如何在 pandas 数据框的单个列中的行上应用函数？

Question

我正在使用一个地址解析库，它以下列方式接受字符串

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 pandas 数据帧的每一行上使用此函数 column.The 数据帧包含两列 (id,address) 这是我目前所拥有的

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

虽然这会运行，但它会产生一系列而不是 'pyap.address.Address'

Answer 1

你必须做你所做的，但反过来：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()

然后用 pyapp 处理每一个：

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

如果有效请告诉我。

如何在 pandas 数据框的单个列中的行上应用函数？

How to apply a function over rows within a single column of a pandas data frame?

python

parsing

dataframe

street-address

pandas