tashrifbillah

#!/usr/bin/env python

import json

reordered='/data/predict1/charts1.json'
raw='/data/predict1/predict-mongodb-backup/charts_20240612.json'

# find out the private charts in raw
# print 0-indexed indices of private charts from raw file

tashrifbillah

General documentation: https://www.gnu.org/software/screen/

Download from: https://ftp.gnu.org/gnu/screen/

Compiling instruction: https://www.gnu.org/software/screen/manual/html_node/Compiling-Screen.html

tashrifbillah

import pandas as pd

df=pd.read_csv('pennebakerctq01_definitions.csv')
dfgiven=pd.read_excel('cnb_ndar_codebook_v5.xlsx')


_aliases=df['Aliases'].unique() 
__aliases=[]
for e in _aliases:
    if pd.isna(e):

tashrifbillah

#!/bin/bash

# convert SSH public key to pem format
ssh-keygen -e -m PKCS8 -f git_rsa.pub > git_rsa.pem

# encrypt
openssl rsautl -encrypt -pubin -inkey git_rsa.pem -in message.txt -out message.enc

# decrypt
openssl rsautl -decrypt -inkey git_rsa -in message.enc

tashrifbillah

import pandas as pd

# cd /data/predict1/to_nda/nda-submissions
df=pd.read_csv('blood_saliva_rack_Pronet.csv')

index=[]
for i,row in df.iterrows():


    rc=row['Rack Code']

tashrifbillah

#!/usr/bin/env python

import sys
import pandas as pd

df=pd.read_csv(sys.argv[1],dtype=str)
df1=df.copy()

df1.rename(columns={'chric_record_id':'participant_id'},inplace=True)
df1["redcap_system_data_format_version"]=1

tashrifbillah

#!/usr/bin/env python

from glob import glob
from os.path import isfile, basename
import pandas as pd

subjects=glob('/data/predict1/data_from_nda/Pronet/PHOENIX/PROTECTED/*/raw/*')
subjects=[basename(s) for s in subjects]

print('for how many subjects inclusionexclusion_criteria_review does not exist?')

tashrifbillah

# execute it from within /data/predict1/data_from_nda/Prescient/PHOENIX/GENERAL

from os.path import dirname, join as pjoin
import pandas as pd
from glob import glob

files=glob('*/processed/*/interviews/open/*_combinedQCRecords.csv')

j=0
for file in files:

tashrifbillah

import pandas as pd

# this is API pulled from Yale REDCap
filename='pronet_dict_20230321.csv'
df=pd.read_csv(filename, dtype=str)

df1=df.copy()

# erase calcs, logics
# replace calc by text

tashrifbillah

#!/usr/bin/env python

import pandas as pd
from glob import glob


def get_count():

    for file in files:
        df=pd.read_csv(file)