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cncdpackage 0.1.3
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
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