Contingency Table

>>> from techminer2.tech_mining.document.kmeans import contingency_table
>>> contingency_table(
...     field='words',
...     #
...     # ITEM FILTERS:
...     top_n=50,
...     occ_range=(None, None),
...     gc_range=(None, None),
...     custom_items=None,
...     #
...     # KMEANS PARAMS:
...     n_themes=6,
...     init="k-means++",
...     n_init=10,
...     max_iter=300,
...     kmeans_tol=0.0001,
...     algorithm="auto",
...     #
...     # DATABASE PARAMS:
...     root_dir="example/",
...     database="main",
...     year_filter=(None, None),
...     cited_by_filter=(None, None),
... ).head(20)
theme                TH_0  TH_1  TH_2  TH_3  TH_4  TH_5
words
fintech 50:8135        10    10    15     1     7     7
financial 44:7123       9     9    13     1     7     5
© 42:6879              10     9     9     1     6     7
technology 39:6527      9    10     7     1     7     5
new 26:4793             1    10     6     1     6     2
service 26:4327         6     8     1     1     6     4
industry 23:4517        2     8     4     0     6     3
study 23:3158           8     1     3     1     6     4
model 19:3820           6     4     2     1     4     2
innovation 19:3070      1     3     6     1     7     1
development 19:2499     2     2     3     0     6     6
author 18:2443          5     0     5     1     3     4
market 17:3446          0     5     3     0     4     5
data 17:2392            7     2     6     1     0     1
research 17:2383        4     2     5     1     2     3
paper 14:2240           4     1     3     1     5     0
finance 14:2199         1     4     7     0     0     2
result 14:2183          6     1     1     1     4     1
sector 13:2748          2     4     2     1     2     2
institution 13:2648     0     6     1     0     4     2