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Dev 1.0.0
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‎.gitignore‎

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/vendor/

‎README.md‎

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# PHP-Scatterplot
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# PHP-Scatterplot
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PHP-Scatterplot is a tool for creating scatter plots.
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You can also retrieve parsed data:
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Mean, Variance, Standard Deviation, Covariance,
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Correlation Coefficient and Regression Line Formula.
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<img src="example/img/ChangingProperties.png" width="400" />
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## Contents
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- [Installation](#installation)
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- [Usage](#usage)
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- [Basic Usage](#basic-usage)
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- [Using Layers](#using-layers)
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- [Changing Properties](#changing-properties)
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- [Parsed Data](#parsed-data)
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- [Example](#example)
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- [License](#license)
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## Installation
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```bash
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composer require macocci7/php-scatterplot
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```
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## Usage
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### Basic Usage
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- PHP
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```php
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<?php
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require('../vendor/autoload.php');
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use Macocci7\PhpScatterplot\Scatterplot;
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$sp = new Scatterplot();
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$layers = [
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[
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'x' => [1,2,3,4,5,6,7,8,9,10,11],
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'y' => [1,2,3,4,5,8,4,7,11,9,1],
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],
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];
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$sp->layers($layers)
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->create('img/BasicUsage.png');
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```
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- Result
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<img src="example/img/BasicUsage.png" width="400" />
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### Using Layers
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- PHP
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```php
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<?php
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require('../vendor/autoload.php');
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use Macocci7\PhpScatterplot\Scatterplot;
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$sp = new Scatterplot();
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$layers = [
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'John' => [
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'x' => [1,2,3,4,5,6,7,8,9,10,11],
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'y' => [1,2,3,4,5,8,4,7,11,9,1],
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],
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'Jake' => [
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'x' => [1,2,3,4,5,6,7,8,9,10,11],
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'y' => [11,8,10,7,9,6,5,3,4,2,1],
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],
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'Hugo' => [
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'x' => [1,2,3,4,5,6,7,8,9,10,11],
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'y' => [4,8,10,1,9,6,5,3,7,1,11],
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],
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'Alex' => [
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'x' => [1,2,3,4,5,6,7,8,9,10,11],
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'y' => [3,5,11,4,8,2,9,10,1,11,7],
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],
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];
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$legends = array_keys($layers);
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$sp->layers($layers)
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->create('img/UsingLayers.png');
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```
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- Result
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<img src="example/img/UsingLayers.png" width="400" />
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### Changing Properties
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- PHP
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```php
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<?php
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require('../vendor/autoload.php');
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use Macocci7\PhpScatterplot\Scatterplot;
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$sp = new Scatterplot();
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$layers = [
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'John' => [
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'x' => [1,2,3,4,5,6,7,8,9,10,11],
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'y' => [1,2,3,4,5,8,4,7,11,9,1],
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],
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'Jake' => [
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'x' => [1,2,3,4,5,6,7,8,9,10,11],
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'y' => [11,8,10,7,9,6,5,3,4,2,1],
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],
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'Hugo' => [
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'x' => [1,2,3,4,5,6,7,8,9,10,11],
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'y' => [4,8,10,1,9,6,5,3,7,1,11],
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],
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'Alex' => [
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'x' => [1,2,3,4,5,6,7,8,9,10,11],
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'y' => [3,5,11,4,8,2,9,10,1,11,7],
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],
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];
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$legends = array_keys($layers);
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$sp->layers($layers)
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->limitX(0, 12)
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->limitY(0, 12)
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->gridXPitch(2)
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->gridYPitch(2)
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->bgcolor('#ccccff')
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->colors(['#ffffff'])
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->plotSize(4)
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->fontColor('#333333')
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->grid(1, '#999999')
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->gridXOn()
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->gridYOn()
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->regressionLine(3, ['#666666', '#cc2222', '#2222cc', '#22cc22'])
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->referenceLineX(1.5, 1, '#00ccff')
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->referenceLineY(1.5, 1, '#00ccff')
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->specificationLimitX(0.5, 11.5, 1, '#ff00ff')
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->specificationLimitY(0.5, 11.5, 1, '#ff00ff')
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->labelX('DATA X')
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->labelY('DATA Y')
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->caption('SCATTER PLOT')
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->legends($legends)
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->create('img/ChangingProperties.png');
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```
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- Result
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<img src="example/img/ChangingProperties.png" width="400" />
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### Parsed Data
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- PHP
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```php
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<?php
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require('../vendor/autoload.php');
