dplyr VS cheatsheets

That's great feedback, thanks!

This tool definitely comes from a place of personal need - beyond just handling large files, I've also never really gelled well with the Excel/Google Sheet model of changing data in place as if you were editing text. I'm a Data Scientist and always preferred the chained data transforms you see in things like dplyr (https://dplyr.tidyverse.org/) or Polars (https://pola.rs/) and I feel this tool maps very closely to the chained model.

Also, thank you for the feature requests! Those would all be very useful - we'll put them on the roadmap.

There's an example of how to use zzz.R with a .onload() function to set options in the dplyr code base: https://github.com/tidyverse/dplyr/blob/bbcfe99e29fe737d456b0d7adc33d3c445a32d9d/R/zzz.r

Look at the tidyverse, especially the case_when or mutate functions.

Before diving into advanced machine learning algorithms or statistical models, we need to start with the basics: collecting and organizing data. Fortunately, both Python and R offer a wealth of libraries that make it easy to collect data from a variety of sources, including web scraping, APIs, and reading from files. Key libraries in Python include requests, BeautifulSoup, and pandas, while R has httr, rvest, and dplyr.

It looks like your syntax is wrong. I think you’re trying to calculate a new variables in your data frame, or alter an existing column in a data frame. Have a look at the select() function in this reference for the proper syntax to use. https://dplyr.tidyverse.org/ Does that help?

A lot of populat libraries have their own logos. Maybe one of them would be good. Check out dplyr for example: https://dplyr.tidyverse.org/

I hope you give it a try when you get a chance: https://dplyr.tidyverse.org/

You can read up on the dplyr-verbs here, which I strongly suggest for your exam! In the code examples, you can simply click on any function you don't understand and it will take you directly to the documentation. Good Luck!

If you're an R user, stringr + its cheatsheet gets you very close to remembering what to do without needing to look further!

For more information on how to use ggplot2 and create charts consult the ggplot2 official page or the ggplot2 cheat graphic.

I'd suggest you have a look at cheatsheets (or download them from GitHub) if you want to get to know your way around a package or set if functions, it saves you a lot of time.

You could use geom_hline and geom_vline, geom_abline, or geom_segment for this. (The ggplot cheat sheet is very useful for answering these kinds of questions, BTW.)

I can't say for sure because I don't know what your ultimate aim is for your visualization. Check out the cheat sheet for ggplot2 here.

Finally just do your analysis. You should also should give a try and see the cheat sheet for data importing on the tidyverse package.

That said, when I’m trying to come up with an interesting way to visualize data, I find the ggplot cheat sheet very helpful: https://github.com/rstudio/cheatsheets/raw/main/data-visualization-2.1.pdf

Here's a cheat sheet: https://github.com/rstudio/cheatsheets/blob/main/strings.pdf

The cheat sheet of the stringr package should give you good overview of string manipulation/ regex in R.

I would very highly recommend that rather than trying to get started by translating an existing graph, you check out some documentation about ggplot first. If nothing else, the ggplot cheat sheet from RStudio should help explain what the component parts of the code are, and that might help you figure out what you actually want to do.