Fork of 1116 of HW3 Loading and Parsing CSV Data

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Fork of 1116 of HW3 Loading and Parsing CSV Data

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Last edited Nov 16, 2022

Created on Nov 16, 2022

Forked from 1116 of HW3 Loading and Parsing CSV Data

This example displays a scatter plot of Spotify track data, separating songs into two groups based on whether their popularity score exceeds 33, with energy values plotted on both axes. It loads a CSV file from a GitHub Gist using Plotly.js's `Plotly.d3.csv` method, then processes the rows in JavaScript to filter and extract the energy values. The visualization renders the two series as separate traces in a single `Plotly.newPlot` chart, titled "Plotting CSV data from AJAX call," demonstrating CSV parsing and conditional data filtering within a React framework.

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A program that loads and parses some CSV data: CSS Named Colors.

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Fork2 of 1116 of HW3 Loading and Parsing CSV Data

This example visualizes Spotify track data by comparing the distribution of energy levels between songs with high popularity (>33) and low popularity (<33). The visualization uses grouped bar and line charts to show counts of tracks across five energy bins, from 0 to 1. The code loads CSV data via Plotly.d3.csv, processes it with conditional logic, and renders the results using Plotly.newPlot with both bar and scatter traces. The Spotify dataset is fetched from a GitHub gist URL, and the chart displays two distinct series for popularity comparison.

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This example visualizes the distribution of Spotify track energy for tracks grouped by popularity, comparing tracks with popularity above and below 33. It loads a CSV dataset using Plotly’s `d3.csv`, then processes the rows by binning energy values into five ranges and normalizing the counts as proportions. The resulting bar and line traces for both groups are rendered in a single Plotly chart using `Plotly.newPlot`, with the CSV fetched via an AJAX call from a GitHub gist URL.

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