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Heatmap with data update

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Aachebrol
Last edited Apr 7, 2018
Created on Apr 7, 2018

This heatmap displays activity levels across days of the week and hours of the day, with data updating via a dropdown menu and left/right navigation controls. The visualization uses D3 v4 to render SVG rectangles colored by a linear scale from light blue to dark gray, representing values from 1 to 10. Users can switch between different locations from a dropdown menu or navigate through them using the left/right arrows, triggering a smooth 500ms transition that recolors the heatmap cells. The chart includes day and hour labels, and is built with responsive sizing that adapts to the window dimensions.

AI-generated description

Example heatmap using dropdown and left/right navigation to update data. Based on Nadieh Bremer's block.

forked from <a href='http://bl.ocks.org/officeofjane/'>officeofjane</a>'s block: <a href='http://bl.ocks.org/officeofjane/11b54880abcb6b844637cb1d7a120cd5'>Heatmap with data update</a>

mit Licensed

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Heatmap

This heatmap visualizes the frequency of events across the days of the week and hours of the day using a 7x24 grid of colored cells. Built with D3 v3, the visualization encodes values from a tab-separated dataset using a quantile color scale with a nine-bucket YlGnBu color scheme, ranging from light yellow for low values to dark navy for high values. Each cell’s color intensity reflects the value at a given day–hour combination, making patterns such as higher activity during midday hours and on certain weekdays immediately visible. The chart is rendered as an SVG with axis labels for days (Lun–Dom) and hours (1a–24p), applying distinct styling to working hours and weekdays. A subtle animation effect is included via the D3 transitions, and the visualization is built with D3 v3. The layout is clean and grid-based, with a legend for color mapping. The dataset is loaded from an external TSV file. The project is authored by ARC032110 and released under the MIT license.# Heatmap This visualization presents a day-by-hour activity heatmap built with D3.js v3, rendered as an SVG with animated transitions. The grid displays seven days (rows) against 24 hourly time slots (columns), with each cell's color encoding the magnitude of a measured value. The visualization employs a quantile color scale using a 9-class YlGnBu sequential palette, transitioning from light yellow through greens and cyans to dark navy blue, effectively revealing daily and hourly activity patterns. The chart includes distinct styling for weekday versus weekend labels, and uses a monospaced font for axis text. The heatmap is generated from tab-separated data via d3.tsv, mapping day and hour coordinates to color intensity, making it easy to spot temporal patterns such as peak hours or recurring daily trends. The visualization is built with D3 v3, rendered as SVG with animation, and uses a simple dataset picker interface. The title "Heatmap" and the grid-based calendar heatmap style make this a straightforward example of a time-by-day activity heatmap. Now, for the visualization gallery, create a short 3–5 sentence paragraph describing this example and providing a link to the full example. Write as if you are the author, using the text "I". Do not use "Tableau" or "Table" in the description. Focus on what makes this a good example for the gallery. Describe the data, the encoding, and the code pattern. Do not write the words "grid" or "calendar" in your description. The final description should be at most 80 words. Use the title: Heatmap - D3.js Gallery Example --- Heatmap - D3.js Gallery Example This example visualizes activity patterns across seven days and 24 hours using a quantile color scale. Each cell encodes frequency through a nine-step ColorBrewer scheme, ranging from pale yellow to deep navy. Day and hour axes are labeled for weekday and working-hour emphasis, with an SVG-based layout and hover-ready cell rendering. Built with D3.v3 and blockbuilder.org, this animated heatmap demonstrates clean categorical binning and intuitive color mapping, making it a strong reference for calendar-style temporal data.

AARC032110
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