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@pandas_dev

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270

Official account of the pandas project

Joined July 2018
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@pandas_dev
pandas
1 month
We're happy to announce the release of #pandas 2.3.0. You can install it with `pip install pandas` or `conda install -c conda-forge pandas`. Thanks to all contributors and sponsors who made this release possible! The release notes can be found at:
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@pandas_dev
pandas
9 months
Hey we're the fastest at writing 2300 Parquet files, we can do it in 0 minutes!. Oh, wait.
@mim_djo
Mim
9 months
#duckdb parquet writer is embarrassingly fast.
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@pandas_dev
pandas
1 year
RT @ThiagoTDotCom: For a second I thought this headline was about @pandas_dev and was like HELLSSS YEAH!. https://t….
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@pandas_dev
pandas
1 year
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:
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@pandas_dev
pandas
1 year
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:
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@pandas_dev
pandas
1 year
RT @datapythonista: How fast can a CSV file be processed? I explain in detail comparing many options such as @pandas_dev, @duckdb, @DataPol….
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@pandas_dev
pandas
1 year
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:
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@pandas_dev
pandas
2 years
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:
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@pandas_dev
pandas
2 years
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:
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@pandas_dev
pandas
2 years
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:.
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@pandas_dev
pandas
2 years
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!.
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@pandas_dev
pandas
2 years
Can #pandas be lazy?. There has been some discussion and a proof of concept about it recently.
@AMAZlNGNATURE
Nature is Amazing ☘️
2 years
breakfast
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@pandas_dev
pandas
2 years
RT @kylebarron2: @feliparagao I can't answer that: read the source code of every project you find interesting!. For me I was a @pandas_dev….
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@pandas_dev
pandas
2 years
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.
@CaioLCastro
Caio L. de Castro
2 years
@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.
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@pandas_dev
pandas
2 years
#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.
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@pandas_dev
pandas
2 years
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!.
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@pandas_dev
pandas
2 years
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.
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@pandas_dev
pandas
2 years
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.
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@pandas_dev
pandas
2 years
We are better than SQL. Except when SQL is better.
@notlinear1
notlinear
2 years
am i the only one who likes both pandas and SQL.
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@pandas_dev
pandas
2 years
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.
@marktenenholtz
Mark Tenenholtz
2 years
I love GPT-4 code assistant but it uses .apply() for every bit of pandas code and I ain't about it.
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