A simple tool to compute and interpret Pearson correlation coefficients.
Project description
correlation_stats_analyzer
A lightweight Python package to compute and interpret the strength and direction of correlation between two numerical datasets using the Pearson Correlation Coefficient.
Features
- Compute the Pearson correlation coefficient between two numeric lists.
- Interpret the result in terms of strength and direction (e.g., "Strong Positive").
- Zero dependencies – works with standard Python only.
- Designed for data science beginners, educators, and small-scale analysis scripts.
Installation
pip install correlation_stats_analyzer
Usage Example
import correlation_stats_analyzer as csa
x = [10, 20, 30, 40, 50]
y = [12, 22, 29, 41, 52]
r = csa.correlation_r(x, y)
strength, direction = csa.interpret_r(r)
print(f"Pearson r: {r:.4f}")
print(f"Strength: {strength}, Direction: {direction}")
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