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Reset Index in Pandas Dataframe
  • Last Updated : 04 Dec, 2018

Let’s discuss how to reset index in Pandas DataFrame. Often We start with a huge dataframe in Pandas and after manipulating/filtering the dataframe, we end up with much smaller dataframe.

When we look at the smaller dataframe, it might still carry the row index of the original dataframe. If the original index are numbers, now we have indexes that are not continuous. Well, pandas has reset_index() function. So to reset the index to the default integer index beginning at 0, We can simply use the reset_index() function.

So let’s see the different ways we can reset the index of a DataFrame.

First see original DataFrame.




# Import pandas package
import pandas as pd
    
# Define a dictionary containing employee data
data = {'Name':['Jai', 'Princi', 'Gaurav', 'Anuj', 'Geeku'],
        'Age':[27, 24, 22, 32, 15],
        'Address':['Delhi', 'Kanpur', 'Allahabad', 'Kannauj', 'Noida'],
        'Qualification':['Msc', 'MA', 'MCA', 'Phd', '10th'] }
  
# Convert the dictionary into DataFrame 
df = pd.DataFrame(data)
  
df

Output:



 
Example #1: Make Own Index Without Removing Default index.




# Import pandas package
import pandas as pd
    
# Define a dictionary containing employee data
data = {'Name':['Jai', 'Princi', 'Gaurav', 'Anuj', 'Geeku'],
        'Age':[27, 24, 22, 32, 15],
        'Address':['Delhi', 'Kanpur', 'Allahabad', 'Kannauj', 'Noida'],
        'Qualification':['Msc', 'MA', 'MCA', 'Phd', '10th'] }
  
index = {'a', 'b', 'c', 'd', 'e'}
  
# Convert the dictionary into DataFrame 
df = pd.DataFrame(data, index)
  
# Make Own Index as index
# In this case default index is exist 
df.reset_index(inplace = True)
  
df

Output:

 
Example #2: Make Own Index and Removing Default index.




# Import pandas package
import pandas as pd
    
# Define a dictionary containing employee data
data = {'Name':['Jai', 'Princi', 'Gaurav', 'Anuj', 'Geeku'],
        'Age':[27, 24, 22, 32, 15],
        'Address':['Delhi', 'Kanpur', 'Allahabad', 'Kannauj', 'Noida'],
        'Qualification':['Msc', 'MA', 'MCA', 'Phd', '10th'] }
  
# Create own index
index = {'a', 'b', 'c', 'd', 'e'}
  
# Convert the dictionary into DataFrame 
# Make Own Index and Removing Default index
df = pd.DataFrame(data, index)
  
df

Output:

 
Example 3: Reset own index and make default index as index.




# Import pandas package
import pandas as pd
    
# Define a dictionary containing employee data
data = {'Name':['Jai', 'Princi', 'Gaurav', 'Anuj', 'Geeku'],
        'Age':[27, 24, 22, 32, 15],
        'Address':['Delhi', 'Kanpur', 'Allahabad', 'Kannauj', 'Noida'],
        'Qualification':['Msc', 'MA', 'MCA', 'Phd', '10th'] }
  
# Create own index
index = {'a', 'b', 'c', 'd', 'e'}
  
# Convert the dictionary into DataFrame 
df = pd.DataFrame(data, index)
  
# remove own index with default index
df.reset_index(inplace = True, drop = True)
  
df

Output:

 
Example #4: Make a column of dataframe as index with remove default index.




# Import pandas package
import pandas as pd
    
# Define a dictionary containing employee data
data = {'Name':['Jai', 'Princi', 'Gaurav', 'Anuj', 'Geeku'],
        'Age':[27, 24, 22, 32, 15],
        'Address':['Delhi', 'Kanpur', 'Allahabad', 'Kannauj', 'Noida'],
        'Qualification':['Msc', 'MA', 'MCA', 'Phd', '10th'] }
  
# Create own index
index = {'a', 'b', 'c', 'd', 'e'}
  
# Convert the dictionary into DataFrame 
df = pd.DataFrame(data, index)
  
# set index any column of our DF and
# remove default index
df.set_index(['Age'], inplace = True)
  
df

Output:

 
Example 5: Make a column of dataframe as index without remove default index.




# Import pandas package
import pandas as pd
    
# Define a dictionary containing employee data
data = {'Name':['Jai', 'Princi', 'Gaurav', 'Anuj', 'Geeku'],
        'Age':[27, 24, 22, 32, 15],
        'Address':['Delhi', 'Kanpur', 'Allahabad', 'Kannauj', 'Noida'],
        'Qualification':['Msc', 'MA', 'MCA', 'Phd', '10th'] }
  
# Create own index
index = {'a', 'b', 'c', 'd', 'e'}
  
# Convert the dictionary into DataFrame 
df = pd.DataFrame(data, index)
  
# set any column as index
# Here we set age column as index
df.set_index(['Age'], inplace = True)
  
# reset index without removing default index
df.reset_index(level =['Age'], inplace = True)
  
df

Output:

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