Skip to main content
SimilarExport ZIP
100%

Melting Data for Multiple Lines

✓ Published1🌍 Public
HHasideluxe
Last edited Aug 7, 2020
Created on Aug 3, 2020

This visualization shows population trends over time for various global regions, with each region represented by a colored line and a corresponding legend. The data comes from UN population estimates and projections, spanning 1950 to 2100. Built with D3 v5, the code melts wide-format CSV data into tidy rows using a custom function before applying scales, axes, and a line generator with curveBasis interpolation. Regions are sorted by their final population value and colored using d3.scaleOrdinal with schemeCategory10.

AI-generated description
MIT Licensed

Similar vizzes

Loading thumbnail…

Melting data for multiple lines

This visualization shows population trends over time for global regions, with each region drawn as a separate colored line and a legend identifying the regions. The data comes from UN population estimates (1950–2014) and medium-variant projections (2015–2100), melted into tidy format. The code uses d3.csv, d3.nest, d3.scaleTime, d3.scaleLinear, d3.scaleOrdinal, d3.line with curveBasis, and d3.axisLeft/axisBottom. A custom colorLegend module renders the legend, while SVG paths with mix-blend-mode multiply display overlapping lines.

Jjlongwellchc
96% match
Loading thumbnail…

Melting Data for Multiple Lines

This visualization shows population trends over time for global regions, displaying multiple lines on a chart with a color-coded legend. The data is sourced from UN population estimates and projections, spanning from 1950 to 2100. The code uses d3.csv and d3.nest to process and group the data, while d3.line with curveBasis generates the smooth paths. Color is assigned via d3.scaleOrdinal with schemeCategory10, and the chart includes axes rendered with d3.axisBottom and d3.axisLeft, with a custom color legend component for identifying each region.

Yyoyo2050
96% match
Loading thumbnail…

Melting Data for Multiple Lines

This visualization shows population trends over time for regions, displaying multiple lines that trace changes from 1950 to 2100. The data is sourced from UN population estimates and medium variant projections, processed through a melting operation that converts wide-format data into long format. The chart uses D3.js v5 APIs including `scaleTime`, `scaleLinear`, `scaleOrdinal`, `line` with `curveBasis` for smooth paths, and `nest` for grouping by region. An ordinal color scale with `schemeCategory10` assigns colors, while a custom legend shows region names.

Ssteveaigbe
95% match
Loading thumbnail…

Melting Data for Multiple Lines

This visualization displays population trends over time by region, using multiple colored lines to represent different countries from 1950 to 2100. The chart employs d3.line with curveBasis for smooth paths, d3.scaleTime and d3.scaleLinear for axes, and d3.nest to group data by country. A custom colorLegend component renders the categorical scale using d3.scaleOrdinal with schemeCategory10. The data comes from UN population estimates, processed through a custom melt function that transforms wide-format CSV data into tidy rows. SVG rendering handles the visualization, with axis labels and a title annotating the chart.

PPotikorn
95% match
Loading thumbnail…

Melting Data for Multiple Lines

This visualization shows population trends over time for global regions, with each region represented as a colored line. The chart uses multiple lines to compare regional population growth from 1950 to 2100, with a color legend on the right side. The code processes United Nations population data by melting it into a tidy format, then uses d3.line with curveBasis to generate smooth paths, d3.nest to group by region, and d3.scaleOrdinal with schemeCategory10 for colors. Axes are rendered using d3.axisLeft and d3.axisBottom, with SVG rendering and custom tick formatting for population values.

CChenluWang96
95% match
Loading thumbnail…

Melting Data for Multiple Lines

This visualization displays population trends over time for various global regions, with each region represented as a distinct colored line. The chart highlights how populations evolve from 1950 to 2100, combining historical estimates with medium-variant projections. The code uses d3.nest to group data by region, d3.line with curveBasis for smooth paths, and d3.scaleOrdinal with schemeCategory10 for colors. A custom colorLegend component renders the interactive legend, while data processing in loadAndProcessData.js melts the CSV dataset into a tidy format using d3.range and timeParse.

Vvic126
95% match
Loading thumbnail…

Melting Data for Multiple Lines

This example shows population trends over time by region, with each region represented as a separate colored line. The visualization uses D3 v5 to load and process UN population estimates from CSV files, then melts the data into a tidy format using custom logic. Multiple lines are rendered with d3.line and curveBasis, while an ordinal color scale with a legend distinguishes regions. Axes are drawn using d3.axisBottom and d3.axisLeft, and the chart updates based on nested data sorted by final population values.

Jjbruzzo
95% match
Loading thumbnail…

Melting Data for Multiple Lines

This visualization displays population trends over time for various world regions using multiple lines. The chart combines historical estimates from a 2017 UN dataset with medium-variant projections through 2100, showing each region’s population trajectory in a distinct color. The code uses d3.csv to load data, d3.nest to group by region, d3.line with curveBasis for smooth paths, and d3.scaleTime and d3.scaleLinear for axes. A custom colorLegend component renders the categorical scale, while d3.axisLeft and d3.axisBottom create labeled tick marks.

Ffbudwill
95% match