Skip to main content
SimilarExport ZIP
100%

VizHub Users Scatterplot B&W

✓ Published0🌍 Public
AAndre J Denais
Last edited May 6, 2021
Created on May 6, 2021

This scatterplot displays the growth of VizHub’s user base over time, with each circle representing a recorded date and corresponding user count. The data originates from a CSV file containing dates and cumulative user totals. The visualization uses D3 v6’s `scaleLinear` for both axes, `extent` to set domains, and `axisBottom` and `axisLeft` for ticks. Circles are rendered via SVG, and the chart fills the browser window with fixed margins, using a black-and-white design for clarity.

AI-generated description

A vanilla HTML implementation of a D3 scatter plot. Shows the Iris Dataset.

MIT Licensed

Similar vizzes

Loading thumbnail…

VizHub User Count Over Time

This visualization tracks the growth of VizHub’s user base from its August 2018 launch through December 2019, using a time-series line chart with green circular markers for each recorded data point. The chart encodes date on the x-axis and cumulative user count on the y-axis, revealing a steady upward trend with more pronounced growth spikes in mid-2019. Built with D3 v4, it uses `d3.scaleTime` and `d3.scaleLinear` for axes, `d3.axisBottom` and `d3.axisLeft` for ticks, and `d3.line` with `d3.curveMonotoneY` for the smoothed line. Data is loaded from a local CSV file via `d3.csv`, with each row parsed into a `Date` object and numeric user count, then rendered as SVG paths and circles.

NNita
85% match
Loading thumbnail…

VizHub User Count Over Time

This line chart shows the growth of VizHub’s user count from its launch in August 2018 through June 2020. The code uses d3.v4 with an SVG rendering approach, employing `d3.scaleTime`, `d3.scaleLinear`, and `d3.line` with a monotone curve. Data points are marked as circles, and the chart includes custom SVG annotations from `d3-svg-annotation` to highlight key events like a Medium post and the VizHub 2.0 Kickstarter. The data comes from a CSV file tracking user totals over time.

Mmahaghpanah
84% match
Loading thumbnail…

VizHub User Count Over Time

This line chart shows the growth in cumulative VizHub user accounts from August 2018 to March 2020. The x-axis displays time in days and the y-axis shows the user count, with annotation labels marking events like a medium post, a Kickstarter campaign, and a course launch. Built with D3 v4, it renders as an SVG using `d3.axisBottom`, `d3.axisLeft`, `d3.line` with a monotone curve, and `d3.annotationLabel` to highlight specific growth triggers. The data comes from a CSV file containing dates and user counts.

YYash G
83% match
Loading thumbnail…

VizHub User Count Over Time

This line chart shows VizHub user growth from its August 2018 launch through February 2020. The SVG visualization uses d3.line with a monotone curve, with each data point marked by a circle whose tooltip reveals the exact user count. Annotations from d3-svg-annotation highlight three growth events: a Medium post, the VizHub 2.0 Kickstarter, and the Datavis 2020 course launch. The code reads a local CSV file with user counts per date, and implements custom axes with tick marks and labels from d3.axisBottom and d3.axisLeft.

Sshehryar-hashir
83% match
Loading thumbnail…

Untitled

This visualization shows the growth of VizHub users over time since the platform launched on August 14, 2018. A line chart traces cumulative user counts across the date range, with the data drawn from a static source. The chart is rendered using D3.js, employing `d3.scaleTime` for the x-axis and `d3.scaleLinear` for the y-axis, with `d3.line` generating the path. Axes are added via `d3.axisBottom` and `d3.axisLeft`, while interactive hover effects are handled through mouse events and `d3.select` for tooltip display.

CChristian
82% match
Loading thumbnail…

Fork of VizHub User Count Over Time

This line chart shows the cumulative number of VizHub users over time, from August 2018 to January 2021, with annotated events like the VizHub 1.0 medium post, the 2.0 Kickstarter, and the Datavis 2020 launch. The visualization uses D3 v4’s `d3.scaleTime`, `d3.scaleLinear`, `d3.line` with a monotone curve, and `d3.axisBottom`/`d3.axisLeft` for axes. Circles mark each data point, while `d3.svg.annotation` from the d3-svg-annotation package adds contextual labels. Data is loaded from a local CSV with date and user count columns, rendered as an SVG with grid lines.

Aall-over-yet
82% match
Loading thumbnail…

Fork of VizHub User Count Over Time

This line chart shows the growth of VizHub users over time, with a steady upward trend punctuated by a notably steeper rise around the late 2020 period. The visualization uses d3.v4 with SVG rendering, employing d3.scaleTime and d3.scaleLinear for axes, and d3.line to draw the path. Data points are marked with circles, and an annotation from d3-svg-annotation highlights a surge labeled "Datavis 2020 Launch." The x-axis represents time while the y-axis counts users, with gridlines and axis labels styled via CSS.

DDasbach.EJ
82% match
Loading thumbnail…

Fork of VizHub User Count Over Time

A line chart shows the cumulative number of VizHub users from August 2018 to July 2021, with circular markers at each data point. The chart uses D3 v4's `scaleTime`, `scaleLinear`, `axisBottom`, and `axisLeft` to build the axes and grid, while `d3.line` draws the path. Annotations via the `d3-svg-annotation` library highlight key events such as the VizHub 1.0 release, a Kickstarter campaign, and the launch of a Datavis 2020 course. The SVG renders the full chart and grid, with data loaded from `users.csv`.

Aarjun-lab663
82% match