UsefulLinks
Computer Science
Data Science
NumPy Library
1. Introduction to NumPy
2. The NumPy ndarray Object
3. Data Types in NumPy
4. Array Creation Techniques
5. Indexing and Slicing
6. Array Manipulation and Reshaping
7. Universal Functions (ufuncs)
8. Array Aggregation and Statistics
9. Broadcasting
10. Linear Algebra Operations
11. Random Number Generation
12. File Input and Output
13. Advanced NumPy Features
14. NumPy Ecosystem Integration
15. Best Practices and Common Pitfalls
5.
Indexing and Slicing
5.1.
Basic Indexing
5.1.1.
Single Element Access
5.1.1.1.
1-D Array Indexing
5.1.1.2.
Multi-dimensional Indexing
5.1.1.3.
Negative Indexing
5.1.2.
Multiple Element Access
5.1.2.1.
Tuple Indexing
5.1.2.2.
Ellipsis Usage
5.2.
Basic Slicing
5.2.1.
Slice Notation
5.2.1.1.
start:stop:step Syntax
5.2.1.2.
Default Values
5.2.2.
1-D Array Slicing
5.2.3.
Multi-dimensional Slicing
5.2.3.1.
Row Slicing
5.2.3.2.
Column Slicing
5.2.3.3.
Submatrix Extraction
5.2.4.
Slice Assignment
5.3.
Advanced Indexing
5.3.1.
Boolean Array Indexing
5.3.1.1.
Creating Boolean Masks
5.3.1.2.
Conditional Selection
5.3.1.3.
Combining Multiple Conditions
5.3.1.4.
Boolean Assignment
5.3.2.
Integer Array Indexing
5.3.2.1.
Fancy Indexing Basics
5.3.2.2.
Multi-dimensional Fancy Indexing
5.3.2.3.
Combining with Slicing
5.3.2.4.
Index Arrays and Broadcasting
5.4.
Views vs. Copies
5.4.1.
Understanding Views
5.4.2.
When Copies are Created
5.4.3.
Explicit Copy Creation
5.4.4.
Memory Implications
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4. Array Creation Techniques
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6. Array Manipulation and Reshaping