Examples and Resources

Here you can find additional resources to learn about Modin. To learn more about advanced usage for Modin, please refer to this section.

Usage Examples

The following notebooks demonstrate how Modin can be used for scalable data science:

• Quickstart Guide to Modin [Source]

• Using Modin with the NYC Taxi Dataset [Source]

• Modin for Machine Learning with scikit-learn [Source]

Tutorials

The following tutorials cover the basic usage of Modin. Here is a one hour video tutorial that walks through these basic exercises.

• Exercise 1: Introduction to Modin [Source PandasOnRay, Source PandasOnDask, Source HdkOnNative]

• Exercise 2: Speed Improvements with Modin [Source PandasOnRay, Source PandasOnDask, Source HdkOnNative]

• Exercise 3: Defaulting to pandas with Modin [Source PandasOnRay, Source PandasOnDask, Source HdkOnNative]

The following tutorials covers more advanced features in Modin:

• Exercise 4: Experimental Features in Modin (Spreadsheet, Progress Bar) [Source PandasOnRay, Source PandasOnDask]

• Exercise 5: Setting up Modin in a Cluster Environment [Source PandasOnRay]

• Exercise 6: Running Modin in a Cluster Environment [Source PandasOnRay]

How to get required dependencies for the tutorial notebooks and to run them please refer to the respective README.md file.

Talks & Podcasts

• Scaling Interactive Data Science with Modin and Ray (20 minute, Ray Summit 2021)

• Unleash The Power Of Dataframes At Any Scale With Modin (40 minute, Python Podcast 2021)

• [Russian] Distributed Data Processing and XGBoost Training and Prediction with Modin (30 minute, PyCon Russia 2021)

• [Russian] Efficient Data Science with Modin (30 minute, ISP RAS Open 2021)

• Modin: Scaling the Capabilities of the Data Scientist, not the Machine (1 hour, RISE Camp 2020)

• Modin: Pandas Scalability with Devin Petersohn (1 hour, Software Engineering Daily Podcast 2020)

• Introduction to the DataFrame and Modin (20 minute, RISECamp 2019)

• Scaling Interactive Pandas Workflows with Modin (40 minute, PyData NYC 2018)

Community contributions

Here are some blogposts and articles about Modin:

• Anaconda Blog: Scale your pandas workflow with Modin by Vasilij Litvinov

• The Modin view of Scaling Pandas by Devin Petersohn

• Data Science at Scale with Modin by Areg Melik-Adamyan

• Speed up Pandas using Modin by Eric D. Brown, D.Sc.

• Explore Python Libraries: Make Your DataFrames Parallel With Modin by Zachary Bennett

• Get faster pandas with Modin, even on your laptops by Parul Pandey

• How to speedup pandas by changing one line of code by Shrivarsheni

• How To Accelerate Pandas With Just One Line Of Code by Analytics India

• An Easy Introduction to Modin: A Step-by-Step Guide to Accelerating Pandas by Intel

Here are some articles contributed by the international community:

• [Chinese] 用 Modin 来提速 pandas 工作流程 by Python Chinese Community

• [German] Was ist Modin? by Dipl.-Ing. (FH) Stefan Luber

• [Russian] Ускоряем Pandas при помощи модуля modin by Разработка

• [Korean] modin 으로 pandas 더 빠르게 사용하기 by 분석뉴비

If you would like your articles to be featured here, please submit a pull request to let us know!