Terms by Cluster Frame

Example

>>> from techminer2.thesaurus.descriptors import ApplyThesaurus, InitializeThesaurus

>>> # Restore the column values to initial values
>>> InitializeThesaurus(root_directory="examples/fintech/", quiet=True).run()
>>> ApplyThesaurus(root_directory="examples/fintech/", quiet=True).run()

>>> from techminer2.manuscript.discussion import ClusterDefinition
>>> (
...     ClusterDefinition()
...     #
...     # FIELD:
...     .with_field("descriptors")
...     .having_terms_in_top(30)
...     .having_terms_ordered_by("OCC")
...     .having_term_occurrences_between(None, None)
...     .having_term_citations_between(None, None)
...     .having_terms_in(None)
...     #
...     # NETWORK:
...     .using_clustering_algorithm_or_dict("louvain")
...     .using_association_index("association")
...     #
...     # TEXT:
...     .with_core_area("fintech")
...     .with_word_length((200, 400, 300))
...     #
...     # DATABASE:
...     .where_root_directory("examples/fintech/")
...     .where_database("main")
...     .where_record_years_range(None, None)
...     .where_record_citations_range(None, None)
...     .where_records_match(None)
...     #
...     .run()
... )

Cluster … Terms

0 0 … FINTECH 38:6131; THE_FINANCIAL_INDUSTRY 09:200… 1 1 … TECHNOLOGIES 15:1633; FINANCIAL_TECHNOLOGIES 1… <BLANKLINE> [2 rows x 4 columns]