def greater_than_con(study_var,var,site_ID,file,cohort_id, site,limit):
'''Function to capture the phenotype specific data above a certain limit (limit included)
Writes data to a seperate tab in an excel spreadsheet.'''
size = len(var)
end_var= list()
total_vals = tot_values(var)
count = 0
site_values = list()
study_values = list()
site_ID_values =list()
cohort_ID_values = list()
recorded_values = list()
for i in range(size):
size_temp = total_vals[i]
temp = var[i]
for j in range (size_temp):
if temp[j] >= limit:
count= count + 1
site_values .append(value_checker(site[i][j]))
study_values.append(value_checker(study_var[i][j]))
site_ID_values.append(value_checker(site_ID[i][j]))
cohort_ID_values.append(value_checker(cohort_id[i][j]))
recorded_values.append(value_checker(temp[j]))
end_var.append(count)
count = 0
data = creating_DF_with_values (site_values,study_values,site_ID_values,cohort_ID_values,recorded_values)
data.to_excel(file , sheet_name = 'Values >= ' + str(limit))
return end_var
def not_con1_exc_zero_sex(study_var,var,site_ID,file,cohort_id,site, limit,sex):
'''Function to capture the phenotype specific data between a certain limit and zero (both values excluded).
This function is intended to be utilised for sex specific biomarkers and it returns
either the male or female data.Writes data to a seperate tab in an excel spreadsheet.'''
size = len(var)
end_var= list()
total_vals = tot_values(var)
count = 0
site_values = list()
study_values = list()
site_ID_values =list()
cohort_ID_values = list()
recorded_values = list()
for i in range(size):
size_temp = total_vals[i]
temp = var[i]
for j in range (size_temp):
if temp[j] > 0 and temp[j] < limit:
count= count + 1
site_values .append(value_checker(site[i][j]))
study_values.append(value_checker(study_var[i][j]))
site_ID_values.append(value_checker(site_ID[i][j]))
cohort_ID_values.append(value_checker(cohort_id[i][j]))
recorded_values.append(value_checker(temp[j]))
end_var.append(count)
count = 0
data = creating_DF_with_values (site_values,study_values,site_ID_values,cohort_ID_values,recorded_values)
data.to_excel(file , sheet_name='0 < ' + sex + ' Values < '+ str(limit))
return end_var
def greater_than_con_samefile(study_var,var,site_ID,file,cohort_id, site,limit):
'''Function to capture the phenotype specific data above a certain limit (limit included)
Writes all data out to a single passed in file rather than different tabs in an excel spreadsheet.'''
size = len(var)
end_var= list()
total_vals = tot_values(var)
count = 0
file.write('\n'+'Values >= ' + str(limit)+'\n')
heading = "Site"+","+"Site ID "+","+"Study ID" +","+"Cohort ID"+ ","+"Recorded Value"
file.write( heading +"\n" )
for i in range(size):
size_temp = total_vals[i]
temp = var[i]
for j in range (size_temp):
if temp[j] >= limit:
count= count + 1
w = value_checker(site[i][j])
x= value_checker(study_var[i][j])
y = value_checker(site_ID[i][j])
z = value_checker(cohort_id[i][j])
a = value_checker(temp[j])
line = str(w) +','+ str(x) + ',' + str(y)+ ',' + str(z) + ','+ str(a)
file.write( line +'\n')
end_var.append(count)
count = 0
file.write('\n\n')
return end_var
def con1_to_con2_samefile(study_var,var,site_ID,file,cohort_id, site,limit1,limit2):
'''Function to capture the phenotype specific data between two different limits (with both excluded)
Writes all data out to a single passed in file rather than different tabs in an excel spreadsheet.'''
size = len(var)
end_var= list()
total_vals = tot_values(var)
count = 0
file.write('\n'+str(limit1) + ' < Values < ' + str(limit2)+'\n')
heading = "Site"+","+"Site ID "+","+"Study ID" +","+"Cohort ID"+ ","+"Recorded Value"
file.write( heading +"\n" )
for i in range(size):
size_temp = total_vals[i]
temp = var[i]
for j in range (size_temp):
if temp[j] > limit1 and temp[j] < limit2 :
count= count + 1
w = value_checker(site[i][j])
x= value_checker(study_var[i][j])
y = value_checker(site_ID[i][j])
z = value_checker(cohort_id[i][j])
a = value_checker(temp[j])
line = str(w) +','+ str(x) + ',' + str(y)+ ',' + str(z) + ','+ str(a)
file.write( line +'\n')
end_var.append(count)
count = 0
file.write('\n')
return end_var
def below_LLQ_to_con1_samefile(study_var,var,site_ID,file,cohort_id, site,llq,limit):
'''Older Function to capture the phenotype specific data between a certain limit and the lower limit of quantification
(with the lower level of quantification included and the value included). Writes all data out to
a single passed in file rather than different tabs in an excel spreadsheet.'''
size = len(var)
end_var= list()
total_vals = tot_values(var)
file.write('\n'+'LLQ =< Values <= '+ str(limit)+'\n')
heading = "Site"+","+"Site ID "+","+"Study ID" +","+"Cohort ID"+ ","+"Recorded Value"
file.write( heading +"\n" )
count = 0
for i in range(size):
size_temp = total_vals[i]
temp = var[i]
for j in range (size_temp):
if temp[j] >= llq and temp[j] <= limit:
count= count + 1
w = value_checker(site[i][j])
x= value_checker(study_var[i][j])
y = value_checker(site_ID[i][j])
z = value_checker(cohort_id[i][j])
a = value_checker(temp[j])
line = str(w) +','+ str(x) + ',' + str(y)+ ',' + str(z) + ','+ str(a)
file.write( line +'\n')
end_var.append(count)
count = 0
file.write('\n\n')
return end_var
def con1_to_con2(study_var,var,site_ID,file,cohort_id, site,limit1,limit2):
'''Function to capture the phenotype specific data between two different limits (with both excluded)
Writes data to a seperate tab in an excel spreadsheet.'''
