Python pandas，如何读取没有列标签的excel文件然后插入列标签？
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Python pandas, How could I read excel file without column label and then insert column label?
提问by JonghoKim
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
我有我想将其作为列标签插入的列表。但是当我使用熊猫的 read_excel 时，他们总是将第 0 行视为列标签。我怎么能把文件读作熊猫数据框，然后把列表作为列标签
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
这是我个人的列名列表
print set_index
[20140109, 20140213, 20140313, 20140410, 20140508, 20140612]
And I want to make dataframe as below
我想制作如下数据框
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
回答by DSM
Pass header=Noneto tell it there isn't a header, and you can pass a list in namesto 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.)
传递header=None告诉它没有标题，您可以同时传递一个列表names来告诉它您要使用的内容。（请注意，您的示例中缺少列名；我假设这是偶然的。）
For example:
例如：
>>> 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
或者
>>> 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.
并且您始终可以通过分配给df.columns.
