python Pandas : map and return Nan

Question

我有两个数据框，第一个是:

id code
1   2
2   3
3   3
4   1

第二个是:

id code  name
1    1   Mary
2    2   Ben
3    3   John

我想映射数据框 1，使其看起来像:

id code  name
1   2    Ben
2   3    John
3   3    John
4   1    Mary

我尝试使用这段代码:

mapping = dict(df2[['code','name']].values)
df1['name'] = df1['code'].map(mapping)

我的映射是正确的，但是映射值都是NAN:

mapping = {1:"Mary", 2:"Ben", 3:"John"}

id code  name
1   2    NaN
2   3    NaN
3   3    NaN
4   1    NaN

谁能知道为什么以及如何解决？

Answer 1

问题是 code 列中的值类型不同，因此需要通过 astype 转换为整数或字符串对于两者中的相同类型:

print (df1['code'].dtype)
object

print (df2['code'].dtype)
int64

print (type(df1.loc[0, 'code']))
<class 'str'>

print (type(df2.loc[0, 'code']))
<class 'numpy.int64'>

---

mapping = dict(df2[['code','name']].values)
#same dtypes - integers
df1['name'] = df1['code'].astype(int).map(mapping)

#same dtypes - object (obviously strings)
df2['code'] = df2['code'].astype(str)
mapping = dict(df2[['code','name']].values)
df1['name'] = df1['code'].map(mapping)

---

print (df1)
   id code  name
0   1    2   Ben
1   2    3  John
2   3    3  John
3   4    1  Mary