data-science-ipython-notebooks
fugue
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| data-science-ipython-notebooks | fugue | |
|---|---|---|
| 1 | 11 | |
| 26,459 | 1,876 | |
| - | 2.3% | |
| 0.0 | 6.7 | |
| about 1 month ago | 3 days ago | |
| Python | Python | |
| GNU General Public License v3.0 or later | Apache License 2.0 |
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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.
data-science-ipython-notebooks
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Beginner in Python for Data Science
data science ipython notebooks
fugue
- FLaNK Stack Weekly 22 January 2024
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Daft: A High-Performance Distributed Dataframe Library for Multimodal Data
Please integrate it with Fugue.
https://github.com/fugue-project/fugue
- Fugue: A unified interface for distributed computing
- [Discussion] Open Source beats Google's AutoML for Time series
- Ask HN: How do you test SQL?
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Replacing Pandas with Polars. A Practical Guide
Fugue is an interesting library in this space , though I haven’t tried it
https://github.com/fugue-project/fugue
A unified interface for distributed computing. Fugue executes SQL, Python, and Pandas code on Spark, Dask and Ray without any rewrites.
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The hand-picked selection of the best Python libraries and tools of 2022
fugue — distributed computing done easy
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[P] Open data transformations in Python, no SQL required
This looks similar to fugue, am I right? How do they compare?
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What the Duck?!
I am looking forward to how Substrait could help removing this friction. It aims to provide a standardised intermediate query language (lower level than SQL) to connect frontend user interfaces like SQL or data frame libraries with backend analytical computing engines. It is linked to the Arrow ecosystem. Something like Ibis or Fugue could become the front and DuckDB the backend engine.
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Pyspark now provides a native Pandas API
There's dask-sql, but I think it is being abandoned for fugue-project. I'm actually excited for this project as it is trying to provide a backend agnostic solution, which would seem like a difficult, lofty goal. I wish them luck.
What are some alternatives?
manjaro-linux - Shell scripts for setting up Manjaro Linux for Python programming and deep learning
modin - Modin: Scale your Pandas workflows by changing a single line of code
BirdNET - Soundscape analysis with BirdNET.
Optimus - :truck: Agile Data Preparation Workflows made easy with Pandas, Dask, cuDF, Dask-cuDF, Vaex and PySpark
kmodes - Python implementations of the k-modes and k-prototypes clustering algorithms, for clustering categorical data
mlToolKits - learningOrchestra is a distributed Machine Learning integration tool that facilitates and streamlines iterative processes in a Data Science project.
sports-betting - Collection of sports betting AI tools.
ploomber - The fastest ⚡️ way to build data pipelines. Develop iteratively, deploy anywhere. ☁️
PMapper - A tool for quickly evaluating IAM permissions in AWS.
xarray - N-D labeled arrays and datasets in Python
data-science - :bar_chart: Path to a free self-taught education in Data Science!
chispa - PySpark test helper methods with beautiful error messages