Welcome to the AutoPlots wiki! AutoPlots exists because I'm looking for the easiest way to deliver the best possible plots. I hook into echarts4r because it connects to Echarts which is my favorite javascript plotting library. The plots are beautiful, dynamic, and fully customizable. The trick is enabling users to customize in the easiest way possible, which is the goal of this package.

There is a package manual in the vignette folder, which displays all functions that are exported in AutoPlots.

Contributions are always welcome. Below are some guiding thoughts for helping to contribute. If you can think of more feel free to update this comment. The package manual can be found here: https://github.com/AdrianAntico/AutoPlots/blob/main/vignette/AutoPlots_1.0.0.pdf

Areas of contribution

• Adding new Plot Types: https://echarts.apache.org/en/option.html#series Check out this link for new plot ideas
• Enhancing Existing Plot Types: https://echarts.apache.org/en/option.html Check out this link for ideas for adding new parameters that enable additional customization options.
• Code generation: would people want to run an automated function and also have source code returned? Code return is interesting because there is a data wrangling component and a plotting component. Perhaps one would want to customize the data wrangling or plotting component and getting the source code could help in that next step. If you inspect any of the functions, you'll see that there is a parameter called "PreAgg". PreAgg is logical and tells the function (if set to TRUE) that you already prepared the data and all the function needs to do is display the data. However, if you're working with raw data, the function should do the data wrangling for you and then display. Currently, I utilize data.table to do all data wrangling for preparing the data for display. It would be cool to also have an option to utilize rpolars to do the data wrangling and have its code returned as a result. Both data.table and rpolars are fast and memory efficient. If you want addition data wrangling options, feel free to include them (such as dplyr).
• Bug fixes: inevitably there will be bugs and we should strive to have a bug-free package. Bugs can include issues that cause error, design flaws, or anything that leads to poor user experience.
• Parameter Definitions: Let's make them more descriptive for ease of use. Also, lets add coded examples. There is a function in the package called, "FakeDataGenerator()" that you can use for mock data to demonstrate usage.
• Documentation: Parameter definitions can always be made more clear. Let's make it as easy as possible for users to understand what a parameter will do, how to utilize it, and when they should utilize it.

https://echarts4r.john-coene.com/articles/chart_types.html

1. Geo plots: https://echarts4r.john-coene.com/articles/map.html Get the basics done first and then customizations later
2. Polar plots: https://echarts4r.john-coene.com/articles/chart_types.html#polar
3. Funnel plots: https://echarts4r.john-coene.com/articles/chart_types.html#funnel
4. Effects Scatter plots: https://echarts4r.john-coene.com/articles/chart_types.html#effect-scatter
5. Radial plots: https://echarts4r.john-coene.com/articles/chart_types.html#radial
6. Sankey: https://echarts4r.john-coene.com/articles/chart_types.html#sankey
7. Parallel plots: https://echarts4r.john-coene.com/articles/chart_types.html#parallel
8. Sunburst: https://echarts4r.john-coene.com/articles/chart_types.html#sunburst
9. Tree: https://echarts4r.john-coene.com/articles/chart_types.html#tree
10. Treemap: https://echarts4r.john-coene.com/articles/chart_types.html#treemap
11. Calendar: https://echarts4r.john-coene.com/articles/chart_types.html#calendar
12. Gauge: https://echarts4r.john-coene.com/articles/chart_types.html#gauge
13. Radar: https://echarts4r.john-coene.com/articles/chart_types.html#radar
14. Liquid Fill: https://echarts4r.john-coene.com/articles/chart_types.html#liquifill