(numerous sources and helpful tutorials on line helped produce this working example)
This Repo: https://github.com/TFaucheux/dc-test
npm install
ng serve
or
nb build --prod
- angular dc typings - [https://github.com/DefinitelyTyped/DefinitelyTyped/blob/master/types/dc/dc-tests.ts]
- Two charts with same dim. do not filter. Create duplicate dims. Instead.*
- Add chloropleth map. - see if region edits, if not use state or dma etc. [https://jsfiddle.net/djmartin_umich/9VJHe/] 2b. Leaflet - https://github.com/Intellipharm/dc-addons#leafletjs
- Scatterplot chart - explore Reductio exception
- Line charts - see Stephen few percentage technique.
- Date picker logic - service and UI, theme or slider. Look for d3 example.
- Project data - use 2nd chartgroup ndx var.
- KPIs - add cards and summary metrics
- Circo.js circular date chart. https://github.com/nicgirault/circosJS
- heat map - what to include http://bl.ocks.org/tjdecke/5558084
- Data table, pagination if possible, but without first. https://github.com/HamsterHuey/intothevoid.io/blob/master/code/2017/dcjs%20sortable%20table/dcjsSortableTable.html
- Determine what to do about detail sizes - scroll,limit, or expand.
- Dollar amounts - 5.2M
- BigData binning - https://github.com/uwdata/imMens/wiki
- Scala CSV web service - https://github.com/melrief/PureCSV
- Boxplot - what data? - https://dc-js.github.io/dc.js/examples/boxplot-time.html
- Number charts - https://dc-js.github.io/dc.js/examples/number.html
- Series - https://dc-js.github.io/dc.js/examples/series.html
- Sparklines - https://dc-js.github.io/dc.js/examples/sparkline.html
- Switching time intervals
- Aggregated Data - https://dc-js.github.io/dc.js/examples/table-on-aggregated-data.html
- Reduct.io - https://github.com/dc-js/dc.js/blob/b6bb3b214a1b1302fd65f6732ef2f1beb40ab62a/web/examples/sunburst-with-value-accessor.html
"Knowing what to avoid isn’t everything, but it’s a good start. Here’s a list of the 13 mistakes that I’ll describe in detail":
1. Exceeding the boundaries of a single screen
2. Supplying inadequate context for the data
3. Displaying excessive detail or precision
4. Expressing measures indirectly
5. Choosing inappropriate media of display
6. Introducing meaningless variety
7. Using poorly designed display media
8. Encoding quantitative data inaccurately
9. Arranging the data poorly
10. Ineffectively highlighting what’s important
11. Cluttering the screen with useless decoration
12. Misusing or overusing color
13. Designing an unappealing visual display