Python 熊猫：映射并返回 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

我尝试使用此代码：

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

谁能知道为什么要解决？

Answer 1

问题是列中的值类型不同，code因此有必要将astype两者中的相同类型转换为整数或字符串：print (df1['code'].dtype)objectprint (df2['code'].dtype)int64print (type(df1.loc[0, 'code']))<class 'str'>print (type(df2.loc[0, 'code']))<class 'numpy.int64'>mapping = dict(df2[['code','name']].values)#same dtypes - integersdf1['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)&nbsp; &nbsp;id code&nbsp; name0&nbsp; &nbsp;1&nbsp; &nbsp; 2&nbsp; &nbsp;Ben1&nbsp; &nbsp;2&nbsp; &nbsp; 3&nbsp; John2&nbsp; &nbsp;3&nbsp; &nbsp; 3&nbsp; John3&nbsp; &nbsp;4&nbsp; &nbsp; 1&nbsp; Mary

Answer 2

另一种方法是使用 dataframe.mergedf.merge(df2.drop(['id'],1), how='left', on=['code'])输出：&nbsp; &nbsp; id&nbsp; code&nbsp; &nbsp;name0&nbsp; &nbsp;1&nbsp; &nbsp;2&nbsp; &nbsp; &nbsp; Ben1&nbsp; &nbsp;2&nbsp; &nbsp;3&nbsp; &nbsp; &nbsp; John2&nbsp; &nbsp;3&nbsp; &nbsp;3&nbsp; &nbsp; &nbsp; John3&nbsp; &nbsp;4&nbsp; &nbsp;1&nbsp; &nbsp; &nbsp; Mery