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use Macocci7\PhpScatterplot\Analyzer;
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$a = new Analyzer();
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$layers = [
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'John' => [
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'x' => [1,2,3,4,5,6,7,8,9,10,11],
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'y' => [1,2,3,4,5,8,4,7,11,9,1],
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],
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'Jake' => [
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'x' => [1,2,3,4,5,6,7,8,9,10,11],
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'y' => [11,8,10,7,9,6,5,3,4,2,1],
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],
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];
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var_dump($a->parse($layers));
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```
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- Result
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```bash
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array(2) {
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["John"]=>
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array(6) {
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["count"]=>
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int(11)
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["x"]=>
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array(5) {
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["Mean"]=>
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int(6)
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["Max"]=>
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int(11)
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["Min"]=>
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int(1)
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["Variance"]=>
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int(10)
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["StandardDeviation"]=>
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float(3.1622776601683795)
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}
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["y"]=>
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array(5) {
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["Mean"]=>
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int(5)
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["Max"]=>
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int(11)
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["Min"]=>
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int(1)
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["Variance"]=>
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float(10.181818181818182)
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["StandardDeviation"]=>
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float(3.1908961408698624)
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}
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["Covariance"]=>
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float(5.181818181818182)
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["CorrelationCoefficient"]=>
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float(0.5135343537364686)
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["RegressionLineFormula"]=>
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array(2) {
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["a"]=>
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float(0.5181818181818182)
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["b"]=>
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float(1.8909090909090907)
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}
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}
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["Jake"]=>
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array(6) {
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["count"]=>
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int(11)
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["x"]=>
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array(5) {
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["Mean"]=>
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int(6)
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["Max"]=>
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int(11)
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["Min"]=>
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int(1)
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["Variance"]=>
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int(10)
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["StandardDeviation"]=>
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float(3.1622776601683795)
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}
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["y"]=>
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array(5) {
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["Mean"]=>
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int(6)
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["Max"]=>
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int(11)
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["Min"]=>
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int(1)
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["Variance"]=>
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int(10)
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["StandardDeviation"]=>
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float(3.1622776601683795)
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}
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["Covariance"]=>
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float(-9.454545454545455)
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["CorrelationCoefficient"]=>
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float(-0.9454545454545453)
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["RegressionLineFormula"]=>
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array(2) {
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["a"]=>
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float(-0.9454545454545455)
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["b"]=>
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float(11.672727272727274)
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}
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}
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}
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```
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## Example
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- [BasicUsage.php](example/BasicUsage.php) >> results in [BasicUsage.md](example/BasicUsage.md)
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- [UsingLayers.php](example/UsingLayers.php) >> results in [UsingLayers.md](example/UsingLayers.md)
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- [ChangingProperties.php](example/ChangingProperties.php) >> results in [ChangingProperties.md](example/ChangingProperties.md)
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- [ParsedData.php](example/ParsedData.php) >> results in [ParsedData.txt](example/ParsedData.txt)
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## License
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[MIT](LICENSE)
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***
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*Document written: 2023/06/06*
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*Document updated: 2023/06/07*
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Copyright 2023 macocci7.

‎composer.json‎

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{
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"name": "macocci7/php-scatterplot",
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"description": "it's easy to use for creating scatter plots.",
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"version": "1.0.0",
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"type": "library",
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"license": "MIT",
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"autoload": {
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"psr-4": {
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"Macocci7\\PhpScatterplot\\": "src/"
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}
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},
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"authors": [
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{
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"name": "macocci7",
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"email": "macocci7@yahoo.co.jp"
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}
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],
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"minimum-stability": "stable",
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"require": {
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"intervention/image": "^2.7",
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"macocci7/php-frequency-table": "^1.1"
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}
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}

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