>>> from sklearn.decomposition import PCA
>>> from techminer2.factor_analysis.tfidf import terms_by_dimension_frame
>>> terms_by_dimension_frame(
... #
... # PARAMS:
... field="author_keywords",
... #
... # TF PARAMS:
... is_binary=True,
... cooc_within=1,
... #
... # TF-IDF PARAMS:
... norm=None,
... use_idf=False,
... smooth_idf=False,
... sublinear_tf=False,
... #
... # TERM PARAMS:
... top_n=20,
... occ_range=(None, None),
... gc_range=(None, None),
... custom_terms=None,
... #
... # DESOMPOSITION PARAMS:
... decomposition_estimator = PCA(
... n_components=5,
... whiten=False,
... svd_solver="auto",
... tol=0.0,
... iterated_power="auto",
... n_oversamples=10,
... power_iteration_normalizer="auto",
... random_state=0,
... ),
... #
... # DATABASE PARAMS:
... root_dir="example/",
... database="main",
... year_filter=(None, None),
... cited_by_filter=(None, None),
... ).head()
dim 0 1 2 3 4
author_keywords
FINTECH 31:5168 4.959197 -0.131331 -0.127054 -0.021353 0.127476
INNOVATION 07:0911 0.316050 1.870215 1.111843 -0.552452 -0.021560
FINANCIAL_SERVICES 04:0667 -0.082353 0.895051 0.128205 1.239682 -0.242869
FINANCIAL_INCLUSION 03:0590 -0.039071 -0.170843 -0.618483 -0.383141 -0.474122
FINANCIAL_TECHNOLOGY 03:0461 -0.228786 0.327462 -0.051164 0.419388 -0.291788