red_amber
A dataframe library for Rubyists. (by red-data-tools)
polars
Dataframes powered by a multithreaded, vectorized query engine, written in Rust (by ritchie46)
| red_amber | polars | |
|---|---|---|
| 1 | 144 | |
| 62 | 26,514 | |
| - | 3.9% | |
| 8.5 | 10.0 | |
| 3 months ago | 1 day ago | |
| Ruby | Rust | |
| MIT License | 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.
red_amber
Posts with mentions or reviews of red_amber.
We have used some of these posts to build our list of alternatives
and similar projects. The last one was on 2023-01-19.
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Tried polars in Ruby
So while the Arrow C binding for the Ruby language is relatively well-developed, polars-df is not an Arrow C binding, but a binding to Polars implemented in Rust. magnus is used for the connection between Ruby and Rust. In fact, there is also a Ruby data frame that uses the Arrow binding, which is called RedAmber. But we are not talking about that now.
polars
Posts with mentions or reviews of polars.
We have used some of these posts to build our list of alternatives
and similar projects. The last one was on 2024-01-08.
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Why Python's Integer Division Floors (2010)
This is because 0.1 is in actuality the floating point value value 0.1000000000000000055511151231257827021181583404541015625, and thus 1 divided by it is ever so slightly smaller than 10. Nevertheless, fpround(1 / fpround(1 / 10)) = 10 exactly.
I found out about this recently because in Polars I defined a // b for floats to be (a / b).floor(), which does return 10 for this computation. Since Python's correctly-rounded division is rather expensive, I chose to stick to this (more context: https://github.com/pola-rs/polars/issues/14596#issuecomment-...).
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Polars
https://github.com/pola-rs/polars/releases/tag/py-0.19.0
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Stuff I Learned during Hanukkah of Data 2023
That turned out to be related to pola-rs/polars#11912, and this linked comment provided a deceptively simple solution - use PARSE_DECLTYPES when creating the connection:
- Polars 0.20 Released
- Segunda linguagem
- Polars: Dataframes powered by a multithreaded query engine, written in Rust
- Summing columns in remote Parquet files using DuckDB
- Polars 0.34 is released. (A query engine focussing on DataFrame front ends)