python - 从 pandas 的 JSON 列中提取属于特定键的值

Question

例如，我有一个如下所示的数据框:

    name      eventlist
0   a         [{'t': '1234', 'n': 'user_engagem1'},{'t': '2345', 'n': 'user_engagem2'},{'t': '3456', 'n': 'user_engagem3'}]
1   b         [{'t': '2345', 'n': 'user_engagem4'},{'t': '1345', 'n': 'user_engagem5'},{'t': '1356', 'n': 'user_engagem6'},{'t': '1345', 'n': 'user_engagem5'},{'t': '1359', 'n': 'user_engagem6'}]
2   c         [{'t': '1334', 'n': 'user_engagem3'},{'t': '2345', 'n': 'user_engagem4'},{'t': '3556', 'n': 'user_engagem2'}]

我用一个字符串尝试了 re.findall，它似乎有效，我得到了这样的结果['1234', '2345', '3456'], 但我不能将它应用到数据框中

#code 1,apply to string successfully
str="[{'t': '1234', 'n': 'user_engagem'},{'t': '2345', 'n': 'user_engagem'},{'t': '3456', 'n': 'user_engagem'}]"
print(re.findall(r"t': '(.+?)', '", str))

#code 2,apply to dateframe doesn't work
df['t']=df['events'].str.findall(r"t': '(.+?)', '", df['events'])
print(list)

我想得到这样的结果

    name      eventlist

0   a         ['1234', '2345', '3456']
1   b         ['2345', '1345','1234','1356', '1356']
2   c         ['1334', '2345', '3556']

或者更好的是，我可以获得这样的结果

    name      t_first       t_last
0   a         1234           3456
1   b         2345           1359
2   c         1334           3556

Answer 1

df['eventlist'] = df['eventlist'].map(lambda x:[i['t'] for i in x])
df
     name                       eventlist
   0    a              [1234, 2345, 3456]
   1    b  [2345, 1345, 1356, 1345, 1359]
   2    c              [1334, 2345, 3556]

df['t_first'] = df['eventlist'][0]
df['t_last']=df['eventlist'].map(lambda x:x[len(x)-1])
df = df[['name','t_first','t_last']]
df
     name t_first t_last
   0    a    1234   3456
   1    b    2345   1359
   2    c    3456   3556