大熊猫可以使用列作为索引吗?

问题:大熊猫可以使用列作为索引吗?

我有一个像这样的电子表格:

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。是否可以使用熊猫将数据读取到列表中,如下所示:

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

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

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]

回答 0

是的,使用set_index可以创建Locality行索引。

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

如果inplace=True未提供,则set_index返回修改后的数据帧。

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]

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

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

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

Example:

> 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]

回答 1

您可以使用进行更改,如已经说明的那样set_index。您无需手动将行与列交换data.T,pandas中有一个transpose()方法可以为您完成此操作:

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

> newdf = df.set_index('Locality').T
> newdf

Locality    ABBOTSFORD  ABERFELDIE
2005        427000      534000
2006        448000      600000

然后您可以获取数据框列值并将其转换为列表:

> newdf['ABBOTSFORD'].values.tolist()

[427000, 448000]

You can change the index as explained already using set_index. You don’t need to manually swap rows with columns, there is a transpose (data.T) method in pandas that does it for you:

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

> newdf = df.set_index('Locality').T
> newdf

Locality    ABBOTSFORD  ABERFELDIE
2005        427000      534000
2006        448000      600000

then you can fetch the dataframe column values and transform them to a list:

> newdf['ABBOTSFORD'].values.tolist()

[427000, 448000]

回答 2

您可以在从Pandas中的电子表格读取数据时使用可用的index_col参数设置列索引。

这是我的解决方案:

  1. 首先,将熊猫作为pd导入: import pandas as pd

  2. 使用pd.read_excel()读入文件名(如果电子表格中有数据),并通过指定index_col参数将索引设置为“ Locality”。

    df = pd.read_excel('testexcel.xlsx', index_col=0)

    在此阶段,如果出现“没有名为xlrd的模块”错误,请使用进行安装pip install xlrd

  3. 为了进行视觉检查,请读取数据框,使用df.head()该数据框将打印以下输出

  4. 现在,您可以获取数据框所需列的值并进行打印

You can set the column index using index_col parameter available while reading from spreadsheet in Pandas.

Here is my solution:

  1. Firstly, import pandas as pd: import pandas as pd

  2. Read in filename using pd.read_excel() (if you have your data in a spreadsheet) and set the index to ‘Locality’ by specifying the index_col parameter.

    df = pd.read_excel('testexcel.xlsx', index_col=0)

    At this stage if you get a ‘no module named xlrd’ error, install it using pip install xlrd.

  3. For visual inspection, read the dataframe using df.head() which will print the following output

  4. Now you can fetch the values of the desired columns of the dataframe and print it