Python NumPy: How to Fix "TypeError: type numpy.ndarray doesn't define __round__ method"

When working with floating-point numbers in Python, the built-in round() function is commonly used for rounding to a specified number of decimal places or to the nearest integer. However, if you attempt to pass a NumPy ndarray directly to Python's round() function, you'll encounter a TypeError: type numpy.ndarray doesn't define __round__ method. This error arises because standard Python functions like round() are not designed to operate element-wise on entire NumPy arrays; NumPy provides its own optimized functions for such array operations.

This guide will clearly explain why this TypeError occurs, demonstrate how to reproduce it, and provide the primary solution: using NumPy's own numpy.round() (or its alias numpy.around()) function, which is specifically designed to perform element-wise rounding on NumPy arrays. We'll also cover rounding to specific decimal places and briefly touch upon numpy.ceil() and numpy.floor() for ceiling and floor rounding respectively.

Understanding the Error: Python's round() vs. NumPy Arrays

• Python's round(number, ndigits=None): This built-in function is designed to round a single number (an int or float) to ndigits precision after the decimal point. If ndigits is omitted or None, it rounds to the nearest integer. It operates on scalar numeric types and expects the object passed to it to have a __round__ special method if it's a custom type.
• NumPy ndarray: A NumPy array is a collection of elements, typically numbers. It does not, by itself, implement the __round__ method that Python's round() function looks for.

The TypeError: type numpy.ndarray doesn't define __round__ method occurs because you're passing a whole NumPy array object to a function (round()) that expects a single number and tries to call a __round__ method which ndarray objects don't have. NumPy uses its own set of universal functions (ufuncs) for element-wise operations like rounding.

Reproducing the Error: Using Python's round() on a NumPy Array

import numpy as np

float_array = np.array([10.23, 25.88, 5.49, 12.50, 7.77])
print(f"Original NumPy array: {float_array}")

try:
    # ⛔️ Incorrect: Passing a NumPy array to Python's built-in round()
    rounded_values_error = round(float_array)
    print(rounded_values_error)
except TypeError as e:
    print(f"Error: {e}")

Output:

Original NumPy array: [10.23 25.88  5.49 12.5   7.77]
Error: type numpy.ndarray doesn't define __round__ method

Solution: Using numpy.round() (or numpy.around())

NumPy provides its own numpy.round(a, decimals=0, out=None) function (aliased as numpy.around()) that is designed to round the elements of an array a to the specified number of decimals.

Basic Rounding to Nearest Integer

If decimals is 0 (the default), np.round() rounds each element to the nearest integer. For values exactly halfway between rounded decimal values, NumPy rounds to the nearest even value (e.g., 2.5 rounds to 2.0, 3.5 rounds to 4.0).

import numpy as np

float_array = np.array([10.23, 25.88, 5.49, 12.50, 7.77])

# ✅ Correct: Use numpy.round() for element-wise rounding
rounded_array_np = np.round(float_array) # decimals defaults to 0
print(f"Array rounded to nearest integer using np.round(): {rounded_array_np}")

# Using the alias np.around()
rounded_array_around = np.around(float_array)
print(f"Array rounded using np.around(): {rounded_array_around}")

Output:

Array rounded to nearest integer using np.round(): [10. 26.  5. 12.  8.]
Array rounded using np.around(): [10. 26.  5. 12.  8.]

Rounding to a Specific Number of Decimal Places

Provide an integer value for the decimals argument.

import numpy as np

detailed_float_array = np.array([1.2345, 6.7891, 3.14159, 0.5555])
num_decimals = 2

# ✅ Round each element to 2 decimal places
rounded_to_2_decimals = np.round(detailed_float_array, decimals=num_decimals)

print(f"Array rounded to {num_decimals} decimal places: {rounded_to_2_decimals}")

Output:

Array rounded to 2 decimal places: [1.23 6.79 3.14 0.56]

Rounding 2D NumPy Arrays

np.round() works element-wise for multi-dimensional arrays as well.

import numpy as np

array_2d_float = np.array([
    [10.123, 20.789, 5.5],
    [30.456, 40.001, 8.999]
])

# Round to nearest integer (decimals=0)
rounded_2d_integers = np.round(array_2d_float)
print("2D array rounded to nearest integers:")
print(rounded_2d_integers)

# Round to 1 decimal place
rounded_2d_1_decimal = np.round(array_2d_float, decimals=1)
print("2D array rounded to 1 decimal place:")
print(rounded_2d_1_decimal)

Output:

2D array rounded to nearest integers:
[[10. 21.  6.]
 [30. 40.  9.]]
2D array rounded to 1 decimal place:
[[10.1 20.8  5.5]
 [30.5 40.   9. ]]

Alternative Rounding Functions: numpy.ceil() and numpy.floor()

If you need specific types of rounding (always up or always down) rather than to the nearest value:

Rounding Up with numpy.ceil()

numpy.ceil(x) returns the ceiling of each element x, which is the smallest integer i such that i >= x.

import numpy as np

float_array = np.array([10.23, 25.88, 5.49, 12.50, 7.77])
ceiling_array = np.ceil(float_array)
print(f"Ceiling of the array (rounded up): {ceiling_array}")

Output:

Ceiling of the array (rounded up): [11. 26.  6. 13.  8.]

Rounding Down with numpy.floor()

numpy.floor(x) returns the floor of each element x, which is the largest integer i such that i <= x.

import numpy as np

float_array = np.array([10.23, 25.88, 5.49, 12.50, 7.77])
floor_array = np.floor(float_array)
print(f"Floor of the array (rounded down): {floor_array}")

Output:

Floor of the array (rounded down): [10. 25.  5. 12.  7.]

Conclusion

The TypeError: type numpy.ndarray doesn't define __round__ method occurs when you incorrectly try to use Python's built-in round() function with a NumPy array. NumPy arrays require NumPy's own vectorized functions for such operations.

• The primary solution is to use numpy.round(your_array, decimals=N) (or its alias numpy.around()) to perform element-wise rounding to the specified number of decimal places (or to the nearest integer if decimals is 0 or omitted).
• For rounding all elements up to the nearest integer, use numpy.ceil(your_array).
• For rounding all elements down to the nearest integer, use numpy.floor(your_array).

By using these dedicated NumPy functions, you can efficiently and correctly round the elements of your NumPy arrays.