5 documents found
A practical introductory guide to exploratory data analysis in Python
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 science.
Exploratory Data Analysis (EDA)…
- Guides
Introduction to data anonymisation: Techniques and case studies
Data anonymization defines the methodology and set of best practices and techniques that reduce the risk of identifying individuals, the irreversibility of the anonymization process, and the auditing of the exploitation of anonymized data by monitoring who, when, and for what purpose they are used…
- Guides
Practical guide for improving the quality of open data
When publishing open data, it is essential to ensure its quality. If data is well documented and of the required quality, it will be easier to reuse, as there will be less additional work for cleaning and processing. In addition, poor data quality can be costly for publishers, who may spend more…
- Guides
A practical introductory guide to exploratory data analysis
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 quality of the data in order to, among other…
- Guides
Share-PSI 2.0: Las mejores prácticas para compartir información del sector público
Iniciativa Aporta – Datos.gob.es ha actualizado y enriquecido las 56 mejores prácticas para compartir información del sector público que fueron recopiladas por la red temática Share-PSI 2.0. El repositorio de Share-PSI 2.0. concebido para servir de orientación a todas las organizaciones públicas a…
- Guías
