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Dashboard Week Day 4: Music & Mental Health

This post was originally published on The Data School blog between 2018 and July 2025, before our program was renamed to MIP’s Analytics Career Accelerator. References throughout this article to “The Data School” or “DS” all refer to what is now MIP’s Analytics Career Accelerator. The program, its people, and its commitment to launching outstanding analytics careers remain the same – just under a new name.

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Our third day of Dashboard Week required us to connect to Music & Mental Health data on Kaggle to make a dashboard to show a story we found.

The first thing that jumped out as me was all the different music genres in the data so I decided to focus my analysis on how the different music genres affect mental health.

 

In Alteryx

The data was quite clean, though the main change I made was to take all of the different genre frequency columns and transpose the data so there was a row per respondent and genre. The other processing included creating a row ID and coding the Likert scale values numerically.

 

In Tableau

I began by exploring relationships with age, number of hours listening to music and other factors not related to the music. I didn’t find much of interest so I decided to look at the frequencies that different respondents listened to different genres, and also look at how their favourite genre was related to how they felt that music affected their mental health conditions. I then wanted to see if different initial mental health conditions seemed correlated with whether they felt that music affected their mental health conditions and found a great trend there. I tried a few other things but ended up wanting to look at how the average age and number of different genres listened to varied with the respondents’ different favourite genres. I hope you enjoy the result!

 

 

Dashboard Week Day 4 – Music & Mental Health

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