Terms by Cluster Frame

>>> from techminer2.packages.networks.co_occurrence.keywords import TermsByClusterDataFrame
>>> (
...     TermsByClusterDataFrame()
...     #
...     # 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)
...     #
...     # NETWORK:
...     .using_clustering_algorithm_or_dict("louvain")
...     .using_association_index("association")
...     #
...     # DATABASE:
...     .where_root_directory_is("example/")
...     .where_database_is("main")
...     .where_record_years_range_is(None, None)
...     .where_record_citations_range_is(None, None)
...     .where_records_match(None)
...     #
...     .run()
... )
                                        0  ...                              2
0                         FINTECH 32:5393  ...  FINANCIAL_INSTITUTION 04:0746
1                         FINANCE 11:1950  ...               COMMERCE 03:0846
2               FINANCIAL_SERVICE 08:1680  ...    FINANCIAL_INCLUSION 03:0590
3                      INNOVATION 08:0990  ...   DIGITAL_TECHNOLOGIES 02:0494
4                  BUSINESS_MODEL 04:1472  ...
5                      BLOCKCHAIN 04:0945  ...
6   FINANCIAL_SERVICES_INDUSTRIES 03:0949  ...
7                         SURVEYS 03:0484  ...
8                         BANKING 03:0370  ...
9             MARKETPLACE_LENDING 03:0317  ...
10               ELECTRONIC_MONEY 03:0305  ...

[11 rows x 3 columns]