NumPy: Take values from a source array and put them at specified indices of another array

NumPy: Array Object Exercise-100 with Solution

Use put to Place Values in Array

Write a NumPy program to take values from a source array and put them at specified indices of another array.

Sample Solution:

Python Code:

# Importing the NumPy library and aliasing it as 'np'
import numpy as np

# Creating a NumPy array 'x' containing floating-point values
x = np.array([10, 10, 20, 30, 30], float)

# Printing the original array 'x'
print(x)

# Printing a message indicating the modification of the array
print("Put 0 and 40 in first and fifth position of the above array")

# Creating a NumPy array 'y' containing floating-point values [0, 40, 60]
y = np.array([0, 40, 60], float)

# Using the 'put()' method to replace values in 'x' at positions 0 and 4 with values from array 'y'
x.put([0, 4], y)

# Printing a message indicating the display of the modified array 'x' after putting two values at specific positions
print("Array x, after putting two values:")
print(x)

Sample Output:

[ 10.  10.  20.  30.  30.]                                                             
Put 0 and 40 in first and fifth position of the above array                            
Array x after put two values:                                                          
[  0.  10.  20.  30.  40.]

Explanation:

In the above example –

‘x = np.array([10, 10, 20, 30, 30], float)’ creates a NumPy array 'x' with the elements 10, 10, 20, 30, and 30 of float data type.

‘y = np.array([0, 40, 60], float)’ creates a new NumPy array 'y' with the elements 0, 40, and 60 of float data type. Note that the 60 is not used in this example.

x.put([0, 4], y): Use the put function to replace the values at indices 0 and 4 in the 'x' array with the values from the 'y' array. The first and second values from 'y' (0 and 40) are used to replace the values at indices 0 and 4 in 'x', respectively.

Finally print() function prints the modified 'x' array. The output will be [0, 10, 20, 30, 40].

Pictorial Presentation:

Python-Numpy Code Editor:

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