tidytable
Tidy interface to 'data.table' (by markfairbanks)
pak
A fresh approach to package installation (by r-lib)
| tidytable | pak | |
|---|---|---|
| 26 | 1 | |
| 435 | 623 | |
| - | 1.3% | |
| 8.2 | 9.3 | |
| 27 days ago | 3 days ago | |
| R | C | |
| GNU General Public License v3.0 or later | - |
The number of mentions indicates the total number of mentions that we've tracked plus the number of user suggested alternatives.
Stars - the number of stars that a project has on GitHub. Growth - month over month growth in stars.
Activity is a relative number indicating how actively a project is being developed. Recent commits have higher weight than older ones.
For example, an activity of 9.0 indicates that a project is amongst the top 10% of the most actively developed projects that we are tracking.
Stars - the number of stars that a project has on GitHub. Growth - month over month growth in stars.
Activity is a relative number indicating how actively a project is being developed. Recent commits have higher weight than older ones.
For example, an activity of 9.0 indicates that a project is amongst the top 10% of the most actively developed projects that we are tracking.
tidytable
Posts with mentions or reviews of tidytable.
We have used some of these posts to build our list of alternatives
and similar projects. The last one was on 2023-04-09.
- Tidyverse 2.0.0
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fuzzyjoin - "Error in which(m) : argument to 'which' is not logical"
If you need speed, you should consider using dtplyr (or tidytable), or even dbplyr with duckdb.
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tidytable v0.10.0 is now on CRAN - use tidyverse-like syntax with data.table speed
What do you think of this instead?
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Offering several functions to create the same object in my package
Here's an example - I use this in a package I've built called tidytable. Here is the as_tidytable() function I use that uses method dispatch.
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Dplyr performance issues (Late 2022)
If you're having performance issues with dplyr you can also try out tidytable
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R Dialects Broke Me
Iād say tidytable is a better option these days as it supports more functions. Although I think dtplyr has improved on this front recently, but still lags. The author of tidytable contributes to dtplyr as well.
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Why is mlr3 so under-marketed?
I know you said it 'feels much faster' which isn't exactly a data oriented comparison, but tidymodels performs very well. You can see one of the dplyr functions as step_* in tidymodels, for example mutate vs. step_mutate under recipes library. The author of tidytable, which uses data.table, had some revisions due to this conversation, just as an example.
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Why is {dplyr} so huge, and are there any alternatives or a {dplyr} 'lite' that I can use for the basic mutate, group_by, summarize, etc?
Tidytable is what you might be looking for: https://markfairbanks.github.io/tidytable/, this will require a bit of refactoring (e.g group-bys happen as arguments in summarise/mutate). You'll get data.table like speed in a very compact & complete package.
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Programming with R {dplyr}
People can also use tidytable and keep the same workflow they're already used to š
- tidytable v0.8.1 is on CRAN - it also comes with a new logo! Need data.table speed with tidyverse syntax? Check out tidytable.
pak
Posts with mentions or reviews of pak.
We have used some of these posts to build our list of alternatives
and similar projects. The last one was on 2022-12-15.
-
Why is {dplyr} so huge, and are there any alternatives or a {dplyr} 'lite' that I can use for the basic mutate, group_by, summarize, etc?
For installation, check out pak https://github.com/r-lib/pak, it's able to install in parallel.
What are some alternatives?
When comparing tidytable and pak you can also consider the following projects:
dtplyr - Data table backend for dplyr
poorman - A poor man's dependency free grammar of data manipulation
tidypolars - Tidy interface to polars
rmarkdown - Dynamic Documents for R
polars - Dataframes powered by a multithreaded, vectorized query engine, written in Rust
awesome-R - A curated list of awesome R packages, frameworks and software.
Apache Arrow - Apache Arrow is a multi-language toolbox for accelerated data interchange and in-memory processing
RFI - R-Fortran Interface for Modern Fortran
tidyr - Tidy Messy Data
r4ds - R for data science: a book
root - The official repository for ROOT: analyzing, storing and visualizing big data, scientifically
Tidier.jl - Meta-package for data analysis in Julia, modeled after the R tidyverse.