大 pandas 可以使用列作为索引吗? [英] Could pandas use column as index?

问题描述

我有一个像这样的电子表格:

I have a spreadsheet like this:

Locality    2005    2006    2007    2008    2009

ABBOTSFORD  427000  448000  602500  600000  638500
ABERFELDIE  534000  600000  735000  710000  775000
AIREYS INLET459000  440000  430000  517500  512500

我不想手动将列与行交换.可以这样使用熊猫将数据读取到列表中吗:

I don't want to manually swap the column with the row. Could it be possible to use pandas reading data to a list as this:

data['ABBOTSFORD']=[427000,448000,602500,600000,638500]
data['ABERFELDIE']=[534000,600000,735000,710000,775000]
data['AIREYS INLET']=[459000,440000,430000,517500,512500]

推荐答案

是，使用

Yes, with set_index you can make Locality your row index.

data.set_index('Locality', inplace=True)

如果未提供inplace=True，则set_index作为结果返回修改后的数据帧.

If inplace=True is not provided, set_index returns the modified dataframe as a result.

示例:

> import pandas as pd
> df = pd.DataFrame([['ABBOTSFORD', 427000, 448000],
                     ['ABERFELDIE', 534000, 600000]],
                    columns=['Locality', 2005, 2006])

> df
     Locality    2005    2006
0  ABBOTSFORD  427000  448000
1  ABERFELDIE  534000  600000

> df.set_index('Locality', inplace=True)
> df
              2005    2006
Locality                  
ABBOTSFORD  427000  448000
ABERFELDIE  534000  600000

> df.loc['ABBOTSFORD']
2005    427000
2006    448000
Name: ABBOTSFORD, dtype: int64

> df.loc['ABBOTSFORD'][2005]
427000

> df.loc['ABBOTSFORD'].values
array([427000, 448000])

> df.loc['ABBOTSFORD'].tolist()
[427000, 448000]

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