xgboost_ray VS swifter

Compare xgboost_ray vs swifter and see what are their differences.


Distributed XGBoost on Ray (by ray-project)


A package which efficiently applies any function to a pandas dataframe or series in the fastest available manner (by jmcarpenter2)
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xgboost_ray swifter
1 3
118 2,346
5.1% -
6.0 0.0
11 days ago 2 months ago
Python Python
Apache License 2.0 MIT License
The number of mentions indicates the total number of mentions that we've tracked plus the number of user suggested alternatives.
Stars - the number of stars that a project has on GitHub. Growth - month over month growth in stars.
Activity is a relative number indicating how actively a project is being developed. Recent commits have higher weight than older ones.
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.


Posts with mentions or reviews of xgboost_ray. We have used some of these posts to build our list of alternatives and similar projects.

We haven't tracked posts mentioning xgboost_ray yet.
Tracking mentions began in Dec 2020.


Posts with mentions or reviews of swifter. We have used some of these posts to build our list of alternatives and similar projects. The last one was on 2021-09-12.
  • Tidyverse equivalent in Python?
    4 projects | /r/datascience | 12 Sep 2021
    With concat, merge, melt, and pivot_table, that may cover everything I have ever needed. There may be more efficient ways at times, but swifter promises to do that for you, maybe it is true.

What are some alternatives?

When comparing xgboost_ray and swifter you can also consider the following projects:

modin - Modin: Scale your Pandas workflows by changing a single line of code

Dask - Parallel computing with task scheduling

mljar-supervised - Python package for AutoML on Tabular Data with Feature Engineering, Hyper-Parameters Tuning, Explanations and Automatic Documentation

pandera - A light-weight, flexible, and expressive statistical data testing library

Pandas - Flexible and powerful data analysis / manipulation library for Python, providing labeled data structures similar to R data.frame objects, statistical functions, and much more

siuba - Python library for using dplyr like syntax with pandas and SQL

d2l-en - Interactive deep learning book with multi-framework code, math, and discussions. Adopted at 500 universities from 70 countries including Stanford, MIT, Harvard, and Cambridge.

xarray - N-D labeled arrays and datasets in Python

mars - Mars is a tensor-based unified framework for large-scale data computation which scales numpy, pandas, scikit-learn and Python functions.