A lightweight statistics helper library for learning
Project description
mystats-helper
A lightweight, pure-Python statistics helper library built for learning.
Installation
pip install mystats-helper-adamdockstader
In futurecoder / Pyodide
import micropip
await micropip.install("mystats-helper-adamdockstader")
Quick Start
import mystats_helper
data = [4, 8, 15, 16, 23, 42]
# Descriptive statistics
print(mystats_helper.mean(data)) # 18.0
print(mystats_helper.median(data)) # 15.5
print(mystats_helper.stdev(data)) # 13.28...
print(mystats_helper.describe(data)) # full summary dict
# Z-scores
print(mystats_helper.z_scores(data))
# Correlation & regression
x = [1, 2, 3, 4, 5]
y = [2, 4, 5, 4, 5]
print(mystats_helper.correlation(x, y))
slope, intercept = mystats_helper.linear_regression(x, y)
print(f"y = {slope:.2f}x + {intercept:.2f}")
Available Functions
| Function | Description |
|---|---|
mean(data) |
Arithmetic mean |
median(data) |
Median |
mode(data) |
Mode (most frequent value) |
variance(data, population=False) |
Sample or population variance |
stdev(data, population=False) |
Standard deviation |
z_score(x, mu, sigma) |
Single z-score |
z_scores(data) |
Z-scores for all values |
percentile(data, p) |
p-th percentile (0–100) |
iqr(data) |
Interquartile range |
correlation(x, y) |
Pearson's r |
linear_regression(x, y) |
Returns (slope, intercept) |
describe(data) |
Summary dict (count, mean, stdev, min, Q1, median, Q3, max) |
License
MIT
Project details
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