Background:
I have a function that gets a bunch of attributes from a database. Here is the function:
def getData(key, full_name, address, city, state, zipcode):
try:
url = 'https://personator.melissadata.net/v3/WEB/ContactVerify/doContactVerify'
payload={
'TransmissionReference': "test", # used by you to keep track of reference
'Actions': 'Check',
'Columns': 'Gender','DateOfBirth','DateOfDeath','EthnicCode','EthnicGroup','Education','PoliticalParty','MaritalStatus','HouseholdSize','ChildrenAgeRange','PresenceOfChildren','PresenceOfSenior','LengthOfResidence','OwnRent','CreditCardUser','Occupation','HouseholdIncome',
'CustomerID': key,# key
'Records': [{'FullName': str(full_name), 'AddressLine1': str(address), 'City': str(city), 'State': str(state), 'PostalCode': str(zipcode)}]
}
headers = {'Content-Type': 'application/json; charset=utf-8', 'Accept':'application/json', 'Host':'personator.melissadata.net','Expect': '100-continue', 'Connection':'Keep-Alive'}
r = requests.post(url, data=json.dumps(payload), headers=headers)
dom = json.loads(r.text)
Gender = dom['Records'][0]['Gender']
DateOfBirth = dom['Records'][0]['DateOfBirth']
DateOfDeath = dom['Records'][0]['DateOfDeath']
EthnicCode = dom['Records'][0]['EthnicCode']
EthnicGroup = dom['Records'][0]['EthnicGroup']
Education = dom['Records'][0]['Education']
PoliticalParty = dom['Records'][0]['PoliticalParty']
MaritalStatus = dom['Records'][0]['MaritalStatus']
HouseholdSize = dom['Records'][0]['HouseholdSize']
ChildrenAgeRange = dom['Records'][0]['ChildrenAgeRange']
PresenceOfChildren = dom['Records'][0]['PresenceOfChildren']
PresenceOfSenior = dom['Records'][0]['PresenceOfSenior']
LengthOfResidence = dom['Records'][0]['LengthOfResidence']
OwnRent = dom['Records'][0]['OwnRent']
CreditCardUser = dom['Records'][0]['CreditCardUser']
Occupation = dom['Records'][0]['Occupation']
HouseholdIncome = dom['Records'][0]['HouseholdIncome']
return Gender
except:
return None
To make a 'Gender' column I wrap the function into a lambda as so
df['Gender'] = df.apply(lambda row: getData(key, row['Full Name'], row['Address'], row['City'], row['State'], row['Zipcode']))
Objective: I want to do this process simultaneously for all the other attributes you see below Gender, how can I do this in Python.
You can return a dictionary, then expand a series of dictionary objects:
fields = ['Gender', 'DateOfBirth', etc.]
def getData(key, full_name, address, city, state, zipcode):
try:
# your code as before
dom = json.loads(r.text)
return {k: dom['Records'][0][k] for k in fields}
# modify below: good practice to specify exactly which error(s) to catch
except:
return {}
Then expand your series of dictionaries:
dcts = df.apply(lambda row: getData(key, row['Full Name'], row['Address'], row['City'],
row['State'], row['Zipcode']), axis=1)
df = df.join(pd.DataFrame(dcts.tolist()))
As per @spaniard's comment, if you want all available fields, you can simply use:
return json.loads(r.text)['Records'][0]
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