Abstract:

In our society, data holds a pivotal position, driving decision-making across various domains like politics, business, and society. Journalism has also benefited from this data-driven era, as access to extensive databases has unlocked new opportunities. In the education field, themes like infographics, storytelling, and data journalism have emerged prominently, reflecting the significance of this data-driven landscape.

However, to effectively delve into and extract valuable insights from extensive databases, technical skills, particularly in programming, are essential. Unfortunately, journalism education in Portugal often overlooks or inadequately addresses this aspect. Therefore, there is a pressing need to adapt teaching methods to cater to the emerging demands of these future professionals.

Aware that data journalists currently need new knowledge and skills to be successful in their profession, in this paper we present a brief introduction to Python, accessible to those who have no programming knowledge. Where the main objectives are to prepare a database for analysis and do some simple analysis. The code used is presented in a simple way and with comments in order to be easily adapted to other databases.

Recognizing the evolving demands of data journalists and their need for new knowledge and skills to excel in their profession, in this work we provide a brief introduction to Python, designed for those with no prior programming experience. The primary objectives include database preparation for analysis and performing basic data analysis tasks. The provided code is presented in a straightforward manner, accompanied by comments, making it easily adaptable for use with other databases.

The presented examples showcase the added value of using a programming language to analyze large databases. Moreover, the provided code can be effortlessly replicated to deal with other databases.

In this way, we aim to contribute to the continuous adaptation of journalism education in our course while fostering the same in other higher education institutions. By disseminating our findings, especially the utilized code, which has comments, we hope that fellow colleagues can adapt it to their needs. And also contribute to the exchange of knowledge and best practices among different higher education institutions.

Keywords:

Journalism, Data analysis, Python.