Small Datasets for testing functionalities
Presentation
eds-scikit was build to work seamlessly on a pre-existing OMOP database. However, the library also provides some toy datasets so that you can try out some features even without having access to a database.
Usage
First, you can display all availables synthetic datasets:
from eds_scikit import datasets
datasets.list_all_synthetics()
# Out: ['load_ccam', 'load_consultation_dates', 'load_hierarchy', 'load_icd10', 'load_visit_merging', 'load_stay_duration', 'load_suicide_attempt', 'load_tagging', 'load_biology_data']
To load a specific dataset, simply run:
data = datasets.load_icd10()
data
# Out: ICD10Dataset(condition_occurrence, visit_occurrence)
The data object is similar to objects available in eds_scikit.io, namely:
For instance, tables are available as attributes:
data.condition_occurrence
# Out: person_id condition_source_value condition_start_datetime condition_status_source_value visit_occurrence_id
0 1 C10 2010-01-01 DP 11
1 1 E112 2010-01-01 DAS 12
2 1 D20 2012-01-01 DAS 13
3 1 A20 2020-01-01 DP 14
4 1 A21 2000-01-01 DP 15
5 1 X20 2000-01-01 DP 16
6 1 C10 2010-01-01 DP 16
7 1 C10 2010-01-01 DP 17
As shown in the tutorial, you can now try out the corresponding conditions_from_icd10() function.