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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
Advanced NumPy Features
Structured Arrays
Creating Structured Arrays
dtype Definition
Field Names and Types
Nested Structures
Accessing Structured Data
Field Access
Multi-field Selection
Record Arrays
Operations on Structured Arrays
Sorting by Fields
Field Manipulation
Memory Layout and Performance
Array Memory Layout
C-order vs. Fortran-order
Strides and Memory Access
flags Attribute
Performance Optimization
Contiguous Arrays
Cache-friendly Operations
In-place Operations
out Parameter Usage
Memory Views
View vs. Copy Distinction
Creating Views
Shared Memory Implications
Advanced Indexing Techniques
Multi-dimensional Advanced Indexing
Index Broadcasting
Combining Index Types
Performance Implications
Masked Arrays
numpy.ma Module
Creating Masked Arrays
Masked Array Operations
Handling Invalid Data
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