# import pandas  module for data frame
import pandas as pd
  
# Create dataframe for student data in different colleges
subjectsdata = {'Name': ['sravan', 'sravan', 'sravan', 'sravan', 
                         'sravan', 'sravan', 'sravan', 'sravan', 
                         'Ojaswi', 'Ojaswi', 'Ojaswi', 'Ojaswi', 
                         'Ojaswi', 'Ojaswi', 'Ojaswi', 'Ojaswi',
                         'Rohith', 'Rohith', 'Rohith', 'Rohith',
                         'Rohith', 'Rohith', 'Rohith', 'Rohith'],
                  
                'college': ['VFSTRU', 'VFSTRU', 'VFSTRU', 'VFSTRU',
                            'VFSTRU', 'VFSTRU', 'VFSTRU', 'VFSTRU',
                            'VIT', 'VIT', 'VIT', 'VIT', 'VIT', 'VIT',
                            'VIT', 'VIT', 'IIT-Bhu', 'IIT-Bhu', 'IIT-Bhu', 
                            'IIT-Bhu', 'IIT-Bhu', 'IIT-Bhu', 'IIT-Bhu',
                            'IIT-Bhu'],
                  
                'subject': ['java', 'dbms', 'dms', 'coa', 'python', 'dld',
                            'android', 'iot', 'java', 'dbms', 'dms', 'coa',
                            'python', 'dld', 'android', 'iot', 'java',
                            'dbms', 'dms', 'coa', 'python', 'dld', 'android',
                            'iot']
                }
  
# Convert into data frame
df = pd.DataFrame(subjectsdata)
  
# print the data(student records)
print(df)

# Set the hierarchical index
df = df.set_index(['Name', 'college'], drop=False)
  
# print data frame
df

# setting index
df = df.set_index(['Name', 'college'])
  
# print data frame
df

# Swap the levels in the index
df.swaplevel('Name', 'college')

# Summarize the results by college
df.sum(level='college')