collapse VS awesome-R

Compare collapse vs awesome-R and see what are their differences.

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collapse awesome-R
2 6
599 5,781
- -
9.6 4.0
4 days ago about 2 months ago
C R
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.

collapse

Posts with mentions or reviews of collapse. We have used some of these posts to build our list of alternatives and similar projects. The last one was on 2022-05-01.
  • is there a package using data.table that provides functions for descriptive stats, missingness etc?
    1 project | /r/rstats | 12 Oct 2022
    The ask is a little unclear. You might be interested in collapse and more generally in other packages in the fastverse. I guess it's also worth pointing out that data.table already provides alternative methods for certain base R descriptive stats functions (e.g., mean, etc.) that are automatically used when applied to datatables.
  • Benchmarking for loops vs apply and others
    2 projects | /r/rstats | 1 May 2022
    If you are looking for performance I would recommend to check the collapse package. The following line "collapse" = collapse::fsum(df_datatable$x, g=df_datatable$g) is around 2x faster than base::rowsum, and the dplyr style syntax doesn't add that much of an overhead "collapse dplyr" = df_datatable |> fgroup_by(g) |> fsum(x)

awesome-R

Posts with mentions or reviews of awesome-R. We have used some of these posts to build our list of alternatives and similar projects. The last one was on 2024-01-13.

What are some alternatives?

When comparing collapse and awesome-R you can also consider the following projects:

fastverse - An Extensible Suite of High-Performance and Low-Dependency Packages for Statistical Computing and Data Manipulation in R

fontawesome - Easily insert FontAwesome icons into R Markdown docs and Shiny apps

writexl - Portable, light-weight data frame to xlsx exporter for R

easystats - :milky_way: The R easystats-project

priceR - Economics and Pricing in R

sf - Simple Features for R

bruceR - 📦 BRoadly Useful Convenient and Efficient R functions that BRing Users Concise and Elegant R data analyses.

lab02_R_intro - Vežbe 2: Uvod u R

tableone - R package to create "Table 1", description of baseline characteristics with or without propensity score weighting

viridis - Colorblind-Friendly Color Maps for R

r-yaml - R package for converting objects to and from YAML

llr - Lisp-like-R: A clojure inspired lisp that compiles to R in R