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We're happy to announce the release of #pandas 2.2.2. You can install it with `pip install pandas` or `mamba install -c conda-forge pandas`. Thanks to all contributors and sponsors who made this release possible! The release notes can be found at: pandas.pydata.org/docs/whatsnew/…
We're happy to announce the release of #pandas 2.2.1. You can install it with `pip install pandas` or `mamba install -c conda-forge pandas`. Thanks to all contributors and sponsors who made this release possible! The release notes can be found at: pandas.pydata.org/docs/whatsnew/…
How fast can a CSV file be processed? I explain in detail comparing many options such as @pandas_dev, @duckdb, @DataPolars, #Python, #R, #Rustlang and more in this new blog post: datapythonista.me/blog/how-fast-…
We're happy to announce the release of #pandas 2.2.0. You can install it with `pip install pandas` or `mamba install -c conda-forge pandas`. Thanks to all contributors and sponsors who made this release possible! The release notes can be found at: pandas.pydata.org/docs/whatsnew/…
We are excited to announce a release candidate for #pandas 2.2.0 has just been released. If all goes well, we'll release #pandas 2.2.0 in about 2 weeks. Full list of changes and contributors: pandas.pydata.org/docs/dev/whats…
We're happy to announce the release of #pandas 2.1.4. You can install it with `pip install pandas` or `mamba install -c conda-forge pandas`. Thanks to all contributors and sponsors who made this release possible! The release notes can be found at: pandas.pydata.org/docs/whatsnew/…
A new edition of the data manipulation, analysis and visualization in #python course at Ghent University by @jorisvdbossche and myself is scheduled on 29, 31 January and 2 February 2024. For more information, see shorturl.at/qDVW9 #pandas #seaborn #matplotlib
We're happy to announce the release of #pandas 2.1.2. You can install it with `pip install pandas` or `mamba install -c conda-forge pandas`. Thanks to all contributors and sponsors who made this release possible! The release notes can be found at: pandas.pydata.org/docs/whatsnew/…
We're happy to announce the release of #pandas 2.1.1. You can install it with `pip install pandas` or `mamba install -c conda-forge pandas`. You can find what's new in this version in the release notes. Thanks to all contributors and sponsors who made this release possible!
@feliparagao I can't answer that: read the source code of every project you find interesting! For me I was a @pandas_dev user, wanted to improve IO support with Stata files, and dug into the code to figure out how it worked. My first pr 🥹 github.com/pandas-dev/pan…
This is the (much more efficient) workaround which you're encouraged to use instead - nice one @CaioLCastro ! Use `concat` a single time outside the loop, rather than multiple times inside it
This is the (much more efficient) workaround which you're encouraged to use instead - nice one @CaioLCastro ! Use `concat` a single time outside the loop, rather than multiple times inside it
#pandas has two internal ways to store strings: NumPy and PyArrow (faster). pandas 3.0 will change the default and strings will use PyArrow when for example calling read_csv. You can get this change now in pandas 2.1 with: pandas.options.future.infer_string = True
We're happy to announce the release of #pandas 2.1.0. You can install it with `pip install pandas` or `mamba install -c conda-forge pandas`. You can find what's new in this version in the release notes. Thanks to all contributors and sponsors who made this release possible!
Do you know how to extend #pandas with a fast language like #rustlang? Core developer @datapythonista shows you how in this step by step tutorial at @EuroSciPy. m.youtube.com/watch?v=iUEzNm…
Is it possible to write dataframe-agnostic code that works with #pandas dataframes but also with dataframes from other libraries? Are we there yet? Core developer Marco Gorelli gives you the answer in this @EuroSciPy talk. m.youtube.com/watch?v=gAGG21…
Do you want to learn more about #pandas 2.0 and beyond? Core developers @jorisvdbossche and Richard Shadrach gave a talk about it at @EuroSciPy. youtu.be/NK7RuG4rQpI
We are better than SQL. Except when SQL is better.
Artificial intelligence may not be so intelligent if it uses pandas .apply() when not strictly necessary. Our operations are usually vectorized (very fast), .apply() is usually not, so it may be very slow. Avoid loops and apply if a pandas operation exists for what you need.
Artificial intelligence may not be so intelligent if it uses pandas .apply() when not strictly necessary. Our operations are usually vectorized (very fast), .apply() is usually not, so it may be very slow. Avoid loops and apply if a pandas operation exists for what you need.
We are excited to announce a release candidate for #pandas 2.1.0 has just been released. If all goes well, we'll release #pandas 2.1.0 in about 1 week. Full list of changes and contributors: pandas.pydata.org/docs/dev/whats…
Matt Harrison @__mharrison__
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Mike Driscoll @driscollis
118K Followers 1K Following I tweet about everything #Python Writing about Python @mousevspython @realpython Teaching at @TeachMePy Author of multiple books - https://t.co/MdP25zw5zQ
Matplotlib @matplotlib
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Peter Wang 🦋 @pwang
48K Followers 2K Following Chief AI & Co-founder @AnacondaInc; invented @pyscript_dev, @PyData @Bokeh @Datashader. Former physicist. A student of the human condition. bsky: @wang.social
Reuven M. Lerner @reuvenmlerner
27K Followers 1K Following Helping you become more confident with Python and Pandas. Corporate training. Newsletters. Courses. Books. Videos. I tweet my students' best Python questions!
