将Python Pandas和Numpy – 拼接多级索引为单个索引

首先，让我们使用它们的别名导入所需的Pandas和Numpy库，将多个索引连接到单个索引中－

import pandas as pd
import numpy as np

创建Pandas系列－

d = pd.Series([('Jacob', 'North'),('Ami', 'East'),('Ami', 'West'),('Scarlett', 'South'),('Jacob', 'West'),('Scarlett', 'North')])

现在，使用Numpy arrange()方法－

dataFrame = pd.Series(np.arange(1, 7), index=d)

现在，映射并连接－

dataMap = dataFrame.index.map('_'.join)

示例

以下是代码－

import pandas as pd
import numpy as np

# pandas series
d = pd.Series([('Jacob', 'North'),('Ami', 'East'),('Ami', 'West'),('Scarlett', 'South'),('Jacob', 'West'),('Scarlett', 'North')])

dataFrame = pd.Series(np.arange(1, 7), index=d)

# mapping and joining
dataMap = dataFrame.index.map('_'.join)

print"\nResult after mapping:\n",dataMap

输出

这将产生以下输出－

Result after mapping:
Index([u'Jacob_North', u'Ami_East', u'Ami_West', u'Scarlett_South', u'Jacob_West', u'Scarlett_North'],dtype='object')