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
Features for the creation of data spaces
A data space is an ecosystem where, on a voluntary basis, the data of its participants (public sector, large and small technology or business companies, individuals, research organizations, etc.) are pooled. Thus, under a context of sovereignty, trust and security, products or services can be…
- Guides
How to deal with a data analysis project?
By analysing data, we can discover meaningful patterns and gain insights that lead to informed decision making. But good data analysis needs to be methodical and follow a series of steps in an orderly fashion. In this video (in Spanish) we give you some tips on the steps to follow:
The importance…
- 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
Emerging Technologies and Open Data: Predictive Analytics
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 categories:
Descriptive analytics, which…
- Reports and studies
