sphx_glr_plot_polyfit_001.png
    :class: sphx-glr-single-img





.. code-block:: python

    import numpy as np
    import matplotlib.pyplot as plt

    np.random.seed(12)

    x = np.linspace(0, 1, 20)
    y = np.cos(x) + 0.3*np.random.rand(20)
    p = np.poly1d(np.polyfit(x, y, 3))

    t = np.linspace(0, 1, 200)
    plt.plot(x, y, 'o', t, p(t), '-')
    plt.show()

**Total running time of the script:** ( 0 minutes  0.012 seconds)


.. _sphx_glr_download_intro_numpy_auto_examples_plot_polyfit.py:


.. only :: html

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



  .. container:: sphx-glr-download

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



  .. container:: sphx-glr-download

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


.. only:: html

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

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