How to fix AttributeError: module numpy has no attribute float’ in Python

While working with the Python NumPy module, you might encounter the error “module ‘numpy’ has no attribute ‘float'”. This error arises because numpy’s float attribute has been deprecated and removed in favor of using standard Python types. In this article, we will learn how to fix “AttributeError: module ‘numpy’ has no attribute ‘float'”.

What is AttributeError: module ‘numpy’ has no attribute ‘float’?

The “AttributeError: module ‘numpy’ has no attribute ‘float‘” means that the codebase is unable to find the ‘float’ datatype in the NumPy module. It occurs because recent versions of numpy have deprecated and removed the float attribute. This means, using numpy.float in your code will lead to an error, as it no longer exists in the numpy module.

Syntax:

Attributeerror: module 'numpy' has no attribute 'float'

Why does AttributeError: module ‘numpy’ has no attribute ‘float’ Occur in Python?

Common reasons why AttributeError: module ‘numpy’ has no attribute ‘float’ errors occur in Python are:

Deprecation of np.float

Numpy deprecated np.float in version 1.20 and removed it entirely in version 1.24. This deprecation means that the alias is no longer available, and using it will result in an AttributeError.

Python
import numpy as np

# Deprecated usage causing the error
x = np.float(3.14)
print(x)

Output:

Deprecation of numpy.float

Use of Outdated Code

The error “Outdated usage causing the error” typically arises when using outdated code or deprecated features. In the given code snippet, using dtype=np.float is outdated because recent versions of numpy no longer support this syntax.

Python
import numpy as np

# Outdated usage causing the error
x = np.array([1, 2, 3], dtype=np.float)
print(x)

Output:

Fix AttributeError: module ‘numpy’ has no attribute ‘float’

Below are some of the ways by which we can fix AttributeError: module ‘numpy’ has no attribute ‘float’ in Python:

Directly Use Python Built-in Types

Using the built-in Python types directly means replacing the outdated numpy attribute (np.float) with the standard Python type (float). This solution ensures compatibility with recent numpy versions and avoids the “AttributeError: module ‘numpy’ has no attribute ‘float'” error.

Python
import numpy as np

# numpy inbuilt float datatype
x = np.array([1, 2, 3], dtype=float)
print(x)

Output:

[1. 2. 3.]

Explicitly Specify Python Types

Explicitly specifying Python types involves using dtype=’float64′ or dtype=’float32′ in numpy arrays instead of relying on the deprecated np.float attribute.

Python
import numpy as np

# explicitily specifying float datatype
x = np.array([1, 2, 3], dtype='float64')
print(x)

Output:

[1. 2. 3.]



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