size = len(var)
end_var= list()
total_vals = tot_values(var)
count = 0
site_values = list()
study_values = list()
site_ID_values =list()
cohort_ID_values = list()
recorded_values = list()
for i in range(size):
size_temp = total_vals[i]
temp = var[i]
for j in range (size_temp):
if temp[j] > limit1 and temp[j] < limit2 :
count= count + 1
site_values .append(value_checker(site[i][j]))
study_values.append(value_checker(study_var[i][j]))
site_ID_values.append(value_checker(site_ID[i][j]))
cohort_ID_values.append(value_checker(cohort_id[i][j]))
recorded_values.append(value_checker(temp[j]))
end_var.append(count)
count = 0
data = creating_DF_with_values (site_values,study_values,site_ID_values,cohort_ID_values,recorded_values)
data.to_excel(file , sheet_name = str(limit1) + ' < Values < ' + str(limit2))
return end_var
def below_LLQ_to_con1(study_var,var,site_ID,file,cohort_id, site,llq,limit):
'''Function to capture the phenotype specific data between a certain limit and the lower limit of quantification
(with the lower level of quantification included and the value included). Writes data to a seperate tab in an excel spreadsheet.'''
size = len(var)
end_var= list()
total_vals = tot_values(var)
count = 0
site_values = list()
study_values = list()
site_ID_values =list()
cohort_ID_values = list()
recorded_values = list()
for i in range(size):
size_temp = total_vals[i]
temp = var[i]
for j in range (size_temp):
if temp[j] >= llq and temp[j] <= limit:
count= count + 1
site_values .append(value_checker(site[i][j]))
study_values.append(value_checker(study_var[i][j]))
site_ID_values.append(value_checker(site_ID[i][j]))
cohort_ID_values.append(value_checker(cohort_id[i][j]))
recorded_values.append(value_checker(temp[j]))
end_var.append(count)
count = 0
data = creating_DF_with_values (site_values,study_values,site_ID_values,cohort_ID_values,recorded_values)
data.to_excel(file , sheet_name='LLQ =< Values <= '+ str(limit))
return end_var
def remove_inserted_values(all_sites, branching, missing):
'''Original logic for removing the inserted values for branching and missing values. '''
size = len(all_sites)
new_site_var = list(all_sites)
total_vals = tot_values(all_sites)
for i in range(size):
size_temp = total_vals[i]
temp = all_sites[i]
for j in range(size_temp):
if temp[j] == branching or temp[j] == str(branching) or temp[
j] == missing or temp[j] == str(missing):
new_site_var.remove(temp[j])
return new_site_var
def greater_than_con_original(var, limit):
'''Older function which just captures all values above a certain limit (included)
without writing to a file. '''
size = len(var)
end_var= list()
total_vals = tot_values(var)
count = 0
for i in range(size):
size_temp = total_vals[i]
temp = var[i]
for j in range (size_temp):
if temp[j] >= limit:
count= count + 1
end_var.append(count)
count = 0
return end_var
def con1_to_con2_original(var, limit1, limit2):
'''Older function which just captures all values between two limits (with both excluded)
without writing to a file. '''
size = len(var)
end_var= list()
total_vals = tot_values(var)
count = 0
for i in range(size):
size_temp = total_vals[i]
temp = var[i]
for j in range (size_temp):
if temp[j] > limit1 and temp[j] < limit2 :
count= count + 1
end_var.append(count)
count = 0
return end_var
def above_con1_exc_zero_original(var, limit):
'''Older function which just captures all values between zero(excluded)
and a certain value(included) without writing to a file. '''
size = len(var)
end_var= list()
total_vals = tot_values(var)
count = 0
for i in range(size):
size_temp = total_vals[i]
temp = var[i]
for j in range (size_temp):
if temp[j] <= limit and temp[j] >0 :
count= count + 1
end_var.append(count)
count = 0
return end_var
def below_LLQ_to_con1_original(var,llq,limit):
'''Older function which just captures all values between the lower limit of quantification(included)
and a certain value(excluded) without writing to a file. '''
size = len(var)
end_var= list()
total_vals = tot_values(var)
count = 0
for i in range(size):
size_temp = total_vals[i]
temp = var[i]
for j in range (size_temp):
if temp[j] >= llq and temp[j] < limit:
count= count + 1
end_var.append(count)
count = 0
return end_var
stat_table = pd.DataFrame({ 'Minimum' : minimum,
'Maximum' : maximum,
'Mean' : mean,
'Median' : median,
'Standard Deviation' : stand_dev }, index=sites)
print(stat_table)
stat_table.to_excel(writer , sheet_name='Sheet1')
##########
#QC table
total = tot_values(glucose_all_sites)
null_num = null_number(glucose_all_sites)
zero_nums = zero_number(glucose_all_sites)
LLD_inc_zero_num = LLD_inc_zero(glucose_all_sites,lld_glucose)
LLD_exc_zero_num = LLD_exc_zero(glucose_all_sites,lld_glucose)
ULD_num =ULD(glucose_all_sites,uld_glucose)
QC_table = pd.DataFrame({ 'Total Values ' : total ,
'Null Values ' : null_num,
'Zero Values ' : zero_nums,
'Values Below LLD (inc 0) ' : LLD_inc_zero_num,
'Values Below LLD (exc 0)' :LLD_exc_zero_num ,
'Values Above ULD ': ULD_num}, index=sites)
print(QC_table)