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PyPI · #3798 most downloaded on PyPI
Modin: Make your pandas code run faster by changing one line of code.
Last release 1 years ago
02 Oct 2025
Ships unpredictably
gaps range from 2 weeks to 8 months
Most releases are documented
notes for 51 of the last 60 stable releases
1 version withdrawn
withdrawn after publishing
8 years old
110 releases · first in 2018
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One column per quarter.
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This release updates the pandas version and fixes some minor bugs.
This release updates the pandas version and fixes some minor bugs.
fill_value parameter for DataFrame.sub, other binary ops (#1109)The following users contributed code to Modin since the last release.
@gshimansky (Maintainer) @devin-petersohn (Maintainer)
🎉🎉 Thank you! 🎉🎉
In this release we focused on improving testing infrastructure and fixing outstanding bugs. One particular longstanding bug with the Dask runtime, rel
In this release we focused on improving testing infrastructure and fixing outstanding bugs. One particular longstanding bug with the Dask runtime, related to serialization, was fixed (#1096). This revealed an oppourtinity for more optimization when it comes to serialization within the repository.
as_index=False for DataFrame.groupby (#1041)The following users contributed code to Modin since the last release.
@elonp (First time contributor) ⭐️ @KevOBrien (First time contributor) ⭐️ @devin-petersohn (Maintainer)
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Fix DeprecationWarning: invalid escape sequence \d
Modin 0.7 comes with the largest expansion of the API since the first release. Modin now supports over 83% of the pandas API, up from 71% last release. A number of long awaited features have been implemented to include: I/O support for Dask for parquet and other column stores and groupby with a list of column names.
CategoricalDtype dtypes (#889)read_csv (#899)__array_prepare__ from Series API (#900)df.squeeze when axis=0 on a 1x1 dataframe (#902)skiprows logic for read_csv (#918)apply when args is set (#953)count when numeric_only=False (#1002)loc where slice on columns only threw Exception (#1024)DataFrame.at_time and Series.at_time (#991)between_time for Series and `DataFram… (#992)combine for Series and DataFrame (#995)combine_first for DataFrame and `Seri… (#996)droplevel for Series and DataFrame (#1000)assign for DataFrame (#998)first for Series and DataFrame (#1006)last for DataFrame and Series (#1007)swapaxes for DataFrame and Series (#1010)tz_convert for Series and DataFrame (#1013)tz_localize for Series and DataFrame (#1014)tshift (#1016)swaplevel for Series and DataFrame (#1018)reorder_levels for DataFrame and Series (#1022)take for Series and DataFrame (#1020)truncate for Series and DataFrame (#1026)n_workers for Dask from default to number of cores (#965)py (#935)pure=False for Dask Client.submit and hash=False for `… (#957)The following users contributed code to Modin since the last release.
@ecoughlan (First time contributor) ⭐️ @aeroaks (First time contributor) ⭐️ @eavidan (Returning contributor) 🌟 @devin-petersohn (Maintainer)
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Deprecate Travis CI in favor of GitHub Actions
The 0.6.3 release comes with several bugfixes and code quality improvements. Notably, the CI was moved to GitHub Actions for faster test completion time and better developer experience. There were also new additions to Modin functionality: level argument for any and all and new implementation for Dask readers with read_csv and read_json.
None (#838)map and apply over a Series that contains list values (#840)get_dummies (#845)astype (#870)read_csv and read_json. (#861)The following users contributed code to Modin since the last release.
@rliu4439 (First time contributor) ⭐️ @smola (First time contributor) ⭐️ @RehanSD (Returning contributor) 🌟 @devin-petersohn (Maintainer)
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This release contains a large number of new functionality for our internal Modin DataFrame abstraction, as well as many backend enhancements that dram
This release contains a large number of new functionality for our internal Modin DataFrame abstraction, as well as many backend enhancements that dramatically improve performance.
We attempted to update to the latest version of Ray, but due to some API changes and changes in behavior, we had to revert that change until we can verify that this version of Ray will work with the large memory workloads of Modin.
modin_frame.filter_full_axis and update query and dropna to use (#815)concat when the axes and partitioning is aligned (#818)head, tail, etc. (#819)quantile to list of Reductions (#826)The following users contributed code to Modin since the last release.
@williamma12 (Maintainer) @devin-petersohn (Maintainer)
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This release includes several bugfixes and improvements to the backend. It also fixes support for windows users and adds new install targets. See the
This release includes several bugfixes and improvements to the backend. It also fixes support for windows users and adds new install targets. See the README for more information.
names values for groupby on MultiLevelIndex (#788)Series.map to support dictionary of operations and support (#787)groupby + reduce for partitions with only 1 row (#795)DataFrame.apply when the result of the apply is a Series (#796)any() in groupby.py to accept arguments (#802)The following users contributed code to Modin since the last release.
@sbrugman (First time contributor) 🌟 @xrmx (First time contributor) 🌟 @rliu4439 (First time contributor) 🌟 @williamma12 (Maintainer) @devin-petersohn (Maintainer)
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This release contains a large number of internal changes and some new functionality. Notably, a Dask backend for Windows support was added, and the pa
This release contains a large number of internal changes and some new functionality. Notably, a Dask backend for Windows support was added, and the pandas version was updated to 0.25.1. There were a number of minor bugfixes as well. The entire backend was refactored in #721 to support future additions easier and query planning.
We also dropped Python2 support while updating to the newest pandas version. pandas is no longer supporting Python2, so we will not as well.
groupby (#773)map_full_axis style functions to fold (#769)The following users contributed code to Modin since the last release.
