Pandas中set_index和reset_index的用法及区别

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，重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