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.
Python's datatable package is a library for efficient data processing. It is synonymous with R's data.table library and can be used for various kinds of data processing, feature engineering and modeling tasks as part of data science pipelines.
It closely resembles pandas but is more focused on speed and multi-threaded data processing operations being particularly useful on large datasets.
There are a total of 100 datatable exercises divided into 10 sets of 10 exercises each.
✅ Structured as exercises or tutorials - Choose your style
✅ Suitable for beginners, intermediates or 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 |
|---|---|---|---|---|
| Exercises |  |
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| Solutions | |
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| Style | Colab | Kaggle | Binder | GitHub |
|---|---|---|---|---|
| Exercises | ETA: 7th July, 2021 | ETA: 7th July, 2021 | ETA: 7th July, 2021 | ETA: 7th July, 2021 |
| Solutions | ETA: 7th July, 2021 | ETA: 7th July, 2021 | ETA: 7th July, 2021 | ETA: 7th July, 2021 |
| Style | Colab | Kaggle | Binder | GitHub |
|---|---|---|---|---|
| Exercises | ETA: 10th July, 2021 | ETA: 10th July, 2021 | ETA: 10th July, 2021 | ETA: 10th July, 2021 |
| Solutions | ETA: 10th July, 2021 | ETA: 10th July, 2021 | ETA: 10th July, 2021 | ETA: 10th July, 2021 |
| Style | Colab | Kaggle | Binder | GitHub |
|---|---|---|---|---|
| Exercises | ETA: 13th July, 2021 | ETA: 13th July, 2021 | ETA: 13th July, 2021 | ETA: 13th July, 2021 |
| Solutions | ETA: 13th July, 2021 | ETA: 13th July, 2021 | ETA: 13th July, 2021 | ETA: 13th July, 2021 |
| Style | Colab | Kaggle | Binder | GitHub |
|---|---|---|---|---|
| Exercises | ETA: 16th July, 2021 | ETA: 16th July, 2021 | ETA: 16th July, 2021 | ETA: 16th July, 2021 |
| Solutions | ETA: 16th July, 2021 | ETA: 16th July, 2021 | ETA: 16th July, 2021 | ETA: 16th July, 2021 |
| Style | Colab | Kaggle | Binder | GitHub |
|---|---|---|---|---|
| Exercises | ETA: 19th July, 2021 | ETA: 19th July, 2021 | ETA: 19th July, 2021 | ETA: 19th July, 2021 |
| Solutions | ETA: 19th July, 2021 | ETA: 19th July, 2021 | ETA: 19th July, 2021 | ETA: 19th July, 2021 |
| Style | Colab | Kaggle | Binder | GitHub |
|---|---|---|---|---|
| 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 be run locally by cloning the repo and running on your local jupyter server or by clicking on the link to any of the supported platforms.
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.