Effective Python for Data Scientists
Efficient Python Tricks and Tools for Data Scientists
1. How to Read This Book
2. Python Built-in Methods
2.1. String
2.2. Number
2.3. List
2.3.1. Good Practices
2.3.2. Get Elements
2.3.3. Unpack Iterables
2.3.4. Join Iterables
2.3.5. Interaction Between 2 Lists
2.3.6. Apply Functions to Elements in a List
2.4. Tuple
2.5. Dictionary
2.6. Function
2.7. Classes
2.8. Datetime
2.9. Best Practices
2.10. Code Speed
3. Python Built-in Libraries
3.1. Collections
3.2. Itertools
3.3. Functools
3.4. Operator
3.5. Typing
4. Pandas
4.1. Change Values
4.2. Get Values
4.3. Testing
5. NumPy
5.1. NumPy
6. Data Science Tools
6.1. Feature Extraction
6.2. Get Data
6.3. Manage Data
6.4. Machine Learning
6.5. Natural Language Processing
6.6. Time Series
6.7. Sharing and Downloading
6.8. Tools to Speed Up Code
6.9. Visualization
6.10. Tools for Best Python Practices
6.11. Better Pandas
6.12. Testing
7. Cool Tools
7.1. Alternative Approach
7.2. Workflow Automation
7.3. Code Review
7.4. Better Outputs
7.5. Git and GitHub
7.6. Environment Management
8. Jupyter Notebook
8.1. Jupyter Notebook
9. Insights From Data
9.1. Find Top Most Popular Languages
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2.3.
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2.2.
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2.3.1.
Good Practices
