pandas set_index和reset_index的用法

1.set_index

DataFrame可以通过set_index方法,可以设置单索引和复合索引。 
DataFrame.set_index(keys, drop=True, append=False, inplace=False, verify_integrity=False) 
append添加新索引,drop为False,inplace为True时,索引将会还原为列

In [307]: data
Out[307]: 
     a    b  c    d
0  bar  one  z  1.0
1  bar  two  y  2.0
2  foo  one  x  3.0
3  foo  two  w  4.0
 
In [308]: indexed1 = data.set_index('c')
 
In [309]: indexed1
Out[309]: 
     a    b    d
c               
z  bar  one  1.0
y  bar  two  2.0
x  foo  one  3.0
w  foo  two  4.0
 
In [310]: indexed2 = data.set_index(['a', 'b'])
 
In [311]: indexed2
Out[311]: 
         c    d
a   b          
bar one  z  1.0
    two  y  2.0
foo one  x  3.0
    two  w  4.0

  

2.reset_index

reset_index可以还原索引,从新变为默认的整型索引 
DataFrame.reset_index(level=None, drop=False, inplace=False, col_level=0, col_fill=”) 
level控制了具体要还原的那个等级的索引 
drop为False则索引列会被还原为普通列,否则会丢失

In [318]: data
Out[318]: 
         c    d
a   b          
bar one  z  1.0
    two  y  2.0
foo one  x  3.0
    two  w  4.0
 
In [319]: data.reset_index()
Out[319]: 
     a    b  c    d
0  bar  one  z  1.0
1  bar  two  y  2.0
2  foo  one  x  3.0
3  foo  two  w  4.0

 

转自:https://blog.csdn.net/jingyi130705008/article/details/78162758

posted @ 2018-09-24 10:51  静悟生慧  阅读(15840)  评论(0编辑  收藏  举报