SciPy has the number of sub-packages for the various scientific computing domains. The following table is given below:
| Sr. |
Sub-Package |
Description |
| 1. |
scipy.cluster |
Cluster algorithms are used to vector quantization/ Kmeans. |
| 2. |
scipy.constants |
It represents physical and mathematical constants. |
| 3. |
scipy.fftpack |
It is used for Fourier transform. |
| 4. |
scipy.integrate |
Integration routines |
| 5. |
scipy.interpolation |
Interpolation |
| 6. |
scipy.linalg |
It is used for linear algebra routine. |
| 7. |
scipy.io |
It is used for data input and output. |
| 8. |
scipy.ndimage |
It is used for the n-dimension image. |
| 9. |
scipy.odr |
Orthogonal distance regression. |
| 10. |
scipy.optimize |
It is used for optimization. |
| 11. |
scipy.signal |
It is used in signal processing. |
| 12. |
scipy.sparse |
Sparse matrices and associated routines. |
| 13. |
scipy.spatial |
Spatial data structures and algorithms. |
| 14. |
scipy.special |
Special Function. |
| 15. |
scipy.stats |
Statistics. |
| 16. |
scipy.weaves |
It is a tool for writing. |
Here, we described the brief introduction of the SciPy subpackages. We will learn about these packages in further tutorial.
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