Skip to main content
SimilarExport ZIP
100%

Melting Data for Multiple Lines

✓ Published1🌍 Public
Ffbudwill
Last edited Jun 24, 2020
Created on Jun 24, 2020

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.

AI-generated description
MIT Licensed

Similar vizzes

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
97% 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
96% match
Loading thumbnail…

Melting Data for Multiple Lines

This visualization shows population trends over time for different global regions, with multiple lines plotted on a time-series chart. The legend and color scale indicate which line corresponds to which region. The code uses d3.csv to load UN population 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 module renders the interactive legend using SVG circles and text.

SSatish Chandra Gupta
96% 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
96% match
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 example visualizes population over time by region, showing six major world regions as distinct colored lines from 1950 to 2100. The chart uses a line generator with curveBasis for smooth paths, while a color legend identifies each region. The code melts wide-format UN population data into tidy rows, combining estimates and medium-variant projections from CSV files. It employs d3.scaleTime, d3.scaleLinear, d3.scaleOrdinal, d3.nest, and d3.axisBottom/axisLeft, rendering as SVG with custom tick formatting for abbreviated population values.

Ppplomith
96% 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