cncd-package 0.1.2

A Python package for CNCD

Download

pip install cncd-package

Loading the QC checks class

from cncd_package.QC import QC_Check

Reading data

sharing paths of different datasets:

• \cncd-dc1\DATA SCIENCE DEPARTMENT\1_phenotype_data\3_master_files_entry_1_entry_2_raw\april_2023\entry_1\updated_master_cad_2nd_entry_april_2023.csv
• \cncd-dc1\DATA SCIENCE DEPARTMENT\1_phenotype_data\3_master_files_entry_1_entry_2_raw\april_2023\entry_1\updated_master_dm_2nd_entry_april_2023.csv
• \cncd-dc1\DATA SCIENCE DEPARTMENT\1_phenotype_data\3_master_files_entry_1_entry_2_raw\april_2023\entry_1\updated_master_hf_1st_entry_april_2023.csv
• \cncd-dc1\DATA SCIENCE DEPARTMENT\1_phenotype_data\3_master_files_entry_1_entry_2_raw\april_2023\entry_1\updated_master_nafld_1st_entry_april_2023.csv
• \cncd-dc1\DATA SCIENCE DEPARTMENT\1_phenotype_data\3_master_files_entry_1_entry_2_raw\april_2023\entry_1\updated_master_pgr_1st_entry_april_2023.csv
• \cncd-dc1\DATA SCIENCE DEPARTMENT\1_phenotype_data\3_master_files_entry_1_entry_2_raw\april_2023\entry_1\updated_master_promis_1st_entry_april_2023.csv
• \cncd-dc1\DATA SCIENCE DEPARTMENT\1_phenotype_data\3_master_files_entry_1_entry_2_raw\april_2023\entry_1\updated_master_stroke_1st_entry_april_2023.csv

import pandas as pd
import warnings

warnings.simplefilter('ignore')

promis_data = pd.read_csv(r"\\cncd-dc1\DATA SCIENCE DEPARTMENT\1_phenotype_data\3_master_files_entry_1_entry_2_raw\april_2023\entry_1\updated_master_promis_1st_entry_april_2023.csv")

Doing QC

qc = QC_Check(dataframe=promis_data, project_id="PROMIS")

Age Check

qc.age_check().head()

	study_id	age
0	D969	106.0
1	LY6648	5.0
2	LY6753	99.0
3	LZ6394	96.0
4	V3629	0.0

Gender Checks

qc.gender_check(gender='male')

	study_id	gender	result
0	LY7080	2.0	MR
1	LY7094	2.0	MR
2	LY7470	2.0	MR
3	V2125	2.0	MR
4	V2134	2.0	MR
...	...	...	...	...
65	R891	2.0	MR
66	R1052	2.0	MR
67	R1560	2.0	MR
68	R1577	2.0	MR
69	R1658	2.0	MR

70 rows × 4 columns

qc.gender_check(gender='female')

	study_id	gender	result
0	K1884	1.0	BIBI
1	LY2898	1.0	BIBI
2	LY2903	1.0	BIBI
3	LY2910	1.0	BANO
4	LY3855	1.0	BIBI
...	...	...	...	...
85	HZ93	1.0	BIBI
86	PZ6	1.0	BIBI
87	PY27	1.0	BIBI
88	SM191	1.0	BB
89	RZ9	1.0	BIBI

90 rows × 4 columns

Check QC status

qc.check_qc_status()

	study_id	status	mi	pre_mi	st_elevation	troponin_positive
0	D1	1.0	0.0	0.0	1.0	0.0
1	D2	1.0	0.0	0.0	1.0	NaN
2	D4	1.0	0.0	0.0	1.0	0.0
3	D5	1.0	0.0	0.0	1.0	2.0
4	D6	1.0	1.0	1.0	1.0	0.0
...	...	...	...	...	...	...
82820	RZ111	1.0	0.0	NaN	1.0	NaN
82827	RZ118	1.0	0.0	NaN	0.0	1.0
82828	RZ119	1.0	0.0	NaN	0.0	1.0
82830	RZ121	1.0	0.0	NaN	1.0	NaN
82831	RZ122	1.0	0.0	NaN	0.0	1.0

31966 rows × 6 columns