def process_file(headers):
"""You may modify this function"""
# Gets the indexes for each code-type used for definitions. Do not modify
field_index = {}
groupby_dict = {}
field_index['ICD10'] = opf.get_header_indices(headers, 'diag_icd10')
field_index['ICD9'] = opf.get_header_indices(headers, 'diag_icd9')
field_index['ICD_YEAR'] = opf.get_header_indices(headers, 'icd_years')
field_index['Patient_ID'] = opf.get_header_indices(headers, 'Patient_ID')
groupby_dict['AFIB_Codes'] = 'concat'
groupby_dict['Earliest_Afib_Diagnosis'] = 'min'
groupby_dict['Other_Malformations'] = 'concat'
groupby_dict['Minimum_Age_At_Other_Malformations'] = 'min'
return field_index, groupby_dict
def process_file(headers, output_column_names):
"""This function is used to find and specify which fields in Biobank you are interested in and what columns you want in your output file. You may modify this function."""
# Must Specify Field Numbers of Fields of Interest. Do Not Change
field_index = {}
# This tells the program where the codes are in the file
field_index['ICD10'] = opf.get_header_indices(
headers, '41202') + opf.get_header_indices(headers, '41204')
field_index['ICD9'] = opf.get_header_indices(
headers, '41203') + opf.get_header_indices(headers, '41205')
field_index['SelfRep_MC'] = opf.get_header_indices(headers, '20002',
'20009')
field_index['Year_Of_Birth'] = opf.get_header_indices(headers, '34')
output_column_names.append('Year_Of_Birth')
# I want each code to be a column name
for code in single_icd10_codes_of_interest:
output_column_names.append(code)
# I want 'Stroke' to be an output column
output_column_names.append('Stroke')
# I want to know what self-reported medical malformations the patient has and the minimum age at which the patient was diagnosed. So I'll have two self-reported columns. Patients will only be assigned a malformation if they meet age criteria.
output_column_names.append('SelfReported_Malformations')
output_column_names.append('Minimum_Age_At_SelfReported_Malformation')
return field_index, output_column_names
def process_file(headers, output_column_names):
"""You may modify this function"""
# Gets the indexes for each code-type used for definitions
field_index = {}
groupby_dict = {}
field_index['ICD10'] = opf.get_header_indices(headers, 'diag_icd10')
field_index['ICD9'] = opf.get_header_indices(headers, 'diag_icd9')
field_index['OPCS'] = opf.get_header_indices(headers, 'oper4')
field_index['ICD_YEAR'] = opf.get_header_indices(headers, 'icd_years')[0]
field_index['OPCS_YEAR'] = opf.get_header_indices(headers, 'opcs_years')[0]
field_index['Patient_ID'] = opf.get_header_indices(headers, 'Patient_ID')
for d in diseases:
output_column_names.append(d)
groupby_dict[d] = 'min'
return field_index, output_column_names, groupby_dict
# ----------------------------------------------
# (DO-NOT-CHANGE
f = open(config.ukb_file)
header = f.readline()
headers = header.split('\t')
headers[0] = '0_0'
line_list = []
lines = f.readlines()
f.close()
# DO-NOT-CHANGE)
# Must Specify Field Numbers of Fields of Interest
year_of_birth_index = opf.get_header_indices(headers, '34')
icd10_index = opf.get_header_indices(
headers, '41202') + opf.get_header_indices(headers, '41204')
opcs_index = opf.get_header_indices(headers, '41200') + opf.get_header_indices(
headers, '41210')
icd9_index = opf.get_header_indices(headers, '41203') + opf.get_header_indices(
headers, '41205')
selfrep_mc_index = opf.get_header_indices(headers, '20002', '20009')
selfrep_op_index = opf.get_header_indices(headers, '20004', '20011')
# Names of Columns for Output File
fieldnames = ['Patient_ID']
fieldnames.append('Year_Of_Birth')
fieldnames.append('CHD')
fieldnames.append('Confirmed')
attrib_select = sh.sheet_to_dict(reader, s, 'Attribute', 'Input')
attrib_conversion = sh.sheet_to_dict(reader, s, 'Attribute', 'Binary', dict_values=True)
with open(config.ukb_file) as f:
header = f.readline()
headers = header.split('\t')
headers[0] = '0_0'
attrib_index = {}
# We find the indicies of the attributes we are interested in.
for a in attrib:
if attrib_select[a] in ('F', 'A'): # There will only be one column associated with this attribute
attrib_index[a] = opf.get_header_indices(headers, attrib[a])
else: # Output all values into separate columns
all_indices = opf.get_header_indices(headers, attrib[a])
if len(all_indices) > 1:
column_num = 0
for index in all_indices:
new_column = a + '_' + str(column_num) # Format: Attribute_0, Attribute_1, etc.
attrib_index[new_column] = [index]
attrib_select[new_column] = attrib_select[a]
attrib_conversion[new_column] = attrib_conversion[a]
column_num += 1
else:
attrib_index[a] = all_indices