Data Frame

>>> from techminer2.packages.associations import DataFrame
>>> (
...     DataFrame()
...     #
...     # COLUMNS:
...     .with_field("raw_author_keywords")
...     .having_terms_in_top(None)
...     .having_terms_ordered_by("OCC")
...     .having_term_occurrences_between(None, None)
...     .having_term_citations_between(None, None)
...     .having_terms_in(["FINTECH", "INNOVATION", "FINANCIAL_SERVICES"])
...     #
...     # ROWS:
...     .having_other_terms_in_top(10)
...     .having_other_terms_ordered_by("OCC")
...     .having_other_term_occurrences_between(None, None)
...     .having_other_term_citations_between(None, None)
...     .having_other_terms_in(None)
...     #
...     # 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()
... )
columns                       FINTECH 31:5168  ...  FINANCIAL_SERVICES 04:0667
rows                                           ...
FINTECH 31:5168                            31  ...                           3
INNOVATION 07:0911                          5  ...                           2
FINANCIAL_SERVICES 04:0667                  3  ...                           4
FINANCIAL_INCLUSION 03:0590                 3  ...                           0
FINANCIAL_TECHNOLOGY 03:0461                2  ...                           1
CROWDFUNDING 03:0335                        2  ...                           0
MARKETPLACE_LENDING 03:0317                 3  ...                           0
BUSINESS_MODELS 02:0759                     2  ...                           1
CYBER_SECURITY 02:0342                      2  ...                           0
CASE_STUDY 02:0340                          2  ...                           0

[10 rows x 3 columns]