Python 大熊猫可以使用列作为索引吗？
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Could pandas use column as index?
提问by Chan Austin
I have a spreadsheet like this:
我有一个这样的电子表格：
Locality 2005 2006 2007 2008 2009
ABBOTSFORD 427000 448000 602500 600000 638500
ABERFELDIE 534000 600000 735000 710000 775000
AIREYS INLET459000 440000 430000 517500 512500
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:
我不想手动交换列与行。是否可以使用 Pandas 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]
回答by Michael Hoff
Yes, with set_indexyou can make Localityyour row index.
是的，使用set_index您可以制作Locality行索引。
data.set_index('Locality', inplace=True)
If inplace=Trueis not provided, set_indexreturns the modified dataframe as a result.
如果inplace=True未提供，则set_index返回修改后的数据帧作为结果。
Example:
例子：
> 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by famargar
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:
您可以使用已经说明的方式更改索引set_index。您不需要手动交换行与列，data.Tpandas 中有一个 transpose( ) 方法可以为您完成：
> 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:
然后您可以获取数据框列值并将它们转换为列表：
> newdf['ABBOTSFORD'].values.tolist()
[427000, 448000]
回答by Steffi Keran Rani J
You can set the column index using index_colparameter available while reading from spreadsheet in Pandas.
您可以在从 Pandas 中的电子表格读取时使用可用的index_col参数设置列索引。
Here is my solution:
这是我的解决方案：
Firstly, import pandas as pd:
import pandas as pdRead 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.For visual inspection, read the dataframe using
df.head()which will print the following output
Now you can fetch the values of the desired columns of the dataframe and print it
首先，导入pandas作为pd：
import pandas as pd使用pd.read_excel()读入文件名（如果您在电子表格中有数据）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，如果您收到“没有名为 xlrd 的模块”错误，请使用
pip install xlrd.对于目视检查，读取数据帧使用
df.head()它将打印以下输出现在您可以获取数据帧所需列的值并打印它
