重新索引

reindex重置索引,如果索引值不存在，就引入缺失值

引數介紹

例項：

import pandas as pd
import numpy as np
from pandas import Series

obj = Series([4.5,7.2,-5.3,3.6],index=['d','b','a','c'])
obj

d    4.5
b    7.2
a   -5.3
c    3.6
dtype: float64


obj2 = obj.reindex(['a','b','c','d','e'])
obj2

a   -5.3
b    7.2
c    3.6
d    4.5
e    NaN
dtype: float64
 

既然有了缺失值，那麼怎麼填充，下面這方法

obj.reindex(['a','b','c','d','e'],fill_value=0)

a   -5.3
b    7.2
c    3.6
d    4.5
e    0.0
dtype: float64

對於DataFrame，reindex可以修改行索引，列索引或者都修改，預設重新索引行

frame = pd.DataFrame(np.arange(9).reshape(3,3),index=['b','c','a'])
frame.reindex(index=['a','b','c','d'],columns=[2,1,0])

    2   1   0
a   8.0 7.0 6.0
b   2.0 1.0 0.0
c   5.0 4.0 3.0
d   NaN NaN NaN
 

利用ix的標籤索引功能

frame.ix[['d','c','b','a'],[0,1,2]]

    0   1   2
d   NaN NaN NaN
c   3.0 4.0 5.0
b   0.0 1.0 2.0
a   6.0 7.0 8.0