web-client-ui
polars
| web-client-ui | polars | |
|---|---|---|
| 5 | 144 | |
| 28 | 26,637 | |
| - | 4.4% | |
| 9.6 | 10.0 | |
| 6 days ago | 3 days ago | |
| TypeScript | Rust | |
| Apache License 2.0 | GNU General Public License v3.0 or later |
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.
web-client-ui
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The new React's documentation
Yes, it wasn't painless, but it has substantially improved our build time and overall been a good move. You can see the PR for our migration: https://github.com/deephaven/web-client-ui/pull/711
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Hi! We are Dr. Amanda Martin and JJ Brosnan, Developer and Python data scientist at Deephaven. Ask us anything about getting started in the data science industry, working with large data sets, and working with streaming data in Python.
Deephaven is open source. It's fundamental transport API (https://deephaven.io/barrage/docs/) and JavaScript Web-UI harness (https://github.com/deephaven/web-client-ui) are Apache-licensed; its core engine is source-available, with a single restriction that will have no impact on parties using it for their own interest.
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@deephaven/grid
README updated with some examples: https://github.com/deephaven/web-client-ui/tree/main/packages/grid
- Quadrillion Rows Example
polars
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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)
What are some alternatives?
scratchjr - With ScratchJr, young children (ages 5-7) can program their own interactive stories and games.
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 🚀
lumino - Lumino is a library for building interactive web applications
modin - Modin: Scale your Pandas workflows by changing a single line of code
scratch-www - Standalone web client for Scratch
datafusion - Apache DataFusion SQL Query Engine
jpy - A bi-directional Python-Java bridge used to embed Java in CPython or the other way round.
DataFrames.jl - In-memory tabular data in Julia
kaggle-environments
datatable - A Python package for manipulating 2-dimensional tabular data structures
TypeScript - TypeScript is a superset of JavaScript that compiles to clean JavaScript output.
Apache Arrow - Apache Arrow is a multi-language toolbox for accelerated data interchange and in-memory processing