python中set index_python 中的Set_index 与reset_index
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 3.0set
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
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
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 3.0set 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 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