Fork of Cars Scatter Plot

Cars Scatter Plot

This scatter plot displays self-reported life satisfaction across the world from 2004 to 2016, mapping each country’s Happiness Rank against the year. The visualization uses D3 v5’s `scaleTime` and `scaleLinear` to position orange, semi-transparent circles within an SVG, with `axisBottom` and `axisLeft` providing labeled axes. Data is loaded via `d3.csv` from a modified World Happiness Report 2017 dataset hosted on VizHub, and the chart includes gridlines and a title annotation.

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Fork of Stylized Scatter Plot

This interactive scatter plot displays country-level well-being indicators, with happiness score on the x-axis and a selectable y-axis metric (economy, social support, generosity, freedom, or corruption). Each circle represents a country, with an HTML `<title>` tooltip showing its exact happiness score. The React-based visualization uses D3 v5 scales (`scaleLinear`), axes (`AxisBottom`, `AxisLeft`), and CSV data loading (`d3.csv`) from a GitHub gist. Users switch the y-axis via a dropdown, triggering React state updates that re-render the SVG marks.

NNikithakatta30

81% match

Cars Scatter Plot

This scatter plot shows the relationship between year and happiness rank for self-reported life satisfaction across the world from 2004 to 2016, with each orange circle representing a data point. The visualization uses D3 v5’s `scaleTime` and `scaleLinear` to map the temporal and ranked variables, while `axisBottom` and `axisLeft` generate the labeled axes with gridlines. The code loads CSV data from a VizHub dataset based on the World Happiness Report 2017 and renders the plot as SVG elements, with semi-transparent circles to reveal overlapping points.

Cars Scatter Plot

This scatter plot shows the relationship between year and happiness rank for self-reported life satisfaction across the world from 2004 to 2016, with each orange circle representing a data point. The visualization uses D3 v5’s `scaleTime` and `scaleLinear` to map the temporal and ranked variables, while `axisBottom` and `axisLeft` generate the labeled axes with gridlines. The code loads CSV data from a VizHub dataset based on the World Happiness Report 2017 and renders the plot as SVG elements, with semi-transparent circles to reveal overlapping points.

Cars Scatter Plot

This scatter plot shows the relationship between year and happiness rank for self-reported life satisfaction across the world from 2004 to 2016, with each orange circle representing a data point. The visualization uses D3 v5’s `scaleTime` and `scaleLinear` to map the temporal and ranked variables, while `axisBottom` and `axisLeft` generate the labeled axes with gridlines. The code loads CSV data from a VizHub dataset based on the World Happiness Report 2017 and renders the plot as SVG elements, with semi-transparent circles to reveal overlapping points.

Cars Scatter Plot

This scatter plot shows the relationship between year and happiness rank for self-reported life satisfaction across the world from 2004 to 2016, with each orange circle representing a data point. The visualization uses D3 v5’s `scaleTime` and `scaleLinear` to map the temporal and ranked variables, while `axisBottom` and `axisLeft` generate the labeled axes with gridlines. The code loads CSV data from a VizHub dataset based on the World Happiness Report 2017 and renders the plot as SVG elements, with semi-transparent circles to reveal overlapping points.

Cars Scatter Plot

This scatter plot visualizes the relationship between family and freedom scores in the 2017 World Happiness Report, sourced from the UCI Machine Learning Repository’s Auto MPG dataset. Each green semi-transparent circle represents a country, with axes labeled “family” and “freedom” and a title noting horsepower versus weight. The code uses d3.csv to load data, d3.scaleLinear with d3.extent for scaling, and d3.axisLeft and d3.axisBottom for axes. It renders circles as SVG elements, with tick lines, axis labels, and a title styled via CSS.

NNTCHANG1289