@loopyme (First time contributor) 🌟 @agardelein (First time contributor) 🌟 @anthonyhsyu (First time contributor) 🌟 @dulinda (Returning contributor) @RehanSD (Returning contributor) @simon-mo (Maintainer) @williamma12 (Maintainer) @devin-petersohn (Maintainer)
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This release contains many performance enhancements and minor bugfixes. Several new features were also added this release.
This release contains many performance enhancements and minor bugfixes. Several new features were also added this release.
reset_index (#739)dot (#719)__setitem__ on new column (#701)The following users contributed code to Modin since the last release.
@dulinda (First time contributor) 🌟 @RehanSD (First time contributor) 🌟 @williamma12 (Maintainer) @devin-petersohn (Maintainer)
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This release includes several fixes to regressions and documentation. We also have preliminary support for an autoscaling cluster (#661). Performance
This release includes several fixes to regressions and documentation. We also have preliminary support for an autoscaling cluster (#661). Performance groupby + sum, count, and other dimension reducing operations was increased by up to 10x from the previous implementation (#659).
usecols when the string name of the column is provided (#652)sort_values after transpose (#679)concat when QueryCompiler is transposed (#681)concat with all Series and axis=1 (#684)The following users contributed code to Modin since the last release.
@williamma12 (Committer) @devin-petersohn (Admin)
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This release is a hotfix for a bug/regression introduced in 0.5.1.
This release is a hotfix for a bug/regression introduced in 0.5.1.
This release includes performance improvements for indexing (loc, iloc, etc.) and some minor bugfixes.
This release includes performance improvements for indexing (loc, iloc, etc.) and some minor bugfixes.
usecols when header=None (#622)loc (#635)step=None (#614)apply error checking for functions that require certain types (#617)The following users contributed code to Modin since the last release.
@ddutt (First time contributor) 🌟 @williamma12 (Committer) @devin-petersohn (Admin)
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This release includes many major new features and updates.
This release includes many major new features and updates.
read_table when sep=False (#547)read_csv when parse_dates and index_col are the same (#548)repr was not correct after mapreduce operation (#552)reset_index when name field of the index is set (#553)read_fwf (#561)datetime to top level API. issue: #542 (#564)concat to accept non-subscriptable objects as keys parameter (#568)level parameter in groupby (#575)astype with "category" as the type passed (#587)QueryCompiler.view to use index-based lookup (#566)sqlalchemy import statement in experimental io (#498)reindex after a transpose (#600)The following users contributed code to Modin since the last release.
@ipacheco-uy (First time contributor) 🌟 @pcmoritz (First time contributor) 🌟 @wuisawesome (First time contributor) 🌟 @williamma12 (Committer) @eavidan (Committer) @devin-petersohn (Admin)
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Nothing published for this version
This release includes many minor bugfixes and an update to pandas 0.24.
This release includes many minor bugfixes and an update to pandas 0.24.
drop_duplicates (#466)include="all" (#486)to_sql() (#461)The following users contributed code to Modin since the last release.
@aglove2189 (First time contributor) 🌟 @williamma12 (Committer) @eavidan (Committer) @devin-petersohn (Admin)
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This is a release candidate. Please test with existing workflows to ensure correctness.
This is a release candidate. Please test with existing workflows to ensure correctness.
drop_duplicates (#466)to_sql() (#461)The following users contributed code to Modin since the last release.
@williamma12 (Committer) @eavidan (Committer) @devin-petersohn (Admin)
🎉🎉 Thank you! 🎉🎉
This release contains a few minor bugfixes and code reformatting. It also includes some enhancements for the user and improved testing.
This release contains a few minor bugfixes and code reformatting. It also includes some enhancements for the user and improved testing.
read_hdf() support to 'fixed' format (#440)DataFrame.drop_duplicates (#433)The following users contributed code to Modin since the last release.
@igorborgest (New contributor) 🔰 @Kopurlso (Returning contributor) 🌟 @eavidan (Committer) @devin-petersohn (Admin)
🎉🎉 Thank you! 🎉🎉
This release came with a lot of bugfixes, new features, and performance enhancements. Notably, you can now use Modin out of core to use larger-than-me
This release came with a lot of bugfixes, new features, and performance enhancements. Notably, you can now use Modin out of core to use larger-than-memory DataFrames with a pandas API! We have also set up an easier way to report bugs, simply email bug_reports@modin.org or feature_requests@modin.org to report bugs or request features. Modin also now supports Dask Delayed as a backend!
loc, iloc, and __getitem__ (#295, #294)__repr__ bugfix (#299)exclude parameter in the remote partition (#321)get_indices (#348)io module (#283)data_management (#290)The following users contributed code to Modin since the last release.
@coobas (New contributor) 🔰 @pcahyna (New contributor) 🔰 @Kopurlso (Returning contributor) 🌟 @eavidan (Committer) @osalpekar (Committer) @williamma12 (Committer) @devin-petersohn (Admin)
🎉🎉 Thank you! 🎉🎉
Nothing published for this version
Updated internal Ray API calls to reflect their API changes
read_table is now supported (#270)read_hdf is now parallelized (#264)The following users contributed code to Modin since the last release.
@janpipek (New contributor) 🔰 @eavidan (Returning contributor) 🌟 @osalpekar (Committer) @williamma12 (Committer) @devin-petersohn (Admin)
🎉🎉 Thank you! 🎉🎉
Fix redis and ray.init re-initialization error.
Fix redis and ray.init re-initialization error.
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Bugfixes and minor refactoring.
Bugfixes and minor refactoring.
Significant improvements in memory overhead. Rewrite of the backend of the system.
Significant improvements in memory overhead. Rewrite of the backend of the system.
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Minor bugfixes and performance improvements
Minor bugfixes and performance improvements
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