Chris Mora

@cmora09·7 public vizzes

Covid-19 Time Series: Total Number of Cases Worldwide Since 01/02/22

This visualization displays the cumulative number of COVID-19 cases worldwide on a Mercator projection map, with each country represented by an orange circle whose radius scales with case count. A date slider lets users scrub through time from January 22, 2020, with circles updating via d3 transitions. Built with D3 v5, it uses d3.geoPath, d3.geoMercator, d3.scaleSqrt, and d3-zoom for interactivity. Hovering reveals tooltips with region and case totals. Data comes from Johns Hopkins via the Humanitarian Data Exchange, rendered as SVG with smooth animations.

Apr 15, 2020

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Covid-19

The visualization maps COVID-19 case counts per country on a world map using SVG circles, with circle radius scaled proportionally to the number of cases on March 25, 2020. It displays data from the Humanitarian Data Exchange, sourced from a CSV file containing daily case numbers since January 22, 2020. The map uses D3 v5’s `geoMercator` projection, `geoPath` to draw country boundaries, and `scaleSqrt` for radius scaling. A range slider is present, though the displayed date label shows placeholder text.

Apr 3, 2020

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Scatter plot

This scatter plot visualizes the relationship between MPG and horsepower using the auto-mpg dataset. Each circle represents a vehicle, positioned by linear scales created with `d3.scaleLinear` and `d3.extent`, with axes generated via `d3.axisBottom` and `d3.axisLeft`. The SVG chart animates circle appearance using `d3.transition` with easeLinear. Data is loaded as CSV and parsed into numbers, with axis labels and gridlines styled through CSS classes.

Mar 31, 2020

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Basic Map

This example displays a basic world map using an SVG canvas, rendering country boundaries with a Mercator projection. It loads geographic data from the `world-atlas` package via a JSON file and converts it into map features using the `topojson` library's `feature` function. The map is drawn with D3 v5's `geoPath` and `geoMercator` APIs, which generate the SVG path data for each country. The visualization is straightforward, showing only the landmasses without additional styling or interactivity.

Mar 30, 2020

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Scatter plot

A scatter plot displays the population of the top 10 most populous countries, with circles positioned along a linear population scale and a point scale for country names. The visualization uses d3.csv to load data, d3.scaleLinear for the x-axis, d3.scalePoint for the y-axis, and d3.axisBottom with a custom tick format converting G to B. Circles appear with a 1000ms d3.transition using easeLinear, rendered as SVG elements with steelblue-to-gray color scaling based on population values.

Mar 30, 2020

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Bar chart

This animated bar chart displays the populations of the ten most populous countries, using horizontal bars colored on a linear scale from orange to brown. The visualization loads data from a CSV file and multiplies each population value by 1,000 for display. Built with D3 v5, it uses `scaleLinear` for the x-axis and population-based coloring, `scaleBand` for the y-axis categories, and `axisBottom` with tick formatting that abbreviates large numbers. Bars animate in over one second using `transition` with `easeLinear`, while SVG renders all elements.

Mar 30, 2020

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D3 intro

This example renders a smiling face using D3 v5 and React, with SVG elements including circles, rectangles, and paths. The face is centered on the screen, and the eyebrows animate upward and downward using chained `transition()` calls with a two-second duration each. The code leverages D3’s `select`, `arc`, and `line` APIs to construct the mouth and nose shapes, while static SVG attributes define the eyes and overall composition. The visualization demonstrates basic SVG drawing and animation within a React framework.

Mar 29, 2020