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Customizing Axes

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Ttracy3057
Last edited Jun 15, 2021
Created on Dec 5, 2020
Forked from Customizing Axes

This example shows a bar chart of employment numbers across occupations in New York City, with interactive year buttons (2010–2019) that update the displayed data. The visualization uses d3.v6 with SVG rendering and animation. Axes are customized using `d3.axisLeft` and `d3.axisBottom`, with a linear scale for the x-axis and a band scale for the y-axis. Clicking a year button triggers a redraw of the chart via inline CSV data, highlighting the selected year in blue.

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Customizing Axes

An interactive bar chart displays employment counts across occupations in New York City for each year from 2010 to 2019, using data from CSV files. Users click year buttons to update the visualization. The chart employs D3 v5’s `scaleBand` and `scaleLinear`, along with `axisBottom` and `axisLeft`, which are customized with tick formatting and removed gridlines. Transitions animate bar updates, while SVG rendering shows the data. The axes are styled per the CSS, and the title reads "Number of Employed in NYC."

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This interactive bar chart shows the number of people employed in New York City across various occupations for each year from 2010 to 2019. Users click year buttons to update the visualization, which animates bar widths and the y-axis with smooth transitions. The chart uses D3 v6 APIs including `scaleLinear`, `scaleBand`, `axisLeft`, and `axisBottom`, along with `transition` methods for the animation. Data is loaded from CSV files containing occupation and employment figures per year.

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This example shows how to customize axes in D3.js v5 by displaying the number of employed people across various occupations in New York City from 2010 to 2019. Users click year buttons to update the bar chart, which animates transitions between datasets using `transition.attr` and `transition.duration`. The code uses `scaleLinear`, `scaleBand`, `axisLeft`, and `axisBottom` with custom tick formatting via `format`. Data is loaded from CSV files, and the visualization renders as SVG rectangles with a steelblue fill.

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