Grid Cartogram component with live COVID demos (plus a MapEditor) / Eric Lo / Observable
Grid Cartogram is a prevalent type of map for showing statistical data based on geographic location. It is a distorted form that each cell of the grid represents one subdivision. The cleanness and simplicity help users understand the information quickly without getting distracted by other elements on a normal map. Below is a US COVID map that visualizes the live data from NYT's repository (transformed into the last N days format). The map demonstrates the main features of the GridMap as well as an
Time Spiral with a COVID Demo / Eric Lo / Observable
Spiral chart visualizes time-based dataset alone an outward spiral. It is beneficial for displaying a large dataset over a long period in a single visualization. Color can be based on values to emphasize the chart's visual aspect or assigned to each period, which helps as a way of observing periodic patterns. Below is an application of the TimeSpiral in a real use case scenario combined with the GridMap. The TimeSpiral plots the cases/deaths number from day one as you hover over each state. * See the
A few weeks ago, I published D3 Render: Truly Declarative and Reusable D3, introducing an experimental library that tries to simplify D3 with one render function. To test the capabilities of this library, I thought I'd start with a mildly complex example—an interactive bubble chart. Rather than using dummy data, I've utilised live COVID-19 datasets from Our World In Data. Note: This chart has been embedded as an infographic in this article as part of The Conversation's COVID-19 coverage. COVID–19: Cellular
Fynd Category D3 Zoom node with context menu / prajax / Observable
Click to zoom in or out TODO fork this notebook create a function which convert fynd category csv input csv link to tree JSON output json link on group right click add context menu , which will create a new form with two input box (name, value) on submit button append new node within same group
D3’s tree layout implements the Reingold–Tilford “tidy” algorithm for constructing hierarchical node-link diagrams, improved to run in linear time by Buchheim et al. Tidy trees are typically more compact than cluster dendrograms, which place all leaves at the same level. See also the Cartesian variant.