.. _sphx_glr_auto_examples_plot_text.py:


=============================
Plotting text
=============================

To plot text, simply pass the text data to the plot function.  By default, the
text samples will be transformed into a vector of word counts and then modeled
using Latent Dirichlet Allocation (# of topics = 100) using a model fit to a
large sample of wikipedia pages.  If you specify semantic=None, the word
count vectors will be plotted. To convert the text t0 a matrix (or list of
matrices), we also expose the format_data function.




.. image:: /auto_examples/images/sphx_glr_plot_text_001.png
    :align: center





.. code-block:: python


    # Code source: Andrew Heusser
    # License: MIT

    # load hypertools
    import hypertools as hyp

    # load the data
    data = [['i like cats alot', 'cats r pretty cool', 'cats are better than dogs'],
            ['dogs rule the haus', 'dogs are my jam', 'dogs are a mans best friend'],
            'i haz a cheezeburger?']

    # plot it
    hyp.plot(data, 'o')

    # convert text to matrix without plotting
    # mtx = hyp.tools.format_data(data, vectorizer='TfidfVectorizer', semantic='NMF')

**Total running time of the script:** ( 0 minutes  7.097 seconds)



.. only :: html

 .. container:: sphx-glr-footer


  .. container:: sphx-glr-download

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



  .. container:: sphx-glr-download

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


.. only:: html

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

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