Python pandas, How could I read excel file without column label and then insert column label?

Question

I have lists which I want to insert it as column labels. But when I use read_excel of pandas, they always consider 0th row as column label. How could I read the file as pandas dataframe and then put the list as column label

  orig_index = pd.read_excel(basic_info, sheetname = 'KI12E00')

    0.619159  0.264191  0.438849  0.465287  0.445819  0.412582  0.397366  \
0   0.601379  0.303953  0.457524  0.432335  0.415333  0.382093  0.382361   
1   0.579914  0.343715  0.418294  0.401129  0.385508  0.355392  0.355123  

Here is my personal list for column name

   print set_index
[20140109, 20140213, 20140313, 20140410, 20140508, 20140612]

And I want to make dataframe as below

    20140109  20140213  20140313  20140410  20140508  20140612
0   0.619159  0.264191  0.438849  0.465287  0.445819  0.412582  0.397366  \
1   0.601379  0.303953  0.457524  0.432335  0.415333  0.382093  0.382361   
2   0.579914  0.343715  0.418294  0.401129  0.385508  0.355392  0.355123

Answer 1

Pass header=None to tell it there isn't a header, and you can pass a list in names to tell it what you want to use at the same time. (Note that you're missing a column name in your example; I'm assuming that's accidental.)

For example:

>>> df = pd.read_excel("out.xlsx", header=None)
>>> df
          0         1         2         3         4         5         6
0  0.619159  0.264191  0.438849  0.465287  0.445819  0.412582  0.397366
1  0.601379  0.303953  0.457524  0.432335  0.415333  0.382093  0.382361
2  0.579914  0.343715  0.418294  0.401129  0.385508  0.355392  0.355123

or

>>> names = [20140109, 20140213, 20140313, 20140410, 20140508, 20140612, 20140714]
>>> df = pd.read_excel("out.xlsx", header=None, names=names)
>>> df
   20140109  20140213  20140313  20140410  20140508  20140612  20140714
0  0.619159  0.264191  0.438849  0.465287  0.445819  0.412582  0.397366
1  0.601379  0.303953  0.457524  0.432335  0.415333  0.382093  0.382361
2  0.579914  0.343715  0.418294  0.401129  0.385508  0.355392  0.355123

And you can always set the column names after the fact by assigning to df.columns.