As we all know, all data science projects include three parts: retrieving data, numerical computation and result visualization. Take seismology as an example, ways for requesting seismic data from providers (IRIS, ISC and NIED etc.) are concluded here.
Thus, this post focuses on collecting serveral useful python library for general scientific numerial computation and visualization.
Visualization
| Library | Dimension | Field | Note |
|---|---|---|---|
| Matplotlib | 2D | General | - |
| seaborn | 2D | Statistics | - |
| Altair | 2D | Statistics | - |
| HoloViews | 2D | General | Extension to Matplotlib … |
| Bokeh | 2D | General | For web interative visualization |
| gmt-python | 2D | Gerneral | Efficient for plotting maps |
| GMSimViz | 3D | automation tool that produces an animated 3D visualization of geological faults, ground motion and other earthquake related data. | Depend on GMT |
Numerical computation
| Library | Note |
|---|---|
| Scipy | Includes modules for linear algebra, optimization, integration, special functions, signal and image processing, statistics, genetic algorithms, ODE solvers, and others |
| sympy | Symbolic mathematics. |
| ad | easily and transparently perform first and second-order automatic differentiation. |
| Pandas | flexible and powerful data analysis / manipulation library for Python, providing labeled data structures similar to R data. |
| PyKrige | 2D/3D kriging interpolation tool |
References
Change log
- 2019-01-07: Initial version