Terms by Cluster Summary

Example

>>> from techminer2.co_occurrence_network.keywords import TermsByClusterSummary
>>> df = (
...     TermsByClusterSummary()
...     #
...     # FIELD:
...     .having_terms_in_top(20)
...     .having_terms_ordered_by("OCC")
...     .having_term_occurrences_between(None, None)
...     .having_term_citations_between(None, None)
...     .having_terms_in(None)
...     #
...     # COUNTERS:
...     .using_term_counters(True)
...     #
...     # NETWORK:
...     .using_clustering_algorithm_or_dict("louvain")
...     .using_association_index("association")
...     #
...     # 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()
... )
>>> df   
   Cluster  ...                                              Terms
0        0  ...  FINTECH 32:5393; FINANCE 11:1950; FINANCIAL_SE...
1        1  ...  FINANCIAL_TECHNOLOGIES 03:0461; CROWDFUNDING 0...
2        2  ...  FINANCIAL_INSTITUTION 04:0746; COMMERCE 03:084...

[3 rows x 4 columns]