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Example code of koolreport/statistics

Informations about the package statistics

Introduction

Talking about data, we also talk about statistics because we learn about data through statistics. The Statistics package allows you to compute basic and advanced statistical measures for columns of your data. The basic measures could be min, max, mean, median, etc. The advanced measures are, for example, lowerQuartile, popStdDeviation and others.

Installation

By downloading .zip file

  1. Download
  2. Unzip the zip file
  3. Copy the folder statistics into koolreport folder so that look like below

By composer

Documentation

Quick start

In your report's setup page, use the process \koolreport\statistics\Statistics with an array parameter in the type of '{{statistical measure}}' => '{{array of column names}}'

Then in your view, you could use the utility StatisticsReader to extract the measures:

Properties

The package supports the following statistical measures:

name description
min Returns the first minimum value of a data series.
max Returns the first maximum value of a data series.
mode Returns the first most common value of a data series.
mean Returns the average value of a data series.
median Returns the middle value that divides a data series into 2 equal halves when ordering.
lowerQuartile Returns the first quartile of the quartiles that divides a data series into 4 equal group when ordering. The second quartile is the median.
upperQuartile Returns the third quartile.
percentile_X Returns the value that X percentage of a data series fall below when ordering. X is an integer from 0 to 100.
meanDeviation Returns the mean absolute deviation value of a data series in the formula of Sum of absolute(elementValue - mean) / length of data series.
popStdDeviation Returns the population standard deviation value of a data series in the formula of Square root of (sum of square(elementValue - mean) / length of data series).
samStdDeviation Returns the sample standard deviation value of a data series in the formula of Square root of (sum of square(elementValue - mean) / (length of data series - 1)).

Support

Please use our forum if you need support, by this way other people can benefit as well. If the support request need privacy, you may send email to us at [email protected].

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