With full support for tidyeval in {gt} and in specific functions in {gtExtras}, you can reference columns and rows just as you would in {dplyr}. You also get all the power of things like:
Fun fact - in about 20 lines of #rstats code you can scrape a table from @FiveThirtyEight , convert the text to a dataframe, and then recreate the _exact_ table with {gt}/{gtExtras}
Want to add some type of unit or symbol to your numbers but still have them align properly? Check out fmt_symbol_first() - has support for specific characters (eg "%") or HTML codes ("%")
You can also use gt_text_img() to add an image to the end of your table header. Useful for specifying the group you are working with, or possibly a company logo.
Want to know how those inline logos were added? That is gt_image_rows() which allows you to replace inline text representing the image with the actual image!
Lastly, there are color palette functions - the gt_hulk_col_numeric() functions applies the hulk palette ("purple" and "green") as a heatmap within a column or across the table.
Alternatively, the gt_color_rows() function is a wrapper around {paletteer} and gt::data_color() that lets you quickly apply colors to the table. {paletteer} provides dozens of built-in palettes, and the function supports discrete or continuous values.
More features will be built into the package over time, so give it a try and let me know what type of other features you would like to see for HTML tables!
- Theme components/elements
- Building your own theme
- Inspiration from @FiveThirtyEight
- 6 Different examples of using the theme
- Full code to reproduce
There are two primary ways I've built #rstats ggplot themes:
- theme() - Add theme components individually, wrap as a function
- %+replace% - Apply an existing theme and overwriting components of it
Use RMarkdown like a reproducible scientific notebook, capturing code, comments, and specific outputs in a output document.
All in plain text that is easily human-readable in version control!
2 - Data Product
Generate all sorts of fancy outputs from RMarkdown, such as:
- Presentations (Powerpoint or web native like remark.js)
- Dashboards w/ flexdashboards
- Reports as HTML, PDF, Word, etc
- Entire websites w/ blogdown, hugodown, distill
Goal 1: Connect with #rstats data science community
- Tons of academic and industry here on Twitter
- do informational interviews with acquaintances
- join @RLadiesGlobal Slack @R4DScommunity
@KTorresStats@RLadiesGlobal@R4DScommunity Goal here is to meet someone who can get your name to a hiring manager
- referrals == stronger chance of interview/hire
- R4DS and #rladies Slack are places outside Twitter to find job posts, ask questions, network
- Info interviews help you understand what pro DS do/expect