RFI
R-Fortran Interface for Modern Fortran (by t-kalinowski)
collapse
Advanced and Fast Data Transformation in R (by SebKrantz)
| RFI | collapse | |
|---|---|---|
| 1 | 2 | |
| 21 | 600 | |
| - | - | |
| 2.6 | 9.6 | |
| over 3 years ago | 8 days ago | |
| C | C | |
| GNU General Public License v3.0 only | 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.
RFI
Posts with mentions or reviews of RFI.
We have used some of these posts to build our list of alternatives
and similar projects. The last one was on 2021-06-09.
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.
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is there a package using data.table that provides functions for descriptive stats, missingness etc?
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.
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Benchmarking for loops vs apply and others
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)
What are some alternatives?
When comparing RFI and collapse you can also consider the following projects:
mpich - Official MPICH Repository
fastverse - An Extensible Suite of High-Performance and Low-Dependency Packages for Statistical Computing and Data Manipulation in R
flang - Flang is a Fortran language front-end designed for integration with LLVM.
writexl - Portable, light-weight data frame to xlsx exporter for R
gcc_termux - Gcc for termux with fortran scipy etc... Use apt for newest updates instructions in README.txt
epanet2toolkit - An R package for calling the Epanet software for simulation of piping networks.
inline - Inline C, C++ or Fortran functions in R
priceR - Economics and Pricing in R