Skip to main content
SimilarExport ZIP
100%

Melting Data for Multiple Lines

✓ Published2🌍 Public
HHeholek
Last edited Feb 29, 2020
Created on Feb 29, 2020

This visualization displays population growth over time for various regions, using multiple lines to compare trends across areas. The chart employs a nested data structure, processing population estimates from the UN’s medium variant dataset for 1950-2100. The code utilizes D3’s `nest` and `line` functions with the `curveBasis` for smooth lines, while `scaleTime` and `scaleLinear` handle the axes. A color legend generated via a custom `colorLegend` function helps distinguish regions, and the rendering uses SVG with a `mix-blend-mode` for overlapping lines.

AI-generated description

This line chart shows one week of temperature (in degrees Celcius) in cities around the world. The data comes from Data Canvas - Sense Your City.

MIT Licensed

Similar vizzes

Loading thumbnail…

Melting Data for Multiple Lines

This visualization displays population growth over time for various regions, using multiple lines to compare trends across areas. The chart employs a nested data structure, processing population estimates from the UN’s medium variant dataset for 1950-2100. The code utilizes D3’s `nest` and `line` functions with the `curveBasis` for smooth lines, while `scaleTime` and `scaleLinear` handle the axes. A color legend generated via a custom `colorLegend` function helps distinguish regions, and the rendering uses SVG with a `mix-blend-mode` for overlapping lines.

HHeholek
100% match
Loading thumbnail…

Melting Data for Multiple Lines

This visualization shows population over time by region, with multiple lines representing different areas across a time series from 1950 to 2100. The chart displays data from UN population estimates and medium variant projections, processed through a melting technique that converts wide-format data into long format using `d3.csv`, `d3.timeParse`, and `d3.range`. The visualization uses `d3.scaleTime` and `d3.scaleLinear` for axes, `d3.nest` to group data by region, and `d3.line` with `curveBasis` for smooth paths. A color legend is implemented via a custom `colorLegend` component using `d3.scaleOrdinal` with `schemeCategory10`.

KKevinw97
95% match
Loading thumbnail…

Melting Data for Multiple Lines

This visualization shows population over time by region, with multiple colored lines tracing each region’s trajectory from 1950 to 2100. The chart uses a time scale for the x-axis, a linear scale for population, and an ordinal color scale with a custom legend. D3’s `nest()` and `scaleOrdinal` group and color the series, while `d3.line` with `curveBasis` smooths the paths. Data comes from UN population estimates and medium-variant projections, melted into a tidy format for plotting as SVG.

NNeepaB
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 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 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
94% match
Loading thumbnail…

Melting Data for Multiple Lines

This visualization displays population over time by region, with multiple colored lines representing different world regions from 1950 to 2100. The chart uses D3 v5’s `nest()` to group data by region, `scaleTime` and `scaleLinear` for axes, and `line` with `curveBasis` to generate smooth paths. Data comes from UN population estimates and medium variant projections, processed by melting wide-format CSV data into tidy long format. A custom `colorLegend` function renders the categorical color scale, and the visualization includes gridlines, axis labels, and a title.

MMounikaBeerelly
94% match
Loading thumbnail…

Melting Data for Multiple Lines

This example visualizes population over time by region, displaying multiple trend lines across a Cartesian coordinate system. The chart uses D3’s `nest` and `line` with `curveBasis` to structure and smooth the data, while `scaleTime`, `scaleLinear`, and `scaleOrdinal` manage the axes and color encoding. A color legend, generated by a custom `colorLegend` function, identifies each region. The data comes from UN population estimates and medium-variant projections, processed through a custom `melt` function that reshapes the dataset.

Rrigt
94% match