To provide 100 datatable exercises over different sections structured as a course or tutorials to teach and learn for beginners, intermediates as well as experts.
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.
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.
Style | Colab | Kaggle | Binder | GitHub |
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Exercises | ||||
Solutions |
Style | Colab | Kaggle | Binder | GitHub |
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Exercises | ||||
Solutions |
Style | Colab | Kaggle | Binder | GitHub |
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Exercises | ||||
Solutions |
Style | Colab | Kaggle | Binder | GitHub |
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Exercises | ||||
Solutions |
Style | Colab | Kaggle | Binder | GitHub |
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Exercises | ||||
Solutions |
Style | Colab | Kaggle | Binder | GitHub |
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Exercises | ||||
Solutions |
Style | Colab | Kaggle | Binder | GitHub |
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Exercises | ETA: 22nd July, 2021 | ETA: 22nd July, 2021 | ETA: 22nd July, 2021 | ETA: 22nd July, 2021 |
Solutions | ETA: 22nd July, 2021 | ETA: 22nd July, 2021 | ETA: 22nd July, 2021 | ETA: 22nd July, 2021 |
Style | Colab | Kaggle | Binder | GitHub |
---|---|---|---|---|
Exercises | ETA: 25th July, 2021 | ETA: 25th July, 2021 | ETA: 25th July, 2021 | ETA: 25th July, 2021 |
Solutions | ETA: 25th July, 2021 | ETA: 25th July, 2021 | ETA: 25th July, 2021 | ETA: 25th July, 2021 |
Style | Colab | Kaggle | Binder | GitHub |
---|---|---|---|---|
Exercises | ETA: 28th July, 2021 | ETA: 28th July, 2021 | ETA: 28th July, 2021 | ETA: 28th July, 2021 |
Solutions | ETA: 28th July, 2021 | ETA: 28th July, 2021 | ETA: 28th July, 2021 | ETA: 28th July, 2021 |
Style | Colab | Kaggle | Binder | GitHub |
---|---|---|---|---|
Exercises | ETA: 31st July, 2021 | ETA: 31st July, 2021 | ETA: 31st July, 2021 | ETA: 25th July, 2021 |
Solutions | ETA: 31st July, 2021 | ETA: 31st July, 2021 | ETA: 31st July, 2021 | ETA: 31st July, 2021 |
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.
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.
This project is licensed under the Apache License 2.0.