poorman
A poor man's dependency free grammar of data manipulation (by nathaneastwood)
tidytable
Tidy interface to 'data.table' (by markfairbanks)
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| poorman | tidytable | |
|---|---|---|
| 2 | 26 | |
| 328 | 434 | |
| - | - | |
| 5.7 | 8.2 | |
| 3 months ago | 20 days ago | |
| R | R | |
| GNU General Public License v3.0 or later | 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.
poorman
Posts with mentions or reviews of poorman.
We have used some of these posts to build our list of alternatives
and similar projects. The last one was on 2022-12-15.
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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?
You might find the poorman package interesting: https://github.com/nathaneastwood/poorman
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Just how widely accepted is tidyr/dplyr these days?
It's true that their packages are heavy on dependencies, and if that is a concern, you have alternatives: - poorman: no dependencies, same syntax as dplyr, but only includes basic verbs. - datawizard: low dependencies, slightly different syntax, has base-R implementations of most of dplyr / tidyr functions, plus some other goodies likes scaling, mean-centering, rank transforming, ... - And of course, data.table: 0 dependencies, ultra-fast (everything is written in optimized C under the hood), can manipulate much bigger data than the Tidyverse, and can do everything the tidyverse can when it comes to data wrangling (however, sometimes the tidyverse has convenience functions that make some operations shorter than with data.table). The downside is that data.table's syntax requires more efforts to learn / is less intuitive to read for neophytes.
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.
What are some alternatives?
When comparing poorman and tidytable you can also consider the following projects:
re2 - R interface to Google re2 (C++) regular expression engine
dtplyr - Data table backend for dplyr
awesome-R - A curated list of awesome R packages, frameworks and software.
tidypolars - Tidy interface to polars
ggplot2 - An implementation of the Grammar of Graphics in R
polars - Dataframes powered by a multithreaded, vectorized query engine, written in Rust
pak - A fresh approach to package installation
Apache Arrow - Apache Arrow is a multi-language toolbox for accelerated data interchange and in-memory processing
fastverse - An Extensible Suite of High-Performance and Low-Dependency Packages for Statistical Computing and Data Manipulation in R
tidyr - Tidy Messy Data
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.