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Takuya Kitazawa

@takuti·13 public vizzes

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Choropleth map

A choropleth map visualizes the global prevalence of HIV/AIDS among adults aged 15-49 in 2017, with countries colored on a yellow-orange-red sequential scale using d3.scaleSequential and interpolateYlOrRd. Gray marks indicate missing data. The visualization uses d3.geoNaturalEarth1 and d3.geoPath to render SVG paths from TopoJSON world atlas data, with country codes matched to CSV data from the IHME via ISO numeric codes. React manages the component lifecycle, loading data asynchronously through custom hooks.

Jan 17, 2021
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Missing migrants on a map

This interactive visualization combines a bubble map of missing migrants with a time-series histogram. The map uses `d3.geoNaturalEarth1` and `d3.geoPath` to render landmasses, with circle radii scaled by the square root of the total dead and missing count via `d3.scaleSqrt`. The histogram below, built with `d3.scaleTime`, `d3.scaleLinear`, and `d3.histogram`, displays monthly totals and supports brushing (`d3.brushX`) to filter the map by date range. Data is loaded from a CSV using `d3.csv`.

Jan 16, 2021
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Migrant death

This visualization displays the monthly count of migrant deaths using a histogram. The bar chart uses React to render SVG rectangles, with D3 scales for time and linear axes. Data comes from the Missing Migrants Global dataset, processed with `d3.csv` and binned by month using `d3.histogram`. The code uses `scaleTime`, `scaleLinear`, and `timeMonths` to define the bins, with tooltips showing exact death totals via SVG `<title>` elements.

Jan 15, 2021
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World map

This world map visualizes global city populations, with semi-transparent circles sized by population using a square-root scale. A Natural Earth projection draws the landmasses, graticule, and country borders via D3's `geoNaturalEarth1` and `geoPath`, while city coordinates are projected and rendered as SVG circles. The map loads geographic data from World Atlas TopoJSON and population data from a CSV, using `topojson.feature` and `topojson.mesh` to construct the land and interior boundaries.

Jan 15, 2021
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Scatter plot with menus

This scatter plot of the Iris dataset displays the relationships between flower measurements, with interactive dropdown menus to select the attributes for the x and y axes. The chart shows all data points colored by species, and hovering over the color legend highlights a single species while fading the others. Built with React and D3, the visualization uses `d3.scaleLinear`, `d3.scaleOrdinal`, and `d3.extent` for scales and domains, while custom React components render SVG axes, circles, and the legend.

Jan 14, 2021
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Line chart

This line chart displays temperature readings over a week, sampled from San Francisco weather data loaded via d3.csv. The React components render an SVG with time-scaled x-axis and linear y-axis, using d3.scaleTime, d3.scaleLinear, and d3.extent for domains. Data points appear as circles, connected by a smooth path generated with d3.line and curveNatural. Axes are custom React components that map tick values from d3 scales, with the y-axis labels formatted using d3.timeFormat.

Jan 14, 2021
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Scatter plot

This scatter plot displays the relationship between petal length and sepal width in the Iris dataset, rendering each flower as a teal circle. The visualization uses React components to structure the SVG output, while D3.js provides the scaleLinear functions for mapping data values to pixel coordinates. Axis components generate tick marks and labels, with text elements annotating both axes. Data is loaded asynchronously from a remote CSV file, and the plot updates once the dataset arrives.

Jan 13, 2021
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Bar chart

This bar chart displays the populations of ten countries in 2020, sorted by country name. Using React and D3 v5, it renders SVG rectangles via a scaleBand for the categorical y-axis and a scaleLinear for the numerical x-axis. The data loads from a CSV via d3.csv. Axes are custom components, and hover tooltips use native SVG `<title>` elements with formatted population values.

Jan 13, 2021
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Loading data with React & d3

This example shows a pie chart of CSS named colors rendered as SVG, where each slice represents one color from a CSV dataset loaded from a GitHub gist. Using React state, the `useEffect` hook triggers `d3.csv` to fetch the data, and conditional rendering displays a loading message until the data arrives. The `d3.pie` and `d3.arc` functions compute the pie layout, with each colored path fill derived from the hex value column. The dataset contains 148 color rows with columns for name and RGB hex value.

Jan 13, 2021
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Fork of Vega-Lite API Template

This example visualizes automotive data from a CSV file, plotting horsepower and weight for each car as circles, with color indicating origin and size encoding miles per gallon. It uses the Vega-Lite API to build the chart declaratively, with D3’s `csv` function for data loading. The visualization leverages vega-lite-api’s `markCircle` and `encode` methods, and it renders SVG output through Vega, vega-lite, and vega-tooltip for interactive tooltips.

Jan 12, 2021
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Mouse Follower

A full-window SVG circles a crosshair that tracks the mouse cursor. A React component uses the `useState` and `useCallback` hooks to store and update the pointer's `clientX` and `clientY` coordinates on every `onMouseMove` event. The circle’s center position is bound directly to these state values, and React re-renders the SVG element instantaneously as the user moves the mouse.

Jan 12, 2021
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Fork of Loading and Parsing CSV Data

This visualization demonstrates the size and structure of a CSV dataset containing CSS named colors. It displays the file size in kilobytes, the number of rows, and the number of columns in a large text readout. The code fetches the remote CSV file using `d3.csv`, then calculates the formatted byte count with `d3.csvFormat` and accesses the parsed data’s length and column information. The example also includes commented-out alternatives using `fetch`, async/await, and `d3.csvParse` to show different parsing workflows.

Jan 12, 2021
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Fork of Hello HTML

A grid of 18 randomly generated smiley faces is rendered on an SVG canvas. Each face is composed of React components: a yellow background circle, two eyes, and a mouth drawn with a D3 arc path. The `index.js` file uses ReactDOM to render the faces, while `d3.range` generates the grid and `Math.random()` varies facial features like eye offset, radius, and mouth width, producing a playful, non-repeating pattern.

Jan 11, 2021