📦 std_hlpr

📊 std_hlpr is a simple JavaScript utility package that provides basic statistical functions, such as:

• Mean (average)
• Standard Deviation
• Z-score (standard score)
• Min-Max Normalization

This package is useful for numeric data preprocessing, such as when you want to normalize data before:

• Statistical analysis
• Data visualization
• Simple machine learning processing on the frontend (e.g., React app or analytics dashboard)

🚀 Features

• ✅ Calculate mean (average)
• ✅ Calculate standard deviation
• ✅ Calculate z-score for a single value or an entire array
• ✅ Perform Min-Max normalization to scale values from 0 → 1
• ✅ Lightweight and dependency-free

🔧 Installation

npm install std-hlpr

📝 Usage Example

// src/App.js (or another file)
import {
  mean_s,
  std_dev,
  z_score_unit,
  z_score_array,
  std_min_max_array
} from './utils/std_hlpr';

const data = [10, 20, 30, 40, 50];

// Calculate mean
const mean = mean_s(data); 
// -> 30

// Calculate standard deviation
const std = std_dev(data, mean); 
// -> 14.142...

// Calculate z-score for a single value
const zSingle = z_score_unit(20, mean, std); 
// -> -0.707...

// Calculate z-scores for all elements in array
const zAll = z_score_array(data);
/* ->
{
  10: -1.414,
  20: -0.707,
  30: 0,
  40: 0.707,
  50: 1.414
}
*/

// Perform Min-Max normalization
const norm = std_min_max_array(data);
/* ->
{
  10: 0,
  20: 0.25,
  30: 0.5,
  40: 0.75,
  50: 1
}
*/

📘 API Reference

mean_s(array)

Calculates the mean of a numeric array.

• Parameter:
  array: number[]
• Return:
  number (mean)

std_dev(array, mean)

Calculates the standard deviation of a numeric array.

• Parameter:
  array: number[]
mean: number (mean of the array, optional for efficiency)
• Return:
  number (standard deviation)

z_score_unit(x, mean, std)

Calculates the z-score of a single value.

• Parameter:
  x: number (value to calculate)
  mean: number (dataset mean)
  std: number (dataset standard deviation)
• Return:
  number (z-score)

z_score_array(array)

Calculates z-scores for all elements of an array.

• Parameter:
  array: number[]
• Return:
  Record<number, number> (object with original value as key and z-score as value)

std_min_max_array(array)

Performs Min-Max normalization to scale values between 0 → 1.

• Parameter:
  array: number[]
• Return:
  Record<number, number> (object with original value as key and normalized value as value)

📄 License

MIT License © 2025
Free to use for personal or commercial projects. 🚀