Ibis
@IbisData
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Expressive analytics in Python at any scale. Questions? Join the discussion at https://t.co/gSgMkpaBEm
Joined July 2009
Ibis offers an API similar to @pandas_dev to connect to SQL databases and big data systems. More info:
ibis-project.org
the portable Python dataframe library
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Ibis 10.0.0 is out! pip install ibis-framework==10.0.0 Lots of new features, bug fixes and two new backends: Amazon Athena and Databricks! Check out the release notes here:
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New blog posts 2/2: Dynamic UDF Rewriting with Predicate Pushdowns https://t.co/9yvlaDflYP Check 'em out!
ibis-project.org
the portable Python dataframe library
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New blog posts 1/2: Does Ibis Understand SQL? https://t.co/oPPMxzi4Lu
ibis-project.org
the portable Python dataframe library
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Ibis 10.0.0 is out! pip install ibis-framework==10.0.0 Lots of new features, bug fixes and two new backends: Amazon Athena and Databricks! Check out the release notes here:
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With the latest version of @pyodide (0.27.1), you can run %pip install ibis-framework[duckdb] to get an expressive, lightning-fast, and *entirely-in-browser* dataframe API! Give it a try at
ibis-project.org
the portable Python dataframe library
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First blog post in a long time! I started writing a post ~2 years ago on adventures counting 130M U.S. buildings by zipcode and finally circled back to write it up. Everybody is a winner really, but @duckdb @IbisData , @ApacheArrow, and @GeoParquet were essential throughout!
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no code transformations using marimo's mo.ui.dataframe and @IbisData! Pass in any Ibis dataframe to mo.ui.dataframe to display a UI for different filters/transformations and get the filtered result back in Python. Plus, you can see the SQL statement generated by Ibis!
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It's never been a better time to get involved with Ibis! If you need Python dataframes that work on the best local engines (@duckdb, @ApacheDataFusio, @DataPolars) and distributed/cloud platforms (@ApacheSpark, @SnowflakeDB, @ClickHouseDB, @trinodb), give us a try!
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The "Tools don't matter" argument falls flat in Data Engineering and ML. - Working with large datasets on a Spark cluster can quickly shift your focus from business problems to infrastructure challenges. - Using Pandas for 10GB+ data demands huge RAM, but switching to @duckdb
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Want to work with Python dataframes on a trillion rows of data in someone else's high-performane OLAP database? Check out our latest blog using Ibis, @ClickHouseDB , and Shiny for Python to build an interactive dashboard on the PyPI downloads dataset:
ibis-project.org
the portable Python dataframe library
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end of an era, for new project think seriously of using a new Dataframe Engine, there are plenty of choices, ibis will drop support for Pandas https://t.co/HlzGSsU4SL
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@IbisData support is very rudimentary but you can connect to #microsoftfabric DWH, list catalog, run sql etc
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My @SciPyConf talk: @IbisData and @duckdb geospatial: a match made on Earth! is on youtube. (there was a problem with the recording, apologies about the yellow background) #geospatial
https://t.co/X7f0pCXMz7
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Here are a few reasons why I prefer using Ibis over Pandas/@DataPolars ( bdw I still use Polars or Data Fusion as the engine ) - @IbisData is lightweight and directly executes queries on the underlying databases, functioning more as a result transporter than a heavy framework. -
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The other popular choices are Confidence and Ambrosia. They slightly differ in features: tea-tasting covers some methods not covered in these packages, and vice versa. Ultimately, tea-tasting aims to cover all the essential methods. But the biggest difference is the support for
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I’ve been really impressed with @IbisData so far. Modern data stacks need to be flexible passing data between @PostgreSQL, dataframes, and analytics dbs like @duckdb or @ClickHouseDB. Super helpful to have one common query language connecting these data sources
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Are you at the #positconf ? Join @cpcloudy tomorrow Wednesday 14th at 2pm PT in the session "It's R And Python, Not R Or Python" and learn how the do we test 20 query engines on every commit in CI in the @IbisData project repo. https://t.co/8w2Oz5NsCU
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