textnets represents collections of texts as networks of documents and words. This provides novel possibilities for the visualization and analysis of texts.
import textnets as tn corpus = tn.Corpus(tn.examples.moon_landing) t = tn.Textnet(corpus.tokenized(), min_docs=1) t.plot(label_nodes=True, show_clusters=True, scale_nodes_by="birank", scale_edges_by="weight")
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If you have a project that you want the spaCy community to make use of, you can suggest it by submitting a pull request to the spaCy website repository. The Universe database is open-source and collected in a simple JSON file. For more details on the formats and available fields, see the documentation. Looking for inspiration your own spaCy plugin or extension? Check out the
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