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Find Exponential of a column in Pandas-Python

Last Updated : 02 Jul, 2021
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Let's see how to find Exponential of a column in Pandas Dataframe. First, let's create a Dataframe:

Python3
# importing pandas and 
# numpy libraries
import pandas as pd
import numpy as np
 
# creating and initializing a list
values= [ ['Rohan', 5, 50.59], ['Elvish', 2, 90.57],
         ['Deepak', 10, 98.51], ['Soni', 4, 40.24], 
         ['Radhika', 1, 99.05], ['Vansh', 15, 85.56] ] 

# creating a pandas dataframe
df = pd.DataFrame(values, columns = ['Name', 
                                     'University_Rank', 
                                     'University_Marks'])

# displaying the data frame
df

  

Output:


 

Dataframe


 

 The exponential of any column is found out by using numpy.exp() function. This function calculates the exponential of the input array/Series.


 

Syntax: numpy.exp(array, out = None, where = True, casting = ‘same_kind’, order = ‘K’, dtype = None) 
 

Return: An array with exponential of all elements of input array/Series. 
 


 

Example 1: Finding exponential of the single column (integer values).


 

Python3
# importing pandas and 
# numpy libraries
import pandas as pd
import numpy as np
 
# creating and initializing a list
values= [ ['Rohan', 5, 50.59], ['Elvish', 2, 90.57],
         ['Deepak', 10, 98.51], ['Soni', 4, 40.24], 
         ['Radhika', 1, 99.05], ['Vansh', 15, 85.56] ] 

# creating a pandas dataframe
df = pd.DataFrame(values, columns = ['Name', 
                                     'University_Rank', 
                                     'University_Marks'])

# finding the exponential value 
# of column using np.exp() function
df['exp_value'] = np.exp(df['University_Rank'])

# displaying the data frame
df

  

Output:


 

exponential value of University_Rank is calculated


 

Example 2: Finding exponential of the single column (Float values).


 

Python3
# importing pandas and 
# numpy libraries
import pandas as pd
import numpy as np
 
# creating and initializing a list
values= [ ['Rohan', 5, 50.59], ['Elvish', 2, 90.57],
         ['Deepak', 10, 98.51], ['Soni', 4, 40.24], 
         ['Radhika', 1, 99.05], ['Vansh', 15, 85.56] ] 

# creating a pandas dataframe
df = pd.DataFrame(values, columns = ['Name', 
                                     'University_Rank', 
                                     'University_Marks'])

# finding the exponential value 
# of column  using np.exp() function
df['exp_value'] = np.exp(df['University_Marks'])

# displaying the data frame
df

  

Output:


 

exponential value of University_Marks is calculated


 


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