Another essential but low-level data science skill, data-driven visualizations!
From the webpage:
Composable
Create small and sharp charts/components that do one thing one well (e.g. Bars, Lines, Legend, Axis, etc.) and compose them to create complex visualizations.
d3.compose works great with your existing charts (even those from other libraries) and it is simple to extend/customize the built-in charts and components.
Automatic Layout
When creating complex charts with D3.js and d3.chart, laying out and sizing parts of the chart are often manual processes.
With d3.compose, this process is automatic:
- Automatically size and position components
- Layer components and charts by z-index
- Responsive by default, with automatic scaling
Why d3.compose?
- Customizable: d3.compose makes it easy to extend, layout, and refine charts/components
- Reusable: By breaking down visualizations into focused charts and components, you can quickly reconfigure and reuse your code
- Integrated: It’s straightforward to use your existing charts or charts from other libraries with d3.compose to create just the chart you’re looking for
Don’t ask me why but users/executives are impressed by even simple charts.
(shrugs) I have always assumed that people use charts to avoid revealing the underlying data and what they did to it before making the chart.
That’s not very charitable but I have never been disappointed in assuming either incompetence and/or malice in chart preparation.
People prepare charts because they are selling you a point of view. It may be a “truthful” point of view, at least in their minds but it is still an instrument of persuasion.
Use well-constructed charts to persuade others to your point of view and be on guard for the use of charts to persuade you. Both of those principles will serve you well as a data scientist.