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
11.
Random Number Generation
11.1.
Random Module Overview
11.1.1.
Legacy RandomState
11.1.2.
New Generator API
11.1.3.
Default Random Number Generator
11.2.
Simple Random Data
11.2.1.
random()
11.2.2.
rand()
11.2.3.
randn()
11.2.4.
randint()
11.2.5.
random_integers()
11.3.
Array Sampling and Permutation
11.3.1.
choice()
11.3.2.
shuffle()
11.3.3.
permutation()
11.4.
Probability Distributions
11.4.1.
Continuous Distributions
11.4.1.1.
uniform()
11.4.1.2.
normal()
11.4.1.3.
exponential()
11.4.1.4.
gamma()
11.4.1.5.
beta()
11.4.1.6.
chi2()
11.4.1.7.
f()
11.4.1.8.
t()
11.4.2.
Discrete Distributions
11.4.2.1.
binomial()
11.4.2.2.
poisson()
11.4.2.3.
geometric()
11.4.2.4.
hypergeometric()
11.4.2.5.
negative_binomial()
11.5.
Random Generator Control
11.5.1.
Seeding
11.5.1.1.
seed()
11.5.1.2.
SeedSequence
11.5.2.
Random State Management
11.5.3.
Reproducibility
11.6.
Multivariate Distributions
11.6.1.
multivariate_normal()
11.6.2.
multinomial()
11.6.3.
dirichlet()
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12. File Input and Output