Scipy library in Python for data science:

 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



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

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