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38K Followers 5K Following Associate Professor @UTKGeography | @Amazon Visiting Academic | Senior Reseach Fellow @UNUINWEH | #EarthEngine GDE | Talk about #opensource #geospatial #dataviz
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9K Followers 644 Following Constantly looking for simple ways to explain complex things in Python https://t.co/jLEyJqmURW
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86K Followers 3K Following Anaconda is the world’s most popular and trusted Python/R platform for data science, machine learning, and AI. We help people change the world. 🐍
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NumPy @numpy_team
39K Followers 11 Following Official account of NumPy. Announcements only. For questions and comments, please use the mailing list [email protected].
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35K Followers 1K Following Machine learning and language models R&D. Builder. Writer. Visualizing AI, ML, and LLMs one concept at a time. @Cohere. https://t.co/TquuQXlLOJ
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sembolizm @servermesorver
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39K Followers 11 Following Official account of NumPy. Announcements only. For questions and comments, please use the mailing list [email protected].
polars data @DataPolars
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2K Followers 2K Following studying cs/viz/@matplotlib @CSCUNYGC and @CityCollegeNY, like to ♥️ tweets. @[email protected], @story645.bsky.social
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Marc Garcia @datapythonista
1K Followers 227 Following #pandas core dev Developer, speaker, trainer, advisor #python #polars #data #rust #rustlang #arrow #apachearrow #linux
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73K Followers 748 Following A community for developers and users of open source scientific tools with 200K+ people 🧑🔬 🧑💻, by @NumFOCUS. Join our Discord: https://t.co/rmBFaQvdMM
NumFOCUS @NumFOCUS
28K Followers 1K Following Our open source scientific software projects are changing the world. We support projects like Pandas, Julia, Jupyter, & NumPy + organize @PyData!
Joris Van den Bossche @jorisvdbossche
2K Followers 136 Following Open source #python developer and teacher. Pandas, GeoPandas and Shapely maintainer. Apache Arrow at Voltron Data Labs https://t.co/Qiwr1KItuh
Jeff Reback @jreback
2K Followers 343 Following
Wes McKinney @wesmckinn
59K Followers 910 Following Principal Architect @posit_pbc, GP @ComposedVC, Co-founder @voltrondata. OSS: @ApacheArrow @pandas_dev @IbisData, "Python for Data Analysis" bookSo my issues tend to get picked up by newer contributors (& this can create problems when there isn't consensus 😓)& I'm now wondering if half the reason for this is b/c I tend to write 'em like coding assignments for undergrads b/c I did that for so many years
@story645 Rather than coding assignments I would assume that is because you provide loads of context and clear paths forward, which is usually what newer contributors lack. So kudos on mastering the art of issue writing.
When @pandas_dev maintainers address your comment 😍 github.com/pandas-dev/pan… github.com/pandas-dev/pan…
How fast can a CSV file be processed? I explain in detail comparing many options such as @pandas_dev, @duckdb, @DataPolars, #Python, #R, #Rustlang and more in this new blog post: datapythonista.me/blog/how-fast-…
Apparently it is ten years today since the first release of seaborn on PyPI 🎂
Since it's been getting attention, I tagged and released seaborn 0.1. You can get it with `pip install seaborn moss` (moss has stat utils)
@pandas_dev @CaioLCastro Concat always made more sense. No point pretending something is inplace when it's not.
@quant_arb we use a hybrid approach. Append to a list, and then concat. res = [] for x in itersomething: res.append(calculations) pd.concat(res) df.append is gruesomely inefficient so maybe it is best to remove
Beautiful 🤩
#pandas has two internal ways to store strings: NumPy and PyArrow (faster). pandas 3.0 will change the default and strings will use PyArrow when for example calling read_csv. You can get this change now in pandas 2.1 with: pandas.options.future.infer_string = True
I need to contribute to pandas starting next year.
We're happy to announce the release of #pandas 2.1.0. You can install it with `pip install pandas` or `mamba install -c conda-forge pandas`. You can find what's new in this version in the release notes. Thanks to all contributors and sponsors who made this release possible!
This tutorial is packed with info on how to create interactive #DataViz! Learn how to query #InfluxDB Cloud with Flight SQL, using @pandas_dev & @ProjectJupyter Notebooks ⬇ bit.ly/3G7Gxs9
@DataPolars is super fast but I am not sure if it can covers huge spectrum of operations which @pandas_dev has. I use both currently. Polars when speed is needed. Pandas for bigger logic operations. Thanks to both for making data analysis in #Python is so great!
Are you wondering what all the buzz is around @DataPolars, and how it compares to @pandas_dev? Check out our latest blog post, where @t_redactyl explains how Polars works under the hood, and the best use cases for this powerful new dataframe library. jb.gg/0js3bt
We are more confusing than SQL. Except when SQL is more confusing.
We are better than SQL. Except when SQL is better.
@pandas_dev In the official documentation it's fine 👌🏼
I need to start playing with this copy-on-write change. Hopefully it will resolve so many of the headaches from dealing with views or copies
#pandas 2 uses less memory if you enable copy-on-write with: pd.options.mode.copy_on_write = True Learn more about CoW from our core developer Patrick in this blog post: phofl.github.io/cow-deep-dive.… And in the official docs: pandas.pydata.org/docs/user_guid…
We are live! We just published the agenda and we have some great talks. This year we have 3 themed tracks - Classic ML, Gen AI, and ML Engineering/Ops. We also feature a keynote talk by @wesmckinn, the creator of @pandas_dev . So excited! pydata.org/telaviv2023/sc…
Aww, apology accepted. Look, we’re on the same team, at least we’re not writing JavaScript.
We'd like to apologize to @teej_m. This tweet was never meant as a personal attack, or a "fix it yourself" as many users understood. We welcome all criticism and work with the community every day to make the API better, constrained by being as backward compatible as possible.
I didn't have pandas coming for me on my 2023 bingo card but here we are
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