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numpy.nan_to_num() in Python

Last Updated : 10 Jul, 2025

numpy.nan_to_num() function replaces NaN (Not a Number) with a specified numerical value (default is 0), and optionally converts positive or negative infinity to finite numbers.

Example:


Output
[ 1.00000000e+000 0.00000000e+000 1.79769313e+308 -1.79769313e+308]

Explanation: By default, NaN is replaced with 0. Infinity values remain unchanged unless specified.

Syntax

numpy.nan_to_num(x, copy=True, nan=0.0, posinf=None, neginf=None)

Parameters:

  • x: Input array (can be scalar, array-like).
  • copy: If True (default), returns a copy. If False, modifies the array in-place.
  • nan: Value to replace NaNs with (default is 0.0).
  • posinf: Value to replace positive infinity with (optional).
  • neginf: Value to replace negative infinity with (optional).

Returns: This method returns an array with the same shape as x, where NaN, +inf and -inf are replaced with finite numbers.

Examples

Example 1: Replace only NaNs with zero


Output
[0. 2. 3.]

Explanation: NaN is replaced with 0, other values are unchanged.

Example 2: Replace NaN and infinite values


Output
[ 0. 1000. -1000. 5.]

Explanation: NaN → 0, +inf → 1000, -inf → -1000 and regular values like 5 remain unchanged.

Example 3: In-place modification with copy=False


Output
[-1.000e+00 9.999e+03]

Explanation: The original array 'a' is modified directly without making a copy.

Related articles:Numpy

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