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Hello! ✨

I'm Nina (she/her), a post doc at the University of Bristol.
My research is in the field of mental health data science, which uses data science methods to understand mental health better.

You'll find the work on my profile falls into three categories:

  • research software for running studies (usually in Python 🐍)
  • data analysis (usually in R πŸ΄β€β˜ οΈ )
  • manuscripts and reports (usually in .Rmd or LaTeX)

I also spend a lot of time working on repositories on my lab group's page, where you'll find more work on webapps, and with Data Ethics Club where you'll find our lovely community of ethics-inclined data people!

Please feel free to email me, find me on Twitter or have a look at my website.
🐦 @ninadicara


  1. very-good-science/data-ethics-club very-good-science/data-ethics-club Public

    A reading list and fortnightly discussion group designed to provoke discussion about ethical applications of, and processes for, data science.

    Python 79 13

  2. very-good-science/data-hazards very-good-science/data-hazards Public

    Data Hazards is a project to find a shared vocabulary for talking about worst-case scenarios of data science - and to use that vocabulary to help people understand and avoid Data Hazards.

    HTML 31 14

  3. DynamicGenetics/COVID-19-Community-Response DynamicGenetics/COVID-19-Community-Response Public

    Mapping community support in Wales during the COVID-19 pandemic

    CSS 5

  4. DynamicGenetics/Mood-Music DynamicGenetics/Mood-Music Public

    A web platform and framework to manage an EMA study with Spotify and Twilio integration (in development)

    Python 2

  5. DynamicGenetics/Spotify-Rehydrator DynamicGenetics/Spotify-Rehydrator Public

    A simple package for developing a full dataset of track features from self-requested Spotify data 🌱


  6. Generate a semi-randomised EMA schedule Generate a semi-randomised EMA schedule
    # EMA Scheduler
    The `ema_schedule` module defines a class that produces a schedule for EMA 'beeps' (survey time points). 
    This version does not contain 'sense-checking' for the arguments inputs. 
    It expects start_time and end_time as floats that represent 24 hour time (i.e. `4.30pm` would be entered as `16.5`)