NumPy: Change the data type of an array

NumPy: Array Object Exercise-39 with Solution

Change Array Data Type

Write a NumPy program to change an array's data type.

Sample Solution:

Python Code:

# Importing the NumPy library with an alias 'np'
import numpy as np

# Creating a NumPy array 'x' with specified data type 'int32'
x = np.array([[2, 4, 6], [6, 8, 10]], np.int32)

# Printing the array 'x'
print(x)

# Printing the data type of array 'x'
print("Data type of the array x is:", x.dtype)

# Changing the data type of array 'x' to 'float'
y = x.astype(float)

# Printing the new data type of array 'y'
print("New Type: ", y.dtype)

# Printing the modified array 'y' with the new data type
print(y)

Sample Output:

[[ 2  4  6]                                                            
 [ 6  8 10]]                                                           
Data type of the array x is: int32                                     
New Type:  float64                                                     
[[  2.   4.   6.]                                                      
 [  6.   8.  10.]]

Explanation:

In the above exercise -

x = np.array([[2, 4, 6], [6, 8, 10]], np.int32): The current line creates a two-dimensional NumPy array ‘x’ with the specified elements and data type np.int32.

print("Data type of the array x is:",x.dtype): The current line prints the data type of the ‘x’ array, which is int32.

y = x.astype(float): The current line creates a new array ‘y’ by changing the data type of ‘x’ to float. The astype() function is used for this purpose.

print("New Type: ",y.dtype): The current line prints the data type of the new ‘y’ array, which is float64 (the default float data type).

print(y): The current line prints the ‘y’ array with the same elements as ‘x’ but with the new data type float64.

Python-Numpy Code Editor:

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