Fork of Pathetic Bar Chart

Fork of Pathetic Bar Chart

This fork of the Pathetic Bar Chart renders the top 10 most populous countries as rectangles with no axes, using React and D3 v5. The chart shows population values for 2020 from the United Nations World Population Prospects 2019 dataset, loaded via `d3.csv`. The code uses `d3.scaleBand` for the y-axis country labels, `d3.scaleLinear` for the horizontal bar lengths, and renders the SVG output through ReactDOM, with a left margin for country names.

Llatifiss

Fork of Pathetic Bar Chart

This fork of the Pathetic Bar Chart displays the top 10 most populous countries as horizontal bars without axes. It uses React with a `useEffect` hook to load CSV data from the United Nations World Population Prospects 2019 via `d3.csv`. The visualization employs `d3.scaleBand` for the y-axis and `d3.scaleLinear` for the x-axis, rendering SVG rectangles and text labels. The code also generates tick marks and labels for the x-axis, though they lack visible axis lines.

Aalitemel89

Fork of Pathetic Bar Chart

This fork of a "pathetic bar chart" displays the top 10 most populous countries as horizontal bars with no axes or labels, ranked by population. The visualization uses React to manage state and render SVG rectangles, with D3 v5’s `csv` for data loading and `scaleBand`/`scaleLinear` for mapping country names and population values to pixel coordinates. Data comes from the United Nations World Population Prospects 2019 dataset.

VVahe Abovyan

Fork of Pathetic Bar Chart

This visualization displays the top 10 most populous countries as a bare bar chart with no axes, using rectangular bars proportional to each country’s 2020 population. The chart loads data from the United Nations World Population Prospects 2019 CSV, then uses `d3.csv`, `scaleBand`, `scaleLinear`, and `max` to map country names and population values to SVG rectangles. React manages the component state and rendering, while D3 handles the data processing and scales. The bars render in an SVG canvas with no labels or gridlines, focusing purely on the relative population sizes.

Aavneet12284

Fork of Pathetic Bar Chart

This example displays the top 10 most populous countries as a rudimentary bar chart with no axes, using a React component and SVG rendering. It loads United Nations World Population Prospects 2019 data from a CSV via `d3.csv`, slices the first ten rows, and maps populations for 2020 to rectangle widths using `d3.scaleLinear`, while `d3.scaleBand` positions each country vertically. The chart omits axis labels and titles, presenting only the bars against a blank canvas.

KKuladeep

Fork of Pathetic Bar Chart

This example displays the top 10 most populous countries as a set of horizontal bars, lacking any axes or labels. The bar lengths encode each country’s 2020 population estimate from the United Nations World Population Prospects 2019 dataset. React manages the component state and rendering, while d3.csv loads and parses the data, and d3.scaleBand and d3.scaleLinear map the country names and population values to SVG rectangle positions and widths. The visualization updates asynchronously after the CSV file is fetched.

TTrevor McReynolds

Fork of Pathetic Bar Chart

This example displays the top 10 most populous countries in 2020 as a bar chart stripped of axes and labels, arranged vertically with bar lengths proportional to population. It loads data from the United Nations World Population Prospects 2019 CSV via `d3.csv`, formats population values, and slices the first ten rows. React manages the loading state and renders SVG rectangles using `scaleBand` for the y-axis positions and `scaleLinear` for bar widths inside a margin-based group.

LLaura Brown

RRennan Henrique Marques de Almeida

Fork of Pathetic Bar Chart

A React-based bar chart displays the top 10 most populous countries from the United Nations World Population Prospects 2019 dataset, with no axes or labels. The chart uses `d3.scaleBand` for vertical country positioning and `d3.scaleLinear` for horizontal bar widths based on 2020 population values. Data is loaded asynchronously via `d3.csv`. The SVG renders each country as a simple `<rect>` element, creating a deliberately minimal, pathetic visualization.