Untitled

100%

✓ Published0🌍 Public

Last edited Jun 4, 2022

Created on Jun 4, 2022

Forked from Melting Data for Multiple Lines

This visualization shows population trends over time for various world regions, using colored lines to represent each region across a timeline from 1950 to 2100. The chart displays the data with a time-scaled x-axis and a linear y-axis for population values. Built with D3 v4, the code utilizes `d3.csv` to load data, `d3.nest` for grouping by region, and `d3.line` to generate the paths. The visualization applies a color legend via a custom `colorLegend` module and incorporates axis labels and gridlines for readability.

AI-generated description

MIT Licensed

Similar vizzes

Loading thumbnail…

Untitled

This example visualizes population growth over time for global regions, drawing on UN population estimates (1950–2014) and medium-variant projections (2015–2100). It renders multiline time-series curves using d3.line with curveBasis, scaled by d3.scaleTime and d3.scaleLinear, while a categorical d3.scaleOrdinal with schemeCategory10 assigns region colors. The chart includes axes, gridlines, and a custom color legend built via d3-selection. Data is processed by melting a wide CSV format into tidy rows, filtering for regions only, and concatenating the historical and projected datasets.

Ccyanea1

89% match

Loading thumbnail…

Untitled

This area chart visualizes global population growth over time, with a maroon filled region beneath a smooth curve and labeled axes. The visualization maps years to the x-axis and population to the y-axis, using data from a CSV file. Built with D3 v5, it employs `scaleTime` and `scaleLinear` for scales, `area` with `curveBasis` to generate the path, and `axisBottom` and `axisLeft` for axes. Population values are formatted with `format('.1s')` to display billions.

Lliechtia

86% match

Loading thumbnail…

Population time-series

This visualization shows population trends over time for world regions, with each region's trajectory drawn as a distinct colored line. A color legend identifies the regions, and the chart title clearly labels the relationship between population and year. The visualization uses D3 v5 APIs including `nest` for data grouping, `scaleTime` and `scaleLinear` for axes, and `line` for generating SVG paths. Data comes from UN population estimates and historical datasets processed via Promise loading. The color legend component updates with transitions, while lines use blend modes for overlapping clarity.

Rreo440

86% match

Loading thumbnail…

Population time-series

This visualization displays population trends for global regions from 1950 to 2100, using animated line charts that color-code each region via a categorical scale. The data, sourced from UN population estimates, is processed through a custom melt function and rendered as SVG with D3 v5, React, and the `d3.axisBottom`, `d3.axisLeft`, and `d3.line` APIs. A color legend with animated transitions clarifies the mapping, while styled tick lines and labels enhance readability.

MManoj Betawar

86% match

Loading thumbnail…

Population time-series

This interactive visualization displays population trends for global regions from 1950 to 2100, using animated line charts that show each region’s growth over time. The data comes from UN population estimates, processed and merged from two CSV files. The visualization is built with React and D3.v5, using d3.line for path generation, d3.scaleTime for the x-axis, and d3.scaleOrdinal with color legends to distinguish regions. The SVG rendering includes axis labels, a chart title, and interactive color legend, with animations applied to legend transitions.

JJorge Emilio Zapata Godoy

85% match

Loading thumbnail…

Population time-series

This example shows population trends over time for world regions, with each region drawn as a colored line against year and population axes. A color legend on the right identifies each region, and the lines are sorted by their final population values. The visualization uses React with D3 v5, including `d3.line`, `d3.nest`, `d3.scaleOrdinal`, and `d3.schemeCategory10` for styling. Data comes from UN population estimates CSV files, processed via a custom melt function, and rendered as animated SVG paths with transitions on the legend.

Sszy1900

85% 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

85% 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

84% match