dplyr VS stringr

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!

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.