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        "\n# Plotting text\n\nTo plot text, simply pass the text data to the plot function.  By default, the\ntext samples will be transformed into a vector of word counts and then modeled\nusing Latent Dirichlet Allocation (# of topics = 100) using a model fit to a\nlarge sample of wikipedia pages.  If you specify semantic=None, the word\ncount vectors will be plotted. To convert the text t0 a matrix (or list of\nmatrices), we also expose the format_data function.\n"
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    {
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      "execution_count": null,
      "metadata": {
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      },
      "outputs": [],
      "source": [
        "# Code source: Andrew Heusser\n# License: MIT\n\n# load hypertools\nimport hypertools as hyp\n\n# load the data\ndata = [['i like cats alot', 'cats r pretty cool', 'cats are better than dogs'],\n        ['dogs rule the haus', 'dogs are my jam', 'dogs are a mans best friend'],\n        'i haz a cheezeburger?']\n\n# plot it\nhyp.plot(data, 'o')\n\n# convert text to matrix without plotting\n# mtx = hyp.tools.format_data(data, vectorizer='TfidfVectorizer', semantic='NMF')"
      ]
    }
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