Mission 🚀

To provide 100 Python Datatable exercises over different sections structured as a course or tutorials to teach and learn for beginners, intermediates as well as experts.

Datatable

The datatable package in Python is a library for efficient data processing, feature engineering and simple modelling of tabular data. It is synonymous with R's data.table library and heavily inspired by it.

It closely resembles pandas but is more focused on speed and multi-threaded data operations being particularly useful on large datasets.

Exercises 📖

There are a total of 100 datatable exercises divided into 10 sets of Jupyter Notebooks with 10 exercises each. It is recommended to go through the exercises in order but you may start with any set depending on your expertise.

✅ Structured as exercises & tutorials - Choose your style
✅ Suitable for beginners, intermediates & experts - Choose your level
✅ Available on Colab, Kaggle, Binder & GitHub - Choose your platform

The exercises are best experienced using datatable's v1.0.0 (Released on 1st July, 2021) & above but recommended to use the latest available version.

Set 01 • Datatable Introduction • Beginner • Exercises 1-10

Style	Colab	Kaggle	Binder	GitHub
Exercises
Solutions

Set 02 • Files and Formats • Beginner • Exercises 11-20

Style	Colab	Kaggle	Binder	GitHub
Exercises
Solutions

Set 03 • Data Selection • Beginner • Exercises 21-30

Style	Colab	Kaggle	Binder	GitHub
Exercises
Solutions

Set 04 • Frame Operations • Beginner • Exercises 31-40

Style	Colab	Kaggle	Binder	GitHub
Exercises
Solutions

Set 05 • Column Aggregations • Beginner • Exercises 41-50

Style	Colab	Kaggle	Binder	GitHub
Exercises
Solutions

Set 06 • Grouping Methods • Intermediate • Exercises 51-60

Style	Colab	Kaggle	Binder	GitHub
Exercises
Solutions

Set 07 • Multiple Frames • Intermediate • Exercises 61-70

Style	Colab	Kaggle	Binder	GitHub
Exercises
Solutions

Set 08 • Time Series • Intermediate • Exercises 71-80

Style	Colab	Kaggle	Binder	GitHub
Exercises
Solutions

Set 09 • Native FTRL • Expert • Exercises 81-90

Style	Colab	Kaggle	Binder	GitHub
Exercises
Solutions

Set 10 • Capstone Projects • Expert • Exercises 91-100

Style	Colab	Kaggle	Binder	GitHub
Exercises
Solutions

The Jupyter Notebooks can also be run locally by cloning the repo and running on your local jupyter server.

git clone https://github.com/vopani/datatableton.git
python3 -m pip install notebook
jupyter notebook

P.S. The notebooks will be periodically updated to improve the exercises and support the latest version.

Contribution 🛠️

Please create an Issue for any improvements, suggestions or errors in the content.

You can also tag @vopani on Twitter for any other queries or feedback.

Credits 🙏

Collaborators

• parulnith
• shrinidhin

Datatable

• Project
• Documentation

License 📋

This project is licensed under the Apache License 2.0.