NumPy is widely used for scientific computing in Physics, Chemistry, Biology, Astronomy, data analysis, machine learning, Natural Language Processing, and many more disciplines.
NumPy integrates seamlessly with other popular Python libraries such as SciPy, Pandas, and Matplotlib, facilitating streamlined workflows in data analysis and scientific computing.
As an example, NumPy is used in Physics for Modeling physical systems, simulations. In Biology, Numpy has applications in Data Analysis and bioinformatics.
The next few pages show a few examples of how NumPy can be used in various scientific calculations,
Physics
- Atmospheruc pressure exponential decay with altitude
- 2-dimension kinematics (projectile)
- Newton’s Universal Law of Gravitation
Chemistry
- Nuclear Chamistry: radioactive isotope decay with time illustrating the concept of half-life
- Relation between pH and H+ Ion Concentration
Finance
- Compound interetst calculation at different interest rates
