The Ultimate 2000s Playlist

Inspiration

We love music, and the 2000s was a golden age! This is the era of music that we grew up with. We wanted to capture the essence of the music of our childhood.

What it does

Our project finds the average value of Spotify's built in song attributes, danceability, loudness, energy, valence, and speechiness for the top 50 songs of the 2000s. Then we use those averages to create a playlist of 2000s songs for which each of their attributes falls within 10% if the average.

How we built it

We used python to utilize the Spotify web API to search for songs and find their attribute values. Then we used the API again to search for songs that fell within our desired attribute value ranges. We also matplotlib to visualize the attribute values and how they changed over time.

Challenges we ran into

None of us are very experienced with using API's, and we have never used the Spotify API. It was difficult to get the data, and change it into a format that we could use.

Accomplishments that we're proud of

We were able to figure out how to access and format data from an API, which we were not sure we would be able to do! We were also able to make an awesome playlist that we are exciting to start listening to.

What we learned

We learned how to get data from an API, and how to format it from a JSON object into something we could work with in Python. We also learned more about data visualization using matplotlib.

What's next for The Ultimate 2000s Playlist

We hoped to be able to make an interactive website that will create a custom nostalgic playlist based on users' attribute preferences. We did not have enough time to figure that out this weekend, but with a bit more work it will hopefully be up and running.

Built With

Submitted to

Carolina Data Challenge 2023

Created by

A lot of my contribution came during the beginning steps of the project. I helped with finding a project idea and structuring the projects many parts. I had some ideas that did not come to fruition due to time. I had the intention of adding more visualizations based on genre but these plans fell through.

Queston Parker
I worked some on the back end development, but mainly on the front end. I helped develop the algorithm to get songs from certain years from the spotify api. It was my second time using html and css and I created an html page for users to input the parameters that they want for their playlist. It was my first time using flask, and I struggled with posting the input data from the html file to the flask file. After a couple of hours, I was finally able to send the data to flask. However, I am still struggling with implementing this data into the playlist generator itself. So for now we just have to manually input the danceability, loudness, valence, energy and speechiness into the code for the playlist generator. I hope to work on syncing this data in order to make the front end usable.

Gaines Diseker
Judson Greer
Nick Mountain