D3 Example

D3 Example

A grouped bar chart displays monthly stock prices for Microsoft, Amazon, and IBM from 2000 to 2010, with months on the x-axis and price on the y-axis. Bars are color-coded by company using a categorical color scale, with a color legend for identification. The chart loads data from `stocks.csv` and renders with SVG, using D3.js version 3.5.5 for scales, axes, nesting, and stacking, alongside the d3-legend library to generate the color legend.

MMariamArabi

89% match

Test

This line chart shows the monthly stock prices of Microsoft, Amazon, and IBM from January 2000 to March 2010, with each company’s price trend drawn as a separate colored line. The visualization uses the D3.js library (version 3.5.17) to parse dates, scale the axes, and render the SVG paths. Data is loaded from a CSV file, then grouped by symbol using `d3.nest()`, with the lines drawn using `d3.svg.line()` and the axes created via `d3.svg.axis()`. The color scale is generated dynamically with `d3.scale.category10()`.

Rrvdv

86% match

Tp3_DV_Rendu2

This visualization compares monthly stock prices for Microsoft, Amazon, and IBM from 2000 to 2010. It displays multiple small multiples, each showing a company’s price trend as a smooth line chart, with the data loaded from a CSV file. Using D3 v3, the code groups data by symbol via `d3.nest`, sorts companies by maximum price, and animates the drawing of each line progressively with a timer. An area fill, rendered via `d3.svg.area`, is added beneath each line, and the axis and scaling are computed dynamically per company.

86% match

Tp3_DV_Rendu5

This visualization compares the monthly stock prices of Microsoft, Amazon, and IBM from 2000 to 2010, showing both individual time series and a stacked area chart. The animation transitions through three views: individual line charts, horizon-style areas for each symbol, and finally a stacked layout. The code uses D3 v3 with SVG rendering, employing d3.svg.line, d3.svg.area, and d3.layout.stack for the layouts, while d3.time.scale handles the date axis. Data comes from a CSV file grouped by stock symbol via d3.nest.

86% match

Multiple lines

This visualization displays the monthly stock prices of Microsoft, Amazon, and IBM from 2000 to 2010 as multiple colored lines on a single chart. The chart uses a time-scaled x-axis and a linear y-axis for price, with each company’s line labeled directly. Built with D3 v4, the code loads data from a CSV, nests it by stock symbol, and renders using SVG paths. It also includes commented-out attempts at streamgraphs and area charts.

CCharlesGaydon

Tp3_DV_Rendu3

This interactive visualization displays the historical stock prices of Microsoft, Amazon, and IBM from January 2000 to March 2010. It uses a combination of individual line charts and a stacked area chart to compare the price trends and relative magnitudes across the three companies. The visualization is rendered as an SVG using D3 version 3, with animated transitions that convert between the line and stacked area representations. The code leverages D3’s time and linear scales, category color palette, and layout stack API to process and display the data from the provided CSV file.

Transitions

A stacked bar chart displays monthly stock prices for Microsoft, Amazon, and IBM from 2000 to 2010, with each layer colored by company. The visualization uses D3.js version 3.5.5 to load CSV data, nest and stack the series, and render SVG axes and rectangles. A d3-legend color scale identifies the three companies, while ordinal and linear scales map months and prices to the chart’s dimensions.

MMariamArabi

Tp3_DV_Rendu4

This visualization shows monthly stock prices for MSFT, AMZN, and IBM from 2000 to 2010, using layered area charts to compare trends across companies. Each symbol is displayed in its own horizontal band, with semi-transparent filled areas colored by company. The code uses D3 v3’s `d3.svg.area()`, `d3.svg.line()`, and `d3.time.scale()` to draw the SVG paths, while `d3.nest()` groups the CSV data by symbol. The chart sorts symbols by maximum price and applies basis interpolation for smooth curves.