如何在熊猫数据框的单个列中的行上应用函数？

Question

我正在使用地址解析库，该库以以下方式接受字符串

import pyap
test_address = """
   4998 Stairstep Lane Toronto ON   
    """
addresses = pyap.parse(test_address, country='CA')
for address in addresses:
        # shows found address
        print(address)
        # shows address parts
        print(address.as_dict())

我想在单个熊猫数据框列的每一行上使用此功能。数据框包含两列（id，address），这是我到目前为止所拥有的

addresses.apply(lambda x: pyap.parse(x['address'], country='CA'),axis=1)

尽管运行，但会生成一个序列，而不是'pyap.address.Address'

Answer 1

您必须做您想做的事，但相反：假设您的数据框是这样的：

d = [{'id': '1', 'address': '4998 Stairstep Lane Toronto ON'}, {'id': '2', 'address': '1234 Stairwell Road Toronto ON'}] 
df = pd.DataFrame(d) 
df

    id  address
0   1   4998 Stairstep Lane Toronto ON
1   2   1234 Stairwell Road Toronto ON

将这些地址提取到列表中

address_list = df['address'].tolist()

然后使用pyapp处理每个：

for al in address_list:
   addresses = pyap.parse(al, country='CA')
   for address in addresses:
        print(address)
        print(address.as_dict())

让我知道它是否有效。