从 melissa 数据库中提取数据，得到一个类型错误：("一元 +： 'str'' 的错误操作数类型"

Question

对于此函数：

def getData(key, full_name, address):
        url = 'https://personator.melissadata.net/v3/WEB/ContactVerify/doContactVerify?id=' + key +'&full=' 
        + full_name +'&a1=' + address
        xml = request.get(url)
        dom = parseString(xml.text)
        response = dom.getElementsByTagName('response')
        Gender = getElementValue(dom, 'Gender')
        DateOfBirth = getElementValue(dom, 'DateOfBirth')
        DateOfDeath = getElementValue(dom, 'DateOfDeath')
        EthnicCode = getElementValue(dom, 'EthnicCode')
        EthnicGroup = getElementValue(dom, 'EthnicGroup')
        Education = getElementValue(dom, 'Education')
        PoliticalParty = getElementValue(dom, 'PoliticalParty')
        MaritalStatus = getElementValue(dom, 'MaritalStatus')
        HouseholdSize = getElementValue(dom, 'HouseholdSize')
        ChildrenAgeRange = getElementValue(dom, 'ChildrenAgeRange')
        PresenceOfChildren = getElementValue(dom, 'PresenceOfChildren')
        PresenceOfSenior = getElementValue(dom, 'PresenceOfSenior')
        LengthOfResidence = getElementValue(dom, 'LengthOfResidence')
        OwnRent = getElementValue(dom, 'OwnRent')
        CreditCardUser = getElementValue(dom, 'CreditCardUser')
        Occupation = getElementValue(dom, 'Occupation')
        HouseholdIncome = getElementValue(dom, 'HouseholdIncome')
        return Gender

当我将其包装到lambda中时：

df['Gender'] = df.apply(lambda row: getData(key, row['Full Name'], row['Address']), axis = 1)

我收到此错误：

TypeError: ("bad operand type for unary +: 'str'", 'occurred at index 0')

这里发生：

   2         url = 'https://personator.melissadata.net/v3/WEB/ContactVerify/doContactVerify?id=' + key +'&full='
----> 3         + full_name +'&a1=' + address

如何解决此问题？

为了完整起见，这里是整个代码（没有Melissa键）：

from xml.dom.minidom import parse,parseString
import xml.dom.minidom
import requests
import sys
import pandas as pd
import numpy as np
key = ''
df = pd.read_csv('data.csv')
def getElementValue(p_dom,p_element):
    if len(p_dom.getElementsByTagName(p_element)) > 0:
       l_value=p_dom.getElementsByTagName(p_element)[0]
       return(l_value.firstChild.data)
    else:
       l_value='NaN'
       return(l_value)
def getData(key, full_name, address):
        url = 'https://personator.melissadata.net/v3/WEB/ContactVerify/doContactVerify?id=' + key +'&full=' 
        + full_name +'&a1=' + address
        xml = request.get(url)
        dom = parseString(xml.text)
        response = dom.getElementsByTagName('response')
        Gender = getElementValue(dom, 'Gender')
        DateOfBirth = getElementValue(dom, 'DateOfBirth')
        DateOfDeath = getElementValue(dom, 'DateOfDeath')
        EthnicCode = getElementValue(dom, 'EthnicCode')
        EthnicGroup = getElementValue(dom, 'EthnicGroup')
        Education = getElementValue(dom, 'Education')
        PoliticalParty = getElementValue(dom, 'PoliticalParty')
        MaritalStatus = getElementValue(dom, 'MaritalStatus')
        HouseholdSize = getElementValue(dom, 'HouseholdSize')
        ChildrenAgeRange = getElementValue(dom, 'ChildrenAgeRange')
        PresenceOfChildren = getElementValue(dom, 'PresenceOfChildren')
        PresenceOfSenior = getElementValue(dom, 'PresenceOfSenior')
        LengthOfResidence = getElementValue(dom, 'LengthOfResidence')
        OwnRent = getElementValue(dom, 'OwnRent')
        CreditCardUser = getElementValue(dom, 'CreditCardUser')
        Occupation = getElementValue(dom, 'Occupation')
        HouseholdIncome = getElementValue(dom, 'HouseholdIncome')
        return Gender
df['Gender'] = df.apply(lambda row: getData(key, row['Full Name'], row['Address']), axis = 1)

我已经使用相同的方法成功地从 zillow 和 mapquest 中提取数据，但我似乎无法让它为 Melissa 工作。

Answer 1

你试过这个吗？

 url = 'https://personator.melissadata.net/v3/WEB/ContactVerify/doContactVerify?id=' + str(key) +'&full=' 
    + str(full_name) +'&a1=' + str(address)

Answer 2

问题是这一行：

+ full_name +'&a1=' + address

似乎您希望它是上一行的延续，但事实并非如此。