1.set_index
DataFrame can be set by the set_index method, which allows you to set both a single index and a composite index.
dataframe.set_index (keys, drop=True, append=False, inplace=False, verify_integrity=False)
append add a new index, drop is False, inplace is True, the index will be restored to the column
DataFrame can be set by the set_index method, which allows you to set both a single index and a composite index.
dataframe.set_index (keys, drop=True, append=False, inplace=False, verify_integrity=False)
append add a new index, drop is False, inplace is True, the index will be restored to the column
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
dataframe.reset_index (level=None, drop=False, inplace=False, col_level=0, col_fill= “)
level controls the index of the specific level to be restored
drop to False, the index column will be restored to the normal column, otherwise it will be lost
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