Heat Map

100%

✓ Published0🌍 Public

Last edited Feb 6, 2022

Created on Feb 5, 2022

This heat map visualizes the average Uber fare amount for different passenger counts across the years 2009 to 2015, with color intensity indicating fare value (green shades for $9–13+) and a toggleable overlay that reveals exact dollar amounts. Built with the p5.js library, it loads a CSV dataset, aggregates fare averages per year and passenger count, and renders colored rectangles in a grid using the `rect` and `fill` functions. A legend on the right maps colors to fare ranges, while axis labels clarify that rows represent years and columns represent passenger counts.

AI-generated description

MIT Licensed

Similar vizzes

Loading thumbnail…

Bar Chart

This bar chart visualizes the total Uber fare amount per year, drawing on a CSV dataset of ride records. The visualization excludes 2008 data and sums the fares for each remaining year, displaying the results as a series of teal bars. The chart is rendered using the p5.js library, which loads the data with `loadTable`, processes it within the `draw` loop, and creates the visual elements. Custom functions like `kFormatter` are used to format large numbers with a "k" suffix on the y-axis, which is labeled "Fare Amount."

DDominic Fernandez

81% match

Loading thumbnail…

D3 Heatmap

This heatmap visualizes the number of Uber rides per month and year, with months on the x-axis, years on the y-axis, and color intensity encoding ride counts. It uses d3.csv to load the dataset, d3.scaleBand for both axes, and d3.scaleSequential with a color interpolator to map counts to cell colors. The SVG is rendered with d3.axisBottom and d3.axisLeft, while cells are drawn as rects. Data is aggregated client-side by parsing timestamps into month-year pairs.

DDominic Fernandez

80% match

Loading thumbnail…

D3 Scatterplot

This interactive D3 scatterplot visualizes cumulative Uber fare amounts per day from 2009 to 2015, using data from a Kaggle dataset. The SVG chart plots each date on the x-axis and total daily fares on the y-axis, with green circles marking individual points. The visualization uses `d3.csv` to load the raw data, `d3.scaleBand` for the time-based x-axis, and `d3.scaleLinear` for the fare amounts. Custom tick marks highlight the first date of each year, while gridlines and labeled axes improve readability.

DDominic Fernandez

77% match

Loading thumbnail…

Dot Plot

This dot plot shows the number of Uber rides per year, with each circle representing a year’s total ride count positioned along a horizontal axis scaled by increments of 2,000 rides. The visualization aggregates data from a CSV file loaded via p5.js’s `loadTable` function, then uses `createCanvas` and `circle` to render the points. Year labels appear along a vertical axis, and ride counts are formatted using a custom `kFormatter` function for values above 1,000. The plot excludes 2008 data and displays results across a 625×625 pixel canvas.

DDominic Fernandez

75% match

Loading thumbnail…

All Uber Trips in NYC from 08/01/2014 to 08/14/2014

This visualization displays basic metadata about all Uber trips in New York City from August 1–14, 2014, reporting the file size in kilobytes, row count, and column count of the source dataset. The page loads a CSV from the FiveThirtyEight GitHub repository using `d3.csv` and then uses `d3.csvFormat` to calculate the raw data size, while reading `data.length` and `data.columns.length` to summarize the table. The results are rendered as large text in a `<pre>` element, with no graphical chart or map shown. The example demonstrates straightforward CSV loading and summary reporting with D3 v5.

Llokesh234

67% match

Loading thumbnail…

HeatMap

A heat map of temperature data for ten cities across the months of 2016, rendered as an interactive grid of colored squares using the p5.js `loadTable` API to fetch a CSV from a GitHub Gist. Each cell encodes average temperature through color saturation—cooler temperatures appear darker—while hovering over a cell displays its exact value. The visualization includes manual axis labels, a temperature color scale legend, and city names positioned along the left edge.

AAllen Ho

66% match

Loading thumbnail…

Yearly Region-Wise Air Passenger Heatmap

This heatmap visualization displays the total air passenger counts for various global regions across time, from 2005 to 2019. It aggregates the data by region and year, using a Viridis color scale to encode the passenger volumes. The visualization is rendered as an SVG graphic using D3.js v5, with axes for years and regions. It relies on D3’s scale functions and a nested data grouping API to structure the dataset, sourced from DataSF’s Air Traffic Passenger Statistics.

NNikhil Bhutani

66% match

Loading thumbnail…

q3

This interactive scatter plot visualizes New York City taxi trip data, showing trip distance against pickup hour. Each circle represents a trip, colored by the day of the week, with a color legend that filters data on hover. The visualization uses React with D3 scales (`scaleLinear`, `scaleOrdinal`) to render SVG elements. The `csv` loader fetches data from a remote gist, while interactive hovering triggers opacity fading for non-selected categories.

UUmarani Vemula

65% match