fresh block

100%

✓ Published0🌍 Public

Last edited Oct 12, 2017

Created on Oct 12, 2017

This visualization displays daily transaction volumes for multiple company IDs over five days in October 2017, with each company represented as a series of bars across the x-axis. The code uses d3.csv to load the data, d3.scaleBand for the categorical x-axis, d3.scaleLinear for the y-axis, and d3.scaleOrdinal with d3.schemeCategory20c for color mapping. It applies d3.stack to group transactions by company, though the rendered SVG currently assigns all stacks a red fill. The data originates from the included dump.csv file.

AI-generated description

Built with blockbuilder.org

mit Licensed

Similar vizzes

Loading thumbnail…

fresh block

A stacked bar chart displays yearly transaction counts for US states from 2010–2016, with each bar segmented by year and a legend identifying the color-coded categories. The visualization uses D3 v4’s `d3.stack()` to compute the layers, `d3.scaleBand()` for the state axis, `d3.scaleLinear()` for the count axis, and `d3.scaleOrdinal()` with `d3.schemeCategory20c` for colors. Data is loaded from a CSV file via `d3.csv`, and the chart renders as SVG with axes generated by `d3.axisBottom` and `d3.axisLeft`.

Aallyraza

79% match

Loading thumbnail…

fresh block

This example shows monthly stock price trends for multiple companies from 2000 to 2010, with each symbol rendered as a separate colored line on a time-series chart. The visualization uses D3 v4’s `d3.line` with a basis curve, `d3.scaleTime` and `d3.scaleLinear` for axes, and `d3.nest` to group data by stock symbol. It loads CSV data from a GitHub gist, parses dates with `d3.timeParse`, and renders static SVG paths with axes. The legend code is commented out, and no animation is implemented.

SSebDelSab

75% match

Loading thumbnail…

fresh block

A stacked area chart displays how four unnamed data categories change over time, with each layer labeled at the right edge and a y-axis formatted as a percentage. The code loads tab-separated data via `d3.tsv`, parses dates with `d3.timeParse`, and builds the visualization using `d3.stack`, `d3.area`, `d3.scaleTime`, `d3.scaleLinear`, and `d3.scaleOrdinal` with `d3.schemeCategory10`. SVG rendering and axes are created with `d3.axisBottom` and `d3.axisLeft`.

AAsilve00

75% match

Loading thumbnail…

fresh block

The visualization compares monthly stock prices for Microsoft, Amazon, and IBM from 2000 to 2010. It presents four distinct area-chart modes—transparent, stacked, separated, and centered—each animated to show the same data under different spatial arrangements. Built with D3.js v4, the code uses `d3.scaleTime`, `d3.scaleLinear`, `d3.area`, and `d3.curveBasis` to render smooth SVG paths. A legend identifies each company by color. The animation transitions between chart types, highlighting how each layout affects the perception of price trends and comparative performance.

HHakkahi

75% match

Loading thumbnail…

fresh block

The visualization shows a time-series area chart of stock prices, with the area colored red for values above 150 and blue for values below 150, highlighting threshold crossings. It uses D3.js (v3) with `d3.svg.area()`, `d3.time.scale()`, and `d3.svg.axis()` to render the SVG. Data is loaded from an external TSV file and parsed with `d3.time.format`. The code splits the dataset into contiguous segments based on the price threshold, then draws each segment as a separate colored area path. Axes are added for time and price, with the y-axis labeled “Price ($)”.

AAaronWitter

75% match

Loading thumbnail…

fresh block

This example shows a horizontal bar chart of the number of issues per company, with company names on the x-axis and value counts on the y-axis. Long company names are wrapped onto multiple lines using a custom `wrap` function that splits text and creates `tspan` elements. The chart is built with D3 v3, using an ordinal scale for the x-axis, a linear scale for the y-axis, and SVG rectangles for bars. The data is loaded as TSV from `data.tsv`, and a `d3-tip` tooltip is attached for mouseover interactions, though its content is currently left empty.

LLGBY4

74% match

Loading thumbnail…

fresh block

This visualization displays the daily market share of web browsers over a three-month period using a stacked area chart. The chart encodes each browser as a colored layer, with the y-axis showing percentage of total usage and the x-axis showing time. Built with D3 v4, it uses `d3.stack()` to stack the data series, `d3.area()` to construct the path geometries, and `d3.scaleTime()` and `d3.scaleLinear()` for the axes. The data is loaded from a TSV file, and category labels are positioned at the right edge of the chart for the larger share layers.

AAsilve00

74% match

Loading thumbnail…

fresh block

This visualization displays a stock price trend over time, with a line chart mapping date to closing value. The code sets up an SVG canvas using D3 v4, defining scales for time and linear values, and constructs a line generator. Although it loads the data from a CSV file via `d3.csv` and parses dates with `d3.timeParse`, the drawing function is empty, so the chart does not actually render any visible line or points.

Aallyraza

74% match