Frustration-One-Year-With-R
An extremely long review of R. (by ReeceGoding)
dtplyr
Data table backend for dplyr (by tidyverse)
| Frustration-One-Year-With-R | dtplyr | |
|---|---|---|
| 16 | 24 | |
| 621 | 654 | |
| - | -0.3% | |
| 2.9 | 7.5 | |
| 10 months ago | 2 months ago | |
| 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.
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.
Frustration-One-Year-With-R
Posts with mentions or reviews of Frustration-One-Year-With-R.
We have used some of these posts to build our list of alternatives
and similar projects. The last one was on 2022-03-22.
- Will R be replaced by python in the coming years in industry for data analysis based bioinformatics (ie omics, NGS analysis)
- O que acham da linguagem R?
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What would you recommend for a mathematician and R person who really sucks at software/computing to learn Python as well? Or: how is Python so much more difficult than R?
python is a lot more consistent than R. it doesn't have most of the bullshit detailed here: https://github.com/ReeceGoding/Frustration-One-Year-With-R
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Modeling and simulation is where it’s at
See my friend's essay about it.
- Frustration: One Year with R
-
don’t
A friend of mine wrote a [recently viral R takedown](https://github.com/ReeceGoding/Frustration-One-Year-With-R) that shocked people in the same way.
- An R user writes down his frustration
- One Year with R
dtplyr
Posts with mentions or reviews of dtplyr.
We have used some of these posts to build our list of alternatives
and similar projects. The last one was on 2023-04-09.
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Tidyverse 2.0.0
Can’t say I’ve used it, but isn’t that what dtplyr is supposed to provide?
https://dtplyr.tidyverse.org/
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Error when trying to use dtplyr::lazy_dt, "invalid argument to unary operator"
# I am trying to follow the example at https://dtplyr.tidyverse.org/
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Millions of rows
FYI the developer of tidytable has been developing dtplyr for the Tidyverse. You might like that too!
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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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Best alternative to Pandas 2023?
https://dtplyr.tidyverse.org/ ?
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R Dialects Broke Me
If you want data.table speed, but using dplyr/tidy then dtplyr is a good package to have handy. Personally I love R, and choose R + NodeJS as my gotos for everything I do, and use Python only when I have to.
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Merging csv from environment.
Also, that dataset is quite big, and the "base" Tidyverse will be excessively slow. You should supplement the "base" Tidyverse packages (i.e. dplyr and tidyr) with either dtplyr or dbplyr (+ duckDB). I'd suggest starting with dtplyr, which should handle 10M+ rows fine.
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mutate ( ) function is only working in code chunk I run it in. It does not change the column in my data frame other than in that one code chunk.
If you want, there's a "substitute" for dplyr called dtplyr (also part of the Tidyverse), which "translates" your dplyr/tidyr code into data.table behind the scenes, and allows you to make your modifications apply directly to the original dataset by default:
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R process taking over 2 hours to run suddenly
Install the dtplyr package and change your code to:
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DS student here: why use R over Python?
Get the best of both worlds (tidyverse + data.tables) with dtplyr, a data.table backend for dplyr.
What are some alternatives?
When comparing Frustration-One-Year-With-R and dtplyr you can also consider the following projects:
review-tuxedo-pulse-15-gen1 - A review of the Tuxedo Pulse 15 (Gen 1).
tidytable - Tidy interface to 'data.table'
tidyr - Tidy Messy Data
polars - Dataframes powered by a multithreaded, vectorized query engine, written in Rust
mech - 🦾 Main repository for the Mech programming language. Start here!
tidypolars - Tidy interface to polars
cheatsheets - Posit Cheat Sheets - Can also be found at https://posit.co/resources/cheatsheets/.
vaex - Out-of-Core hybrid Apache Arrow/NumPy DataFrame for Python, ML, visualization and exploration of big tabular data at a billion rows per second 🚀
forcats - 🐈🐈🐈🐈: tools for working with categorical variables (factors)
Datamancer - A dataframe library with a dplyr like API
argbash - Bash argument parsing code generator
explorer - Series (one-dimensional) and dataframes (two-dimensional) for fast and elegant data exploration in Elixir
Frustration-One-Year-With-R vs review-tuxedo-pulse-15-gen1
dtplyr vs tidytable
Frustration-One-Year-With-R vs tidyr
dtplyr vs polars
Frustration-One-Year-With-R vs mech
dtplyr vs tidypolars
Frustration-One-Year-With-R vs cheatsheets
dtplyr vs vaex
Frustration-One-Year-With-R vs forcats
dtplyr vs Datamancer
Frustration-One-Year-With-R vs argbash
dtplyr vs explorer