How to Change dtype of Array in NumPy Quickly

To change the data type of a NumPy array, use the astype() method with the desired type as an argument, like array.astype(new_dtype). This creates a new array with the changed dtype without modifying the original array.

Syntax

The basic syntax to change the dtype of a NumPy array is:

• new_array = original_array.astype(new_dtype)

Here, original_array is your existing NumPy array, and new_dtype is the target data type you want, such as int, float, or str.

This method returns a new array with the specified dtype and does not change the original array.

python

new_array = original_array.astype(new_dtype)

Example

This example shows how to convert a NumPy array of floats to integers using astype(). It also prints both arrays to show the difference.

python

import numpy as np

original_array = np.array([1.5, 2.3, 3.7, 4.0])
print("Original array:", original_array)
print("Original dtype:", original_array.dtype)

new_array = original_array.astype(int)
print("New array:", new_array)
print("New dtype:", new_array.dtype)

Output

Original array: [1.5 2.3 3.7 4. ]
Original dtype: float64
New array: [1 2 3 4]
New dtype: int64

Common Pitfalls

One common mistake is trying to change the dtype by assigning directly to the dtype attribute, which does not work and raises an error.

Also, converting from float to int truncates the decimal part without rounding.

python

import numpy as np

arr = np.array([1.9, 2.7, 3.1])

# Wrong way - raises AttributeError
try:
    arr.dtype = int
except AttributeError as e:
    print("Error:", e)

# Right way
arr_int = arr.astype(int)
print("Converted array:", arr_int)

Output

Error: 'numpy.ndarray' object attribute 'dtype' is not writable
Converted array: [1 2 3]

Quick Reference

Summary tips for changing dtype in NumPy:

• Use astype() to convert array dtype safely.
• The method returns a new array; original stays unchanged.
• Specify dtype as a type (e.g., int, float) or string (e.g., 'int32').
• Be careful with conversions that lose data (like float to int).

Key Takeaways

Use the astype() method to change a NumPy array's dtype safely.

astype() returns a new array and does not modify the original array.

Directly assigning to the dtype attribute is not allowed and causes errors.

Converting from float to int truncates decimals without rounding.

Specify the target dtype clearly as a type or string in astype().