TheAlgorithms/Python · error · ValueError

The list is empty. Provide a non-empty list.

Error message

The list is empty. Provide a non-empty list.

What it means

Raised by interquartile_range in maths/interquartile_range.py when nums is an empty list. The IQR is defined as Q3 - Q1 of the sorted data, which is meaningless without observations; additionally the function calls nums.sort() and slices around the midpoint, which would fail or produce nonsense on empty input. The explicit ValueError fires first (note: an empty list is falsy, so 'if not nums' also catches None).

Source

Thrown at maths/interquartile_range.py:54

    Return the interquartile range for a list of numeric values.
    :param nums: The list of numeric values.
    :return: interquartile range

    >>> interquartile_range(nums=[4, 1, 2, 3, 2])
    2.0
    >>> interquartile_range(nums = [-2, -7, -10, 9, 8, 4, -67, 45])
    17.0
    >>> interquartile_range(nums = [-2.1, -7.1, -10.1, 9.1, 8.1, 4.1, -67.1, 45.1])
    17.2
    >>> interquartile_range(nums = [0, 0, 0, 0, 0])
    0.0
    >>> interquartile_range(nums=[])
    Traceback (most recent call last):
    ...
    ValueError: The list is empty. Provide a non-empty list.
    """
    if not nums:
        raise ValueError("The list is empty. Provide a non-empty list.")
    nums.sort()
    length = len(nums)
    div, mod = divmod(length, 2)
    q1 = find_median(nums[:div])
    half_length = sum((div, mod))
    q3 = find_median(nums[half_length:length])
    return q3 - q1


if __name__ == "__main__":
    import doctest

    doctest.testmod()

View on GitHub (pinned to f5988cc097)

Solutions

1. Check len(data) > 0 before computing and handle the empty case explicitly (skip, impute, or report).
2. When aggregating groups, skip empty buckets: if not group: continue.
3. If None is possible, distinguish it from [] and convert missing data to an empty-list skip path.

Example fix

// before
iqr = interquartile_range(nums=group_data)  # some groups are empty

// after
if not group_data:
    continue  # or handle empty-group policy
iqr = interquartile_range(nums=group_data)

if not nums:
    raise ValueError("cannot compute IQR of empty data")
iqr = interquartile_range(nums=nums)

def is_non_empty_list(v) -> bool:
    return isinstance(v, list) and len(v) > 0

try:
    iqr = interquartile_range(nums=group)
except ValueError as e:
    if 'empty' in str(e):
        iqr = None  # mark group as having no statistic
    else:
        raise

When it happens

Trigger: Calling interquartile_range(nums=[]) or interquartile_range(nums=None). Any empty or falsy nums argument triggers the guard before sorting.

Common situations: Grouping data by key and hitting an empty group; filters that remove all rows before statistics; ETL pipelines passing empty batches; None defaults flowing through from optional parameters.

Related errors

• Missing an input
• surface_area_cube() only accepts non-negative values
• surface_area_cuboid() only accepts non-negative values
• surface_area_sphere() only accepts non-negative values
• surface_area_hemisphere() only accepts non-negative values

AI-assisted analysis of TheAlgorithms/Python@f5988cc097 (2026-08-14). Data as JSON: /api/errors/c7be32b1028b3178. Report an issue: GitHub.