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Go to the profile of Sofia Pinto
Sofia Pinto in Data science at Nesta

Python packages for assessing the quality of your data

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Go to the profile of Liz Gallagher
Liz Gallagher in Data science at Nesta

Measuring Workforce Greenness via Job Adverts: Part 3, Skills

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Go to the profile of Tom Willcocks
Tom Willcocks in Data science at Nesta

How to Use GitHub Actions to Automate Data Scraping

A tutorial and evaluation of GitHub Actions for…

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Go to the profile of Cath Sleeman
Cath Sleeman in Data science at Nesta

Mind the gap

Five steps to mapping data gaps

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Go to the profile of Emily Bicks
Emily Bicks in Data science at Nesta

Learning about data through physicalisation

This workshop was adapted from the content published by Dr. Samuel Huron et al in…

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Go to the profile of Karlis Kanders
Karlis Kanders in Data science at Nesta

Tutorial: data-driven news discourse analysis with Python (Part 1)

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Go to the profile of Iman Muse
Iman Muse in Data science at Nesta
Overview: Visual representation of the clustering of health apps into 15 clusters. The cluster with the highest number of apps is ‘Workout’ with 428. The cluster with the lowest number of apps is ‘Cycle Tracker Apps’ with 12 apps. Presentation: Each app is represented by a circle, the colour of each circle reflects one of the 15 categories that had been assigned using k means clustering. The figure shows clusters of circles represented by distinctive colours.

Mapping Health Apps

From mindfulness to diet tracking, health apps have the potential to help people…

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Go to the profile of Karlis Kanders
Karlis Kanders in Data science at Nesta

Tutorial: data-driven news discourse analysis with Python (Part 2)

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Go to the profile of Emily Bicks
Emily Bicks in Data science at Nesta

Beyond the hype: GPT-4 vs traditional machine learning for imputing missing data

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Go to the profile of Chris Williamson
Chris Williamson in Data science at Nesta
A team of people participating in an ideation session, sticking post-it notes on a wall

5 key tips for data scientists in mixed-method teams

How to bridge the gaps and work well together

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Data science at Nesta
Data science at Nesta
We use this blog to share technical aspects of our work. Get in touch via dataanalytics@nesta.org.uk or leave a comment on individual articles if you would like to connect with the team.
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