- Data Structure
- Networking
- RDBMS
- Operating System
- Java
- MS Excel
- iOS
- HTML
- CSS
- Android
- Python
- C Programming
- C++
- C#
- MongoDB
- MySQL
- Javascript
- PHP
- Physics
- Chemistry
- Biology
- Mathematics
- English
- Economics
- Psychology
- Social Studies
- Fashion Studies
- Legal Studies
- Selected Reading
- UPSC IAS Exams Notes
- Developer's Best Practices
- Questions and Answers
- Effective Resume Writing
- HR Interview Questions
- Computer Glossary
- Who is Who
Python Pandas and Numpy - Concatenate multiindex into single index
To concatenate multiindex into single index, at first, let us import the required Pandas and Numpy libraries with their respective aliases −
import pandas as pd import numpy as np
Create Pandas series −
d = pd.Series([('Jacob', 'North'),('Ami', 'East'),('Ami', 'West'),('Scarlett', 'South'),('Jacob', 'West'),('Scarlett', 'North')])
Now, use the Numpy arrange() method −
dataFrame = pd.Series(np.arange(1, 7), index=d)
Let us now map and join −
dataMap = dataFrame.index.map('_'.join)
Example
Following is the code −
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
Output
This will produce the following output −
Result after mapping: Index([u'Jacob_North', u'Ami_East', u'Ami_West', u'Scarlett_South', u'Jacob_West', u'Scarlett_North'],dtype='object')
Advertisements