How to get the powers of an array values element-wise in Python-Pandas?

Last Updated : 18 Aug, 2020

Let's see how to get the powers of an array values element-wise. Dataframe/Series.pow() is used to calculate the power of elements either with itself or with other Series provided. This function is applicable for real numbers only, and doesn't give results for complex numbers.
So let's see the programs:

Example 1: The uni-dimensional arrays are mapped to a pandas series with either default numeric indices or custom indexes Then corresponding elements are raised to its own power.

Python3

# import required modules
import numpy as np
import pandas as pd 

# create an array
sample_array = np.array([1, 2, 3])  

# uni dimensional arrays can be
# mapped to pandas series
sr = pd.Series(sample_array) 

print ("Original Array :")
print (sr)

# calculating element-wise power 
power_array = sr.pow(sr)

print ("Element-wise power array")
print (power_array)

Output:

Example 2: Powers can also be computed for floating-point decimal numbers.

Python3

# module to work with arrays in python
import array

# module required to compute power
import pandas as pd

# creating a 1-dimensional floating 
# point array containing three elements
sample_array = array.array('d', 
                           [1.1, 2.0, 3.5])  

# uni dimensional arrays can 
# be mapped to pandas series
sr = pd.Series(sample_array) 

print ("Original Array :")
print (sr)

# computing power of each 
# element with itself 
power_array = sr.pow(sr)

print ("Element-wise power array")
print (power_array)

Output:

Example 3: The Multi-dimensional arrays can be mapped to pandas data frames. The data frame then contains each cell comprising a numeric (integer or floating-point numbers) which can be raised to its own individual powers.

Python3

# module to work with 
# arrays in python
import array

# module required to 
# compute power
import pandas as pd

# 2-d matrix containing 
# 2 rows and 3 columns
df = pd.DataFrame({'X': [1,2],
                   'Y': [3,4],
                   'Z': [5,6]});

print ("Original Array :")
print(df)

# power function to calculate
# power of data frame elements
# with itself
power_array = df.pow(df)

print ("Element-wise power array")
print (power_array)