Skip to main content

Documentation Index

Fetch the complete documentation index at: https://mintlify.com/davi-huanuco/python-matriz-correlacion/llms.txt

Use this file to discover all available pages before exploring further.

Matriz de Indicadores is a desktop application built with Python and Flet that lets you define performance indicators, collect monthly numeric data, generate Pearson correlation matrices, and compare indicators against benchmark reference values — all with a clean graphical interface and local JSON persistence.

Installation

Set up your virtual environment and install all dependencies to run the app.

Quickstart

Get up and running in minutes: clone, install, and launch the app.

User Guide

Step-by-step instructions for managing months, indicators, and data.

Correlation Matrix

Learn how to generate and interpret the Pearson correlation matrix.

What you can do

Manage time periods

Register and organize the months used as columns in your data tables.

Define indicators

Create performance indicators with codes and descriptive names.

Enter monthly data

Input numeric values for each indicator across every registered month.

Benchmarking

Compare indicator averages against reference values and see compliance metrics.

How it works

1

Register your months

Add the time periods (e.g., January, February) that structure your data collection.
2

Define your indicators

Create indicators with a short code (e.g., IND001) and a descriptive name.
3

Enter numeric values

For each indicator, fill in the numeric value for every registered month.
4

Generate the correlation matrix

Click Matriz de correlación to compute Pearson correlation coefficients between all indicator pairs.
5

Benchmark your results

Add benchmark reference values to see gaps, compliance percentages, and pass/fail status per indicator.
All data is stored locally in a datos.json file in the project directory. No internet connection or external database is required.

Build docs developers (and LLMs) love