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• The ylabel(Text) function is used to give label to y axis.
• The title(Text) function is used to give title to a graph created.
• The grid(True)function will add a grid to the graph created. Default is True. If you want grid on x-axis the the
function will be: grid(axis = 'x')and for y axis grid(axis = 'y').
• The xticks(values) function will mark the ticks/points on the x axis.
• The yticks(values) function will mark the ticks/points on the y axis.
SciPy(Scientific Python)
SciPy is a free, open-source Python library used for scientific and technical computing. It plays a crucial role
in fields such as physics, engineering, mathematics, biology, and data science. SciPy is built on the NumPy
extension of Python, which provides support for large, multi-dimensional arrays and matrices, along with a
collection of high-level mathematical functions to operate on these arrays.
SciPy offers a wide range of modules and submodules for scientific computing. Some of the key modules
include:
• scipy.optimize: This module contains functions for solving optimization problems, such as root finding, curve
fitting, minimization, and linear programming.
• scipy.integrate: It provides methods for mathematical integration, including solving ordinary differential
equations (ODEs), differential algebraic equations (DAEs), and performing numerical quadrature.
• scipy.interpolate: This module includes functions for interpolation and approximation techniques, such as
splines, B-splines, and radial basis functions.
• scipy.linalg: This module focuses on linear algebra operations, such as matrix factorization, solving systems of
linear equations, eigenvalue problems, and singular value decomposition (SVD).
• scipy.signal: It provides functions for signal processing tasks, such as filtering, spectral analysis, convolution,
correlation, and wavelet transformations.
• scipy.stats: This module offers a wide range of statistical distributions, statistical functions, hypothesis testing
tools, and statistical modeling.
• scipy.spatial: It deals with spatial data structures and algorithms, including distance computations, clustering,
nearest neighbors, and spatial transformations.
• scipy.fftpack: This module contains functions for fast Fourier transforms (FFT) and related operations for
efficient spectral analysis.
Installing SciPy
The command that installs SciPy is:
pip install scipy
Assuming that Python and pip are already installed in the computer.
Statistical Learning with Python
Now we all have understood that Data Sciences deals with data analysis and data manipulation. But this numeric &
alpha-numeric data analysis and manipulation is not possible without the intervention of Mathematical Statistics.
Python with supported libraries like NumPy, Matplotlib etc have a lot of pre-defined functions that implement
Mathematical statistics without getting into the hassle of doing the calculations and creating the formulas or
equations to find out the results. All we need to do is write that function and pass on the data to it. It’s that simple!
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