test2

100%

✓ Published0🌍 Public

Last edited Nov 21, 2022

Created on Nov 21, 2022

Forked from Yearly Top Genre Trend and Artist with Music Signature

This interactive scatterplot explores the top 20 Spotify songs per year in the U.S. from 2010 to 2019, plotting musical attributes like tempo and energy against each other. Users can switch the color encoding between top genre and artist, and hover over legend items to highlight specific categories while tooltips reveal song details. The visualization uses React with D3 v5 scales for positioning and color, rendering as SVG circles with dropdown menus for axis and color selections.

AI-generated description

This viz shows the change of top genre of Spotify in the U.S. The top 20 songs of each year from 2010 to 2019 are selected foR this analysis. The slider of Year makes it possible to either focusing on a particular year or comparing over years. The color scale can be selected to show the artist or top genre. X and Y axis can be set to the features of interest. To see a specific Top Genre/Artist, just move mouse on the figure legend to hover one. To know the song of each data point, move your mouse over the point on the scatter plot, it will show the title, artist and top genre of that song.

MIT Licensed

Similar vizzes

Loading thumbnail…

Fork of Yearly Top Genre Trend and Artist with Music Signature

This interactive scatter plot explores the top 20 Spotify songs in the U.S. from 2010 to 2019, showing relationships between musical attributes like Tempo, Energy, and Loudness. Users can adjust the X and Y axes via dropdown menus, filter by year, and toggle color encoding between top genre and artist. Hovering over legend items highlights matching points, while hovering over a circle reveals the song’s title, artist, and genre. Built with React and d3.v5, it uses `scaleLinear` for axes, `scaleOrdinal` for colors, and SVG circles for marks. Data originates from a public Spotify dataset.

SSandyWu7179290504

88% match

Loading thumbnail…

Fork of Yearly Top Genre Trend and Artist with Music Signature

This interactive scatterplot visualizes the top 20 Spotify songs in the U.S. for each year from 2010 to 2019, letting users explore musical attributes like tempo, energy, and danceability across different genres and artists. A year slider filters songs, while dropdown menus select the x-axis, y-axis, and color encoding for artist or genre, with a hovering legend highlighting specific categories. The visualization uses D3 v5 scales for positioning and color, React for state management, and renders SVG circles with hover tooltips showing song details from the yearly_music_trend dataset.

SSandyWu7179290504

88% match

Loading thumbnail…

Data

This example presents an interactive scatter plot of Spotify song attributes, allowing users to compare musical features such as Tempo, Energy, and Danceability across tracks from 2010 to 2020. A year slider filters the dataset, while dropdown menus let users select which attributes to plot on the x- and y-axes and which categorical field, either Top Genre or Artist, to use for color encoding. The visualization is built with React, using D3 v6 and v5 APIs including `scaleLinear` and `scaleOrdinal` for axes and color, alongside ReactDropdown for menu selection, and it renders SVG circles with native tooltips. Data is loaded via `d3.csv` from a GitHub gist containing the yearly music trend dataset.

Nnikki81140

87% match

Loading thumbnail…

Yearly Top Genre Trend and Artist with Music Signature

This interactive scatter plot explores how the top 20 Spotify songs in the U.S. vary by year from 2010–2019. A slider selects the year, while dropdown menus choose which musical features (Tempo, Energy, Loudness, etc.) map to the x- and y-axes and whether points are colored by top genre or artist. Users can hover over the color legend to highlight a specific category or hover over a point to see its song details. The visualization is built with React and D3 v5, using SVG scales like `scaleLinear` and `scaleOrdinal` and components for axes, marks, and dropdowns. Data comes from a CSV hosted on GitHub.

ZZiyang Gao

86% match

Loading thumbnail…

Fork of Basic Scatter Plot with React & D3

A scatter plot visualizes the musical characteristics of Spotify's top songs from 2010 to 2019, positioning each track by its danceability and energy scores while sizing circles by popularity. A categorical color scale distinguishes genres, with a legend identifying the ten genre categories. The React app uses D3's `csv` loader to parse song attributes from a local CSV file, then leverages D3's `scaleLinear`, `axisBottom`, and `axisLeft` to construct the chart and its axes.

VVinayak Revankar

83% match

Loading thumbnail…

Spotify_Interactive Polished Scatter Plot_two_track_genre

This interactive scatter plot explores Spotify track attributes, such as danceability, energy, and popularity, across two selectable musical genres. Users can choose attributes from dropdown menus to define the x- and y-axes, and hover over points to see the artist and track name. Circle colors encode the track genre. Built with React, the visualization uses D3 for scales, axes, and the color legend, rendering as SVG.

Sstephanie0215

83% match

Loading thumbnail…

Spotify_Interactive Polished Scatter Plot with Menus and Colors and Color Legend

This interactive scatter plot visualizes a Spotify song dataset, mapping selected audio features like danceability, energy, and popularity against each other on the X and Y axes. A color legend and dropdown menus allow users to switch the categories and attributes being compared, while hovering over legend items fades unrelated data points. The visualization is built with React and D3 v7, using SVG for rendering, and includes filtering capabilities to narrow the data by a popularity range.

Sstephanie0215

83% match

Loading thumbnail…

Top 100 Songs w/ Menus & Color Legends

This interactive scatterplot shows relationships between musical attributes of Spotify’s top 100 songs of 2018. Users can select any attribute—such as duration, energy, danceability, or tempo—for the x- and y-axes using React dropdown menus. Point color encodes each track’s mode (major or minor) via a d3.scaleOrdinal color legend. The visualization is built with React and renders as SVG using d3.scaleLinear for axes and custom React components for marks, axes, and legends. Data comes from a CSV file fetched with d3.csv.

Ssamemurk21

83% match