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Delightful Data Science
Delightful Data Science
1. Code Quality
1.1. Automation
1.2. CI/CD
1.3. Code Style
1.4. Memory Optimization
1.5. Security in Projects
1.6. Typing
1.7. Principles for Code Quality
2. Cool Tools
2.1. Cool Tools
3. Jupyter Notebook Tricks and Tips
3.1. Jupyter Notebook Tips and Tricks
4. Documentation
4.1. Documentation
5. Machine Learning
5.1. Data Augmentation
5.2. EDA
5.3. Feature Selection
5.4. Get Data
5.5. Model Training
5.6. Outlier Detection
5.7. Time Series
5.8. Preprocessing
6. LLM
6.1. LLM
7. NumPy Tips and Tricks
7.1. NumPy Tips and Tricks
8. Pandas Tricks and Tips
8.1. Pandas Tips and Tricks
8.2. Utility Libraries for Pandas
9. Polars
9.1. Polars Tips & Tricks
10. Python Tips and Tricks
10.1. Pure Python + Built-in libraries
10.2. Utilities for Python
10.3. Tooling for Python Projects
11. Scraping Tips and Tricks
11.1. Scraping Tips and Tricks
12. Terraform
12.1. Terraform
13. Testing in Python
13.1. Testing
14. SQL Tips & Tricks
14.1. SQL Tips & Tricks
15. Miscellaneous
15.1. Miscellaneous
Repository
Open issue
.ipynb
.pdf
Testing in Python
13.
Testing in Python
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