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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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