Democritus functions^[1] for working with statistics.

[1] Democritus functions are simple, effective, modular, well-tested, and well-documented Python functions.

We use d8s (pronounced "dee-eights") as an abbreviation for democritus (you can read more about this here).

pip install d8s-stats

You import the library like:

from d8s_stats import *

Once imported, you can use any of the functions listed below.

• def statistical_overview(
      data, *, data_is_sample: bool = False, result_if_no_mode: Any = None, raise_error_if_no_mode: bool = True
  ):
      """Return an overview of the data's statistical properties."""

• def mode(data, *, result_if_no_mode: Any = None, raise_error_if_no_mode: bool = True):
      """Return the item in the data which occurs the greatest number of times."""

• def variance(data, *, data_mean=None, data_is_sample: bool = False):
      """Return the variance of the data (assuming the data represents an entire population)."""

• def stdev(data, *, data_mean=None, data_is_sample: bool = False):
      """Return the standard deviation of the data (assuming the data represents an entire population)."""

• def mean(iterable):
      """Return the average of the list."""

• def harmonic_mean(iterable):
      """Return the harmonic mean of the list."""

• def geometric_mean(iterable):
      """Return the geometric mean of the list."""

👋  If you want to get involved in this project, we have some short, helpful guides below:

• contribute to this project 🥇
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If you have any questions or there is anything we did not cover, please raise an issue and we'll be happy to help.

This package was created with Cookiecutter and Floyd Hightower's Python project template.