Scipy library in Python for data science:

Scipy is the short form of scientific python. Scipy is built on top of Numpy and like Numpy, Scipy is also a open source library. Scipy solves complex and time consuming mathematical problems very easily.

Sub packages of Scipy:

scipy.constants - Mathematical and Physical constants

scipy.cluster -Cluster algorithms

scipy.fftpack - Fourier transform

scipy.integrate - Integration

scipy.interpolate - Interpolation

scipy.io - Data input and output

scipy.linalg -Linear algebra

scipy.optimize -Optimization

scipy.signal -Signal processing

scipy.ndimage -n dimensional image

scipy.sparse -Matrices

scipy.special -Mathematical special function

scipy.stats -Statistics

Examples for Scipy sub packages:

1) Scipy constants:

From constants sub pakages constants related to metric, binary, mass, angle, time, length, pressure, volume, speed, temperature, energy, power, force can be retrieved.

 

Scipy constants

2) Scipy.fftpack- Fourier transform

Fourier transformation sub package is used in signal processing, image processing and noise processing.

 

scipy fft pack

3) Scipy.integrate- Integration

There are many types of functions which can be integrated using this sub package.

quad - Single integration

dblquad - Double integration

tplquad -Triple integration

nquad -n-fold multiple integration

 

scipy integrate sub package

4) scipy.linalg-Linear algebra

This linalg sub package is used to solve linear equations. For example let us consider the following equations

3x+7y=9

2x+5y=8

Here the coefficients of the unknown variables are taken as an array and the right side value is taken as an array

 

scipy linear algebra sub package