Rock is one of the most popular music genre’s today but where did it begin? The following data visualization shows one facet of this complicated answer. In 2011 the Guardian released a list of 100 songs in their editorial judgement represent milestones in the evolution of rock and roll.
From that list we have added deeper context to the song with information about the artists, and analyses of qualitative attributes like energy level, and happy vs. sad. Trace the influence of bands beginning at the origin, Sister Rosetta Tharpe (1919 - 1973), to modern day groups such as Coldplay (1996 - present).
Visually see the “Golden Age” of Rock as song upon song stack around 1970. Below are sections about this site, where to get the data, and how it was built. We would love to hear feedback. You can reach out on Twitter, or by email. Happy exploration!
Excited about data visualization and design, Susie is an experienced front-end developer who has spent recent years focussed on data visualization. She draws from her degrees in art and engineering to bring a well-rounded perspective to data science, telling compelling stories with data and visualization.
@DataToViz
Before starting any data companies, John co-founded a record label in the early 90's Chicago independent music scene. In addition to authoring data strategies and engineering scalable data systems, John has written, engineered, produced, and released several recordings which at present has yet to make anyone's top 100 list.
@BigDataAnalysisSilicon Valley Data Science is a big data and data science consulting company that specializes in agile, data-driven development. We're committed to open source technologies, and using data and science for the public good.
We think applications like this can demonstrate how technology, craft, and data can be combined to deliver new perspectives and insight. We don't always get to talk about the work we do for clients, so we're delighted to share this visualization publicly. Please let us know what you think!
@SVDataScience100 songs that are representative of the history of rock
Choose an artist and find the bands that influenced that artist, and bands that artist influenced.
Find data points about a band such as familiarity, news articles, and reviews, and song data such as energy, speechiness, and danceability.
Find data points about a band such as band tracks, last.fm plays, and band photos.
I switched back and forth from Python and Excel for data exploration and data manipulation.
A website made by Shan Carter. It is used for converting tabular data into JSON objects. A very simple tool, but it has definitely improved my workflow from data exploration to front-end development.
An open source responsive grid and UI kit. Previously I had been using Bootstrap but I wanted to explore some of the other front-end solutions. Gumby interested me because it was built on Sass, which I also wanted to try.
This is a Model-Collection-View JavaScript library. Backbone creates structure for JavaScript code. I’ve learned to love Backbone because the organization it provides is indispensable for making an interactive app.
An open source network graph visualization tool. This was used to analyze the data from Music Bloodline and see the relationship of bands within the Guardian's selection.
Data-Driven Documents, is a JavaScript data visualization library. D3 has been in my toolkit ever since I started front-end development focused on data visualization. The library’s website has many examples of apps built with D3, and the list of examples from the community are extremely helpful.