Examples

This page shows simple examples for each public function in dumbpy. (Examples are shown for demonstration and are not executed during the docs build.)

arithmetic_mean

Compute the average of numbers. Nested lists are flattened first.

from dumbpy import arithmetic_mean

arithmetic_mean([1, 2, 3, 4])  # 2.5
arithmetic_mean([1, [2, 3]])   # 2.0

from dumbpy import arithmetic_mean

# arithmetic_mean([])  # raises ValueError

median

Compute the median (middle value) of numbers. Nested lists are flattened first.

from dumbpy import median

median([3, 1, 2])        # 2
median([1, 2, 3, 4])     # 2.5

from dumbpy import median

# median([])  # raises ValueError

std_deviation

Compute the population standard deviation of numeric values. Nested lists are flattened first.

from dumbpy import std_deviation

std_deviation([1, 1, 1, 1])     # 0.0
std_deviation([1, 2, 3, 4])     # 1.118033988749895

from dumbpy import std_deviation

# std_deviation([])  # raises ValueError

flatten_list

Flatten a nested iterable into a one-dimensional Python list.

from dumbpy import flatten_list

flatten_list([1, 2, [3, 4]])            # [1, 2, 3, 4]
flatten_list([[1, 2], [3, [4, 5]]])     # [1, 2, 3, 4, 5]
flatten_list([])                        # []

from dumbpy import flatten_list

# flatten_list("abc")  # raises TypeError (strings are not allowed as top-level input)

validate_list

Flatten the input and ensure all resulting values are numeric (int, float, or bool).

from dumbpy import validate_list

validate_list([1, 2, 3.5])     # [1, 2, 3.5]
validate_list([1, True, 6])    # [1, True, 6]

from dumbpy import validate_list

# validate_list([1, "a", 3])  # raises TypeError: a is not a numeric value.