Missing migrants multiple views

100%

Missing migrants multiple views

✓ Published0🌍 Public

Last edited May 9, 2021

Created on May 8, 2021

This visualization presents multiple views of missing migrant data from a global 2021 dataset. A world map using a natural Earth projection displays circles scaled by the square root of total dead and missing per location, with tooltips showing exact counts. Below, a date histogram bins reported deaths monthly, stacking totals by time. Built with React and D3 v6, the map uses `geoNaturalEarth1`, `geoPath`, and `geoGraticule` for geographic rendering, while the histogram employs `bin`, `scaleTime`, `scaleLinear`, and `scaleSqrt` for aggregation and scaling. SVG renders all marks, with the world atlas sourced from TopoJSON.

AI-generated description

Scatter plot of temperature dataset using d3 and keeps track using react

MIT Licensed

Similar vizzes

Loading thumbnail…

Missing Migrants multiple views

This visualization presents data on missing migrants through two coordinated views. A world map uses circles scaled by the square root of the count of dead and missing individuals, projecting geographic coordinates with `d3.geoNaturalEarth1` and `d3.geoPath`. A time-series histogram below displays the monthly sum of deaths, binned using `d3.histogram` with `d3.timeMonths` thresholds, using `d3.scaleTime` and `d3.scaleLinear` for axes. The data comes from the Missing Migrants Project, and the React-based build relies on `d3.json` and `topojson` features.

Wwindwaver

94% match

Loading thumbnail…

Missing Migrants - Multiple Views

This interactive visualization combines two coordinated views of missing migrant incidents. A world map uses a natural Earth projection with graticules to display incident locations, with circle sizes scaled by the square root of deaths and missing persons. Below, a time-series histogram bins reported dates into monthly intervals, summing the total dead and missing per month. The map is rendered using d3.geoPath and d3.geoNaturalEarth1, while the histogram leverages d3.bin, d3.scaleTime, and d3.scaleLinear. Data comes from the Missing Migrants Project CSV, loaded with d3.csv, with geographic boundaries from world-atlas TopoJSON.

PPeter Krevenets

94% match

Loading thumbnail…

Missing Migrants with Multiple Views

This interactive visualization presents data on missing migrants through two linked views. A world map displays the geographic distribution of deaths and disappearances using proportional circles, with bubble size scaled according to the total count per location. Below, a time-based histogram aggregates the same data by month, showing the cumulative number of missing migrants over time. Both views use D3 v5 with React, employing `geoNaturalEarth1` projection for the map, `scaleSqrt` for circle sizing, and `histogram` binning for the temporal view. The data comes from CSV files loaded via `d3.csv`, with the map drawing from World Atlas TopoJSON.

Ppnlinyz

93% match

Loading thumbnail…

Missing Migrants - multiple views

This visualization presents the Missing Migrants dataset through two synchronized views: a world map using a bubble chart and a time-series histogram. The map displays circles scaled by the square root of the total dead and missing per location, projected using `geoNaturalEarth1` and `geoPath`. The histogram bins reported dates by month using `d3.bin` and `timeMonths`, summing fatalities per bin. Both views are rendered with SVG via React components, leveraging D3 scales and axes. Data is loaded from a CSV using `d3.csv`.

SSai Phaltankar

93% match

Loading thumbnail…

Missing Migrants: Multiple Views

This visualization displays global migrant mortality events using two coordinated views: a natural Earth projection bubble map and a time-series histogram. The map positions each event as a semi-transparent circle scaled by the square root of the total dead and missing, while the histogram aggregates monthly totals. Both views use React and D3 v5, with `d3.geoNaturalEarth1` and `d3.geoPath` for map rendering and `d3.histogram` for binning. Data comes from the Missing Migrants Project CSV, with country boundaries from World Atlas TopoJSON.

RRiccardo De Lucia

93% match

Loading thumbnail…

34. Missing Migrants Multiple Views

This visualization combines a world map with a time-series bar chart to display data on missing migrants. The map uses a natural Earth projection with sized circles to show total deaths and missing persons by location, while the histogram aggregates the same metric by reported date. Built with React and D3 v5, the example employs `geoNaturalEarth1` for projection, `scaleSqrt` for circle sizing, and `bin` with `timeMonths` thresholds for the histogram. Data comes from the Missing Migrants Project CSV, with country boundaries from World Atlas TopoJSON.

PPrashish Paudel

93% match

Loading thumbnail…

Missing Migrants Multiple Views

This interactive visualization presents missing migrant incidents on a world map with proportional bubbles, alongside a time-series histogram of monthly deaths. The React-based interface renders geographic data using `d3.geoNaturalEarth1`, `d3.geoPath`, and `d3.geoGraticule`, with bubble sizes scaled via `d3.scaleSqrt`. The histogram bins reported dates by month using `d3.histogram` and `d3.timeMonths`. Both views display data from a CSV of Missing Migrants Project records, loaded with `d3.csv` and overlaid on a World Atlas TopoJSON basemap.

Jjwlam83

93% match

Loading thumbnail…

Missing Migrants Multiple Views

This visualization presents recorded incidents of missing migrants through two coordinated views. A bubble map uses a natural Earth projection with graticules to plot incident locations, where circle size encodes the total dead and missing count via a square-root scale. Below, a histogram bins incidents by reported date, summing casualties within monthly intervals. Both views render as SVG using React components and D3 v5 APIs, including `geoNaturalEarth1`, `geoPath`, `scaleSqrt`, `scaleTime`, and `histogram`. Data comes from a CSV of global missing migrant incidents, while country boundaries come from the world-atlas TopoJSON dataset.

Nnpelliccia

93% match