Terms by Cluster Data Frame

>>> from techminer2.packages.networks.co_occurrence.user import TermsByClusterDataFrame
>>> (
...     TermsByClusterDataFrame()
...     #
...     # FIELD:
...     .with_field("raw_keywords")
...     .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_TECHNOLOGY 03:0461
1             INNOVATION 08:0990  ...             CROWDFUNDING 03:0335
2     FINANCIAL_SERVICES 05:0746  ...           SUSTAINABILITY 03:0227
3    FINANCIAL_INCLUSION 03:0590  ...  SUSTAINABLE_DEVELOPMENT 03:0227
4  FINANCIAL_INSTITUTION 03:0488  ...        LITERATURE_REVIEW 02:0560
5                SURVEYS 03:0484  ...
6                BANKING 03:0370  ...
7    MARKETPLACE_LENDING 03:0317  ...
8       ELECTRONIC_MONEY 03:0305  ...

[9 rows x 3 columns]