How to Find dtype of Array in NumPy

To find the data type of a NumPy array, use the dtype attribute of the array object. For example, array.dtype returns the type of elements stored in the array.

Syntax

The syntax to find the data type of a NumPy array is simple:

• array.dtype: Returns the data type of the elements in the array.

python

array.dtype

Example

This example shows how to create a NumPy array and find its data type using the dtype attribute.

python

import numpy as np

# Create a NumPy array of integers
arr = np.array([1, 2, 3, 4])

# Find and print the dtype of the array
print(arr.dtype)

Output

int64

Common Pitfalls

One common mistake is trying to call dtype() as a function instead of accessing it as an attribute. dtype is not a function, so do not use parentheses.

Wrong way:

arr.dtype()

This will cause an error.

Right way:

arr.dtype

python

import numpy as np

arr = np.array([1.5, 2.5, 3.5])

# Wrong: calling dtype as a function
# print(arr.dtype())  # This will raise TypeError

# Correct: access dtype attribute
print(arr.dtype)

Output

float64

Quick Reference

Summary tips to remember when checking dtype of a NumPy array:

• Use array.dtype without parentheses.
• The dtype tells you the type of data stored (e.g., int64, float64, bool).
• Useful for understanding how data is stored and for debugging.

Key Takeaways

Use the attribute array.dtype to find the data type of a NumPy array.

dtype is an attribute, not a function, so do not use parentheses.

The dtype shows the type of elements stored, such as integers or floats.

Knowing the dtype helps understand memory use and data operations.

Always check dtype when working with arrays to avoid type-related bugs.