NumPy RuntimeWarning: Mean of empty slice in Python

Here, we will see how to fix “Numpy Runtimewarning: Mean Of Empty Slice” in Python. In this article, we will see the reasons for it’s occurrence and also the solution of NumPy RuntimeWarning: Mean of empty slice in Python.

What is NumPy RuntimeWarning: Mean of empty slice in Python?

The NumPy RuntimeWarning: Mean of empty slice in Python occurs when attempting to calculate the mean of an empty NumPy array slice. This warning is an indication that the code is trying to perform a mathematical operation on a subset of an array that has no elements. Understanding the reasons behind this warning is crucial for resolving the issue effectively.

Syntax:

Numpy Runtimewarning: Mean Of Empty Slice

Below is the reason why NumPy RuntimeWarning: Mean of empty slice occurs in Python:

• Empty Slicing
• Invalid Indexing

Empty Array

In this example, the code creates an empty NumPy array, and then attempts to calculate the mean of a slice with no elements, triggering a “RuntimeWarning: Mean Of Empty Slice” because there are no values to compute the mean from.

Python3

import numpy as np

#defining the array
empty_array = np.array([])
np.mean(empty_array)

Output

/usr/local/lib/python3.7/site-packages/numpy/core/fromnumeric.py:3441: RuntimeWarning: Mean of empty slice.
  out=out, **kwargs)
/usr/local/lib/python3.7/site-packages/numpy/core/_methods.py:189: RuntimeWarning: invalid value encountered in double_scalars
  ret = ret.dtype.type(ret / rcount)

Invalid Indexing

In this example, below code creates an empty slice with indices [5:2] from a NumPy array, and then attempts to calculate the mean of this empty slice, resulting in a “RuntimeWarning: Mean Of Empty Slice” since there are no elements in the slice.

Python3

import numpy as np

data = np.array([1, 2, 3, 4, 5])
empty_slice = data[5:2]
output = np.mean(empty_slice)
print(output)

Output

packages/numpy/core/fromnumeric.py:3504: RuntimeWarning: Mean of empty slice.
  return _methods._mean(a, axis=axis, dtype=dtype,
/usr/local/lib/python3.10/dist-packages/numpy/core/_methods.py:129: RuntimeWarning: invalid value encountered in scalar divide
  ret = ret.dtype.type(ret / rcount)

Solution for NumPy RuntimeWarning: Mean of empty slice in Python

Below, are the approaches to solve NumPy RuntimeWarning: Mean of empty slice in Python:

• Check for empty arrays
• Correcting indexing

Check For Empty array

In this example, below code creates an empty NumPy array, checks if it’s non-empty before calculating the mean of a slice, and prints the mean if there are elements, or a message stating that the array is empty if it is indeed empty.

Python3

import numpy as np

empty_array = np.array([])

# Checking for empty array before calculating the mean
if len(empty_array) > 0:
    mean_value = np.mean(empty_array[1:3])
    print("Mean:", mean_value)
else:
    print("Array is empty.")

Output

Array is empty.

Correct Indexing

In this example, below code creates a NumPy array with a single element and correctly calculates the mean of the array using appropriate indexing to avoid accessing elements beyond the array bounds.

Python3

import numpy as np

single_element_array = np.array([42])

# Correcting indexing to prevent accessing elements beyond array bounds
mean_value = np.mean(single_element_array[:1])
print("Mean:", mean_value)

Output

Mean: 42.0