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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.

Once you have completed the installation, you can launch Matriz de Indicadores with a single command. The app opens a 900×760 px desktop window in light theme and loads all your saved data from datos.json automatically.
1

Activate the virtual environment

Open a terminal in the project directory and activate the virtual environment:
venv\Scripts\activate
Your prompt will show (venv) to confirm the environment is active.
2

Run the app

Start the application by running main.py:
python main.py
Flet will launch a native desktop window titled Registro de Indicadores. The navigation bar at the top gives you access to all five views.
3

Explore the five views

Use the buttons in the header to navigate between views:
  • Meses — Define the months you want to track. Changes here are synchronized across all other views automatically.
  • Indicadores — Create and manage your performance indicators. Each indicator will appear across all configured months.
  • Datos — Enter numeric values for each indicator and month. Edit values inline and save to persist them to datos.json.
  • Matriz — View the Pearson correlation matrix calculated from your recorded data. Spot relationships between indicators at a glance.
  • Benchmarking — Compare indicator values against benchmark targets and track performance gaps over time.
The app window is fixed at 900×760 px and uses a light theme. All data is saved locally to datos.json in the project root — no internet connection is required.

Explore the user guide

Once the app is running, consult the user guide sections below to learn how to use each view in detail.

Months

Learn how to add, edit, and remove months that define your tracking period.

Indicators

Create and manage performance indicators with codes and descriptive names.

Data entry

Enter and update indicator values for each month using the data table.

Correlation matrix

Interpret the Pearson correlation matrix generated from your data.

Benchmarking

Set benchmark targets and compare them against your recorded values.

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