NumPy: Array converted to a float type

Last update on April 26 2025 12:39:22 (UTC/GMT +8 hours)

Convert Array to Float Type

Write a NumPy program to convert an array to a floating type.

Python NumPy: Array converted to a float type

Sample Solution:

Python Code:

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

# Defining a Python list 'a' containing integers
a = [1, 2, 3, 4]

# Printing the original array 'a'
print("Original array")
print(a)

# Converting the array 'a' to a NumPy array of type float using asfarray()
x = np.asfarray(a)

# Printing the array 'x' after converting to a float type
print("Array converted to a float type:")
print(x)

Sample Output:

Original array                                                          
[1, 2, 3, 4]                                                            
Array converted to a float type:                                        
[ 1.  2.  3.  4.]

Explanation:

In the above code -

a = [1, 2, 3, 4]: Defines a list a containing the integers 1, 2, 3, and 4.

x = np.asfarray(a): The np.asfarray() function converts the given list ‘a’ into a one-dimensional NumPy array with a floating-point data type (by default, it uses float64). In this case, the list ‘a’ contains integers, so they will be converted to floating-point numbers in the resulting NumPy array ‘x’.

For more Practice: Solve these Related Problems:

Convert an integer array to a floating-point array and perform division to showcase float behavior.
Change the data type of an array using astype and verify the conversion through arithmetic operations.
Transform a mixed-type numeric list into a float array and check that all elements are decimals.
Implement a conversion function that takes an array and a target dtype, then confirm the new type with type().

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