如何使用 dataframe/series 个值创建 URL 个字符串的列表？

Question

我有一系列值 IDs，我将其转换为数据帧 dfA，输出为：

	IDs
0	ID_3456789065
1	ID_4546567657
2	ID_1765768878

我正在尝试将 dfA['IDs'] 转换为 URL 的字符串列表，输出为：

'https://api.names.io/v1/ids/ID_3456789065/IDAccounts'
'https://api.names.io/v1/ids/ID_4546567657/IDAccounts'
'https://api.names.io/v1/ids/ID_1765768878/IDAccounts'

如果我手动输入 ID，这会得到我想要的：

acctID = 'ID_3456789065'
f'https://api.names.io/v1/ids/{acctID}/IDAccounts'

输出：

'https://api.names.io/v1/ids/ID_3456789065/IDAccounts'

当我尝试使用不同版本的 dfA 循环时，我总是得到错误的输出或错误：

urlList=[]

for i in dfA:
  acctID = dfA[i]
  urlList = f'https://api.names.io/v1/ids/{acctID}/IDAccounts'
  urlList.append(urlList)

输出：

https://api.names.io/v1/ids/0    ID_3456789065
1    ID_4546567657
2    ID_1765768878
Name: data_bettor, dtype: object/IDAccounts

我也尝试过 .concat 并抛出 TypeError: cannot concatenate object of type '<class 'str'>'; only Series and DataFrame objs are valid

请帮忙！

Answer 1

您可以使用遍历“ID”列的列表理解：

out = [f'https://api.names.io/v1/ids/{acctID}/IDAccounts' for acctID in df['IDs']]

输出：

['https://api.names.io/v1/ids/ID_3456789065/IDAccounts',
 'https://api.names.io/v1/ids/ID_4546567657/IDAccounts',
 'https://api.names.io/v1/ids/ID_1765768878/IDAccounts']

Answer 2

您可以使用：

urlList = list('https://api.names.io/v1/ids/' + df['IDs'] + '/IDAccounts')
print(urlList)

# Output
['https://api.names.io/v1/ids/ID_3456789065/IDAccounts',
 'https://api.names.io/v1/ids/ID_4546567657/IDAccounts',
 'https://api.names.io/v1/ids/ID_1765768878/IDAccounts']

Answer 3

您可以使用 apply() on the IDs column and use to_list 从系列中获取列表：

 df["IDs"].apply(lambda acctID: f'https://api.names.io/v1/ids/{acctID}/IDAccounts').to_list()

这输出：

['https://api.names.io/v1/ids/ID_3456789065/IDAccounts',
 'https://api.names.io/v1/ids/ID_4546567657/IDAccounts',
 'https://api.names.io/v1/ids/ID_1765768878/IDAccounts']

如何使用 dataframe/series 个值创建 URL 个字符串的列表？

How do I create list of URL strings using a dataframe/series of values?

python

url

list

dataframe

pandas