AssQue1

Customising axes with D3.js!

A horizontal bar chart displays the happiness scores of ten countries, using a steelblue fill for each bar. The visualization customizes the axes with D3.js v5 APIs, including `scaleLinear` for the score axis, `scaleBand` for the country axis, and `axisLeft`/`axisBottom` for rendering the tick marks. The SVG chart, drawn via the `select` and `append` methods, reads data from a local CSV file and sets a large font size for all text labels.

79% match

Scatter plot with D3.js!

This scatter plot displays the happiness scores of ten countries, showing each nation’s score along the horizontal axis with country names on the vertical axis. The visualization uses D3.js v5 with an SVG rendering approach, loading data from a CSV file. The code employs `d3.csv`, `scaleLinear`, and `scalePoint` to map scores and countries, while `axisBottom` and `axisLeft` generate the axes with tick lines. Circles are appended for each data point, styled with steelblue fill and opacity.

79% match

Fork of Making A Bar Chart

This bar chart displays Happiness_Score values for countries from a CSV dataset, using horizontal bars with a linear x-scale and banded y-scale. It shows one bar per country, with the bar length encoding the happiness score. The visualization is rendered as SVG using D3 v7, employing `scaleLinear`, `scaleBand`, `axisLeft`, and `axisBottom` to construct the axes and rectangles. The code loads data via `d3.csv` and applies a margin-based layout within a fixed 960×500 viewport.

NNikithakatta30

78% match

Scatter plot with D3.js!

This scatter plot displays the happiness scores of ten countries, with each country positioned along the y-axis and its score plotted on the x-axis. The visualization is rendered as an SVG using D3.js v5, employing `scaleLinear` for the x-axis and `scalePoint` for the categorical y-axis. Data is loaded from a CSV file via `d3.csv`, and axes are generated with `axisBottom` and `axisLeft`. The chart includes labeled axes and a title, with gridlines created through tick sizes.

78% match

Untitled

This scatter plot shows the relationship between Happiness Score and rate of depressive disorders, with each circle’s size encoding population and color distinguishing four geographic regions. The visualization uses D3.js (v3) to load a CSV file via `d3.csv`, maps data to positions with `d3.scaleLinear`, assigns categorical colors with `d3.scaleOrdinal`, and renders SVG circles. Axes are generated using `d3.axisBottom` and `d3.axisLeft`, with opacity set to 0.5 for overlapping points.

Vvihaansubhash

Customising axes with D3.js!

This example shows a horizontal bar chart of the ten happiest countries ranked by their happiness scores. The visualization highlights custom axis styling, where tick marks and lines are recolored, and axis domains are removed for a cleaner look. Built with D3.js v5, it loads data from a CSV file and uses `scaleBand` for the categorical y-axis and `scaleLinear` for the numeric x-axis. The code also leverages `axisLeft` and `axisBottom` to generate axes, with SVG rectangles representing each bar.

Untitled

This scatter plot displays the relationship between a country's Happiness Score and its rate of depressive disorders, with each point's size representing population and color encoding geographic region. The visualization uses d3.csv to load the data, d3.scaleLinear for both axes, and d3.scaleOrdinal for the categorical color mapping. SVG circles are positioned via the xScale and yScale functions, with axis labels and tick marks generated using d3.axisBottom and d3.axisLeft within a React-rendered SVG container.

NNikithakatta30

A6_BarChart with Sequential Scale

This example visualizes the happiness scores of various countries using a bar chart where each bar’s color encodes its score through a sequential blue scale. The chart is rendered as an SVG in a React application, leveraging D3 v7 for scaling and axis generation, while the color mapping is handled by `d3.scaleSequential` with the `interpolateBlues` interpolator. The data is loaded via `d3.csv` from a GitHub-hosted dataset, and a legend is added using the `d3-legend` library to clarify the score-to-color mapping. The visualization highlights the relative happiness rankings across countries while making score differences visually intuitive through color intensity.

DDuc Pham