Skip to main content
SimilarExport ZIP
100%

Melting Data for Multiple Lines

✓ Published0🌍 Public
1158andCAT
Last edited Jul 2, 2020
Created on Jul 2, 2020

This visualization displays population over time by region as multiple colored lines, using an ordinal color scale to distinguish each region. The chart orders the lines by their final population value, creating an intuitive ranking. It uses D3 v5 APIs including `nest()`, `scaleTime()`, `scaleLinear()`, `line()` with `curveBasis`, and `axisBottom`/`axisLeft`. Data is processed from UN population estimate CSVs, melted from wide to long format to generate the time-series paths.

AI-generated description
MIT Licensed

Similar vizzes

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
96% match
Loading thumbnail…

Melting Data for Multiple Lines

This visualization shows projected population over time by region, with multiple colored lines representing different areas. The line paths are sorted by their final population values, and a categorical color legend identifies each region. The code uses D3 v5’s `nest`, `line`, `scaleTime`, `scaleLinear`, and `scaleOrdinal` APIs. Data is loaded from UN population CSV files and melted from wide to long format in `loadAndProcessData.js`, then rendered as an SVG with axis labels and a legend.

Ggabcoderboi
95% 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
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 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 displays population over time by region, with each line representing a different area and a color legend identifying them. The chart uses d3.csv to load UN population data, which is then processed using d3.nest to group data by region. The code demonstrates a data-wrangling technique called "melting," transforming wide-format data with columns per year into tidy data with year, name, and population fields. Multiple lines are drawn using d3.line and curveBasis, with d3.scaleTime and d3.scaleLinear handling the axes and d3.scaleOrdinal applying colors.

Ssingularity6033
95% match
Loading thumbnail…

Melting Data for Multiple Lines

This visualization shows population over time by region, with multiple line paths drawn in a single SVG chart. The lines are grouped by region name and displayed with a categorical color scale, accompanied by a legend. Data comes from UN population estimates and medium variant projections, melted into tidy format with `d3.csv`. The chart uses `d3.scaleTime`, `d3.scaleLinear`, `d3.line`, `d3.axisLeft`, `d3.axisBottom`, `d3.group`, and `d3.scaleOrdinal` to render axes, lines, and legends with SVG.

HHe Jianfeng
95% match
Loading thumbnail…

Melting Data Multiple Lines

The visualization shows population over time by region as multiple smoothed lines, with a color legend and axis labels. It uses D3 v5 APIs including `nest()` for grouping, `line()` with `curveBasis` for path generation, `scaleTime` and `scaleLinear` for axes, and `scaleOrdinal` with `schemeCategory10` for colors. Data is melted from UN population estimates and medium variant CSV files, spanning 1950 to 2100, rendered as SVG paths with multiply blend modes.

CCarloWK1202
94% match