首先创建一个DataFrame

>>> import pandas as pd
>>> df= pd.DataFrame({
    'brand': ['Yum Yum', 'Yum Yum', 'Indomie', 'Indomie', 'Yum Yum'],
    'style': ['cup', 'cup', 'cup', 'pack', 'pack'],
    'rating': [4, 4, 3.5, 15, 5]
})
>>> df
     brand style  rating
0  Yum Yum   cup     4.0
1  Yum Yum   cup     4.0
2  Indomie   cup     3.5
3  Indomie  pack    15.0
4  Yum Yum  pack     5.0

来到赋值场景：

• 需求：需要对 rating 列的[0, 1, 4]行的3个元素赋值为[[5], [5], [4]]， 也就是同时使用位置索引（positional indexing）和标签索引（label-based indexing）
• 官方建议的操作为：

>>> import numpy as np
>>> df.loc[df.index[[0, 1, 4]], 'rating'] = np.array([5, 5, 4]).reshape((3, 1))
>>> df
     brand style  rating
0  Yum Yum   cup     5.0
1  Yum Yum   cup     5.0
2  Indomie   cup     3.5
3  Indomie  pack    15.0
4  Yum Yum  pack     4.0
>>> #或者
>>> df.iloc[[0, 1, 4], df.columns.get_loc('rating')] = np.array([5, 5, 4]).reshape((3, 1))
>>> df
     brand style  rating
0  Yum Yum   cup     5.0
1  Yum Yum   cup     5.0
2  Indomie   cup     3.5
3  Indomie  pack    15.0
4  Yum Yum  pack     4.0
>>>#或者
>>> df.iloc[df.index[[0, 1, 4]], df.columns.get_loc('rating')] = np.array([5, 5, 4]).reshape((3, 1))
>>> df
     brand style  rating
0  Yum Yum   cup     5.0
1  Yum Yum   cup     5.0
2  Indomie   cup     3.5
3  Indomie  pack    15.0
4  Yum Yum  pack     4.0
>>>#或者，使用.get_indexer（）可以同时索引多列如.get_indexer（['style', 'rating']）
>>> df.iloc[df.index[[0, 1, 4]], df.columns.get_indexer(['rating'])] = np.array([4, 4, 5]).reshape((3, 1))
>>> df
     brand style  rating
0  Yum Yum   cup     4.0
1  Yum Yum   cup     4.0
2  Indomie   cup     3.5
3  Indomie  pack    15.0
4  Yum Yum  pack     5.0