I've imported data as a DataFrame. It is being indexed by date range

Hello Barathi,

You can use pandas.dataframe.reset_index(). This function will convert your index to a column.

For example:

import pandas as pd
empoyees = [(11, 'jack', 34, 'Sydney', 70000) ,
(12, 'Riti', 31, 'Delhi' , 77000) ,
(13, 'Aadi', 16, 'Mumbai', 81000) ,
(14, 'Mohit', 31,'Delhi' , 90000) ,
(15, 'Veena', 12, 'Delhi' , 91000) ,
(16, 'Shaunak', 35, 'Mumbai', 75000 ),
(17, 'Shaun', 35, 'Colombo', 63000)
]
empDfObj = pd.DataFrame(empoyees, columns=['ID' , 'Name', 'Age', 'City', 'Salary'])
empDfObj.set_index('ID', inplace=True)
print(empDfObj)
modified = empDfObj.reset_index()
print(modified)

If you run the code, set_index will create the index and arrange the data according to the index, and reset_index() will remove the index and convert it into a column.

Hope you got your answer.

Thanks

1 Reply

Know the answer? Post it — somebody with the same question will find it here.

Rohit Gupta5y ago
Hello Barathi,

You can use pandas.dataframe.reset_index(). This function will convert your index to a column.

For example:
import pandas as pd

empoyees = [(11, 'jack', 34, 'Sydney', 70000) ,
          (12, 'Riti', 31, 'Delhi' , 77000) ,
          (13, 'Aadi', 16, 'Mumbai', 81000) ,
          (14, 'Mohit', 31,'Delhi' , 90000) ,
          (15, 'Veena', 12, 'Delhi' , 91000) ,
          (16, 'Shaunak', 35, 'Mumbai', 75000 ),
          (17, 'Shaun', 35, 'Colombo', 63000)
           ]

empDfObj = pd.DataFrame(empoyees, columns=['ID' , 'Name', 'Age', 'City', 'Salary'])

empDfObj.set_index('ID', inplace=True)
print(empDfObj)

modified = empDfObj.reset_index()
print(modified)
If you run the code, set_index will create the index and arrange the data according to the index, and reset_index() will remove the index and convert it into a column.
Hope you got your answer.

Thanks