print(text)
columns = [
"byr",# (Birth Year)",
"iyr",# (Issue Year)",
"eyr",# (Expiration Year)",
"hgt",# (Height)",
"hcl",# (Hair Color)",
"ecl",# (Eye Color)",
"pid",# (Passport ID)",
"cid"]# (Country ID)"
data=pd.read_csv(data, names= ["Raw", "byr","iyr","eyr","hgt","hcl","ecl","pid","cid"], header=None)
def datacheck(check):
if check.find(col) > 0:
#magic = r'\b'+col+'\S*'
magic = col+'\S+'
return str(re.search(magic, check)[0]).replace(col+":","")
else:
return
for col in columns:
data[col]=data.apply(lambda row: datacheck(row.Raw), axis=1)
data = data.drop(columns=["Raw"])
#print(data)
data['missing'] = data.apply(lambda x: 8-x.count(), axis=1)
print(data['missing'].value_counts())
print(data)
