Python 通过将另一列与字典匹配来更改dataframe的列

我有一个情况：

postStr = """{
                     "zoneId":"0",
                     "id":["a","b","c","d","f","g"],
                     "currencycode":["USD"],

                }"""


postData = json.loads(postStr, object_pairs_hook=OrderedDict)

我有一个数据帧：

df = {
'id':['a','b','c','d','f','g','h','i','j','k'],
'B':['c','d','e','d','d','c','s','e','s','q'],
'S':['f','g','h','j','e','j','t','r','p','p']
}
df1 = pd.DataFrame(df)

现在我想要一个数据frme，如果id在字典中，那么对应的B列变成XX

输出：

    df = {
'id':['a','b','c','d','f','g','h','i','j','k'],
'B' :['XX','XX','XX','XX','XX','c','s','e','s','q'],
'S' :['f','g','h','j','e','j','t','r','p','p']
}
df1 = pd.DataFrame(df)

请帮助

我认为需要：

如果需要更动态的解决方案-用于DataFrame和dictionary中的列名称，并在循环中设置值：

postStr = """{
                     "S":["f","h"],
                     "id":["a","b","c","d","f","g"],
                     "currencycode":["USD"]

                }"""

postData = json.loads(postStr, object_pairs_hook=OrderedDict)
print (postData)
OrderedDict([('S', ['f', 'h']), 
             ('id', ['a', 'b', 'c', 'd', 'f', 'g']), 
             ('currencycode', ['USD'])])

df = {
'id':['a','b','c','d','f','g','h','i','j','k'],
'B':['c','d','e','d','d','c','s','e','s','q'],
'S':['f','g','h','j','e','j','t','r','p','p']
}
df1 = pd.DataFrame(df)

for col in df1.columns.intersection(postData.keys()):
    df1.loc[df1[col].isin(postData[col]), col] = 'XX'
print (df1)
   id  B   S
0  XX  c  XX
1  XX  d   g
2  XX  e  XX
3  XX  d   j
4  XX  d   e
5  XX  c   j
6   h  s   t
7   i  e   r
8   j  s   p
9   k  q   p

---

我这样做了，但得到了：TypeError:string索引必须是整数self.resp_df.loc[self.resp_df['id'].isin（post_req['id']），'returnType']='CTR'@ayushgupta-如何工作转换到类似于

self.resp_df.loc[self.resp_df['id']）.isin（list（post_req['id']），'returnType'='CTR

？self.resp_df.loc[id']，'returnType']='CTR'类型错误：字符串索引必须为integers@ayushgupta-什么是打印（类型（postData['id']）？

postStr = """{
                     "S":["f","h"],
                     "id":["a","b","c","d","f","g"],
                     "currencycode":["USD"]

                }"""

postData = json.loads(postStr, object_pairs_hook=OrderedDict)
print (postData)
OrderedDict([('S', ['f', 'h']), 
             ('id', ['a', 'b', 'c', 'd', 'f', 'g']), 
             ('currencycode', ['USD'])])

df = {
'id':['a','b','c','d','f','g','h','i','j','k'],
'B':['c','d','e','d','d','c','s','e','s','q'],
'S':['f','g','h','j','e','j','t','r','p','p']
}
df1 = pd.DataFrame(df)

for col in df1.columns.intersection(postData.keys()):
    df1.loc[df1[col].isin(postData[col]), col] = 'XX'
print (df1)
   id  B   S
0  XX  c  XX
1  XX  d   g
2  XX  e  XX
3  XX  d   j
4  XX  d   e
5  XX  c   j
6   h  s   t
7   i  e   r
8   j  s   p
9   k  q   p