stringr VS dplyr

Perhaps str_extract_all() from stringr? (since you're already using dplyr)

There are base R ways of finding strings grep(), as well as packages such as {stringer} (cheat sheet available here: https://stringr.tidyverse.org/)

If you're unfamiliar with regex, it may help you review the stringr cheat sheet: https://stringr.tidyverse.org/

Without knowing more, it seems likely that some combination of stringr and fuzzyjoin will be what you need.

Search for info about the grepl-function and read the cheat sheet from the stringr-package, that should get you started: https://stringr.tidyverse.org/

Looks like you have a misunderstanding about the right-most column. Don't think of the cell values as vectors of length=N elements, c("gene1", "gene2", ..."geneN"). Instead, think of each cell as a character string (vector of length=1), "gene 1, gene 2, ... geneN". Finding specific sequence of characters within a string is different from finding matching elements of vectors. Without changing the column, you can use regular expressions and base R string functions and/or stringr if you're more comfortable with tidyverse.

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!