infografía

The following presents a new guide to Exploratory Data Analysis (EDA) implemented in Python, which evolves and complements the version published in R in 2021. This update responds to the needs of an increasingly diverse community in the field of data...

Public sector bodies must make their data available for re-use, making it accessible in the form of open data, as referred to in Spain's legislative framework. The first step for this is that each entity, at local, regional and state level, as well as...

Discover which are the strategic frameworks that mark the publication and use of open data, as well as the most outstanding datasets at local, regional, national and international level through the various infographics that we will publish periodically...

These infographics show examples of the use of open data in certain sectors, as well as data from studies on its impact. New content will be published periodically. 1. Open Data and Urban Management: Innovative Use Cases Published: July 2024...

Open data can be the basis for various disruptive technologies, such as Artificial Intelligence, which can lead to improvements in society and the economy. These infographics address both tools for working with data and examples of the use of open data...

Thanks to these infographics you can learn a little more about the activity of datos.gob.es and the functionalities of the platform. New contents will be published periodically. 1. Dissemination of the data culture Published: January 2023...

The Aporta Challenges are awards for new ideas and prototypes that, making use of open data, lead to efficiency improvements in a specific sector of activity. In this section you will find infographics with information about the different editions...

At the end of each year, at datos.gob.es we take an overview of the activity carried out during the last 365 days. In these infographics you will find a summary of the actions carried out and the achievements. New content will be published periodically...

Before performing data analysis, for statistical or predictive purposes, for example through machine learning techniques, it is necessary to understand the raw material with which we are going to work. It is necessary to understand and evaluate the...

In order to extract the full value of data, it is necessary to classify, filter and cross-reference it through analytics processes that help us draw conclusions, turning data into information and knowledge. Traditionally, data analytics is divided into 3...