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• Graphical Technique: Graphs are commonly used to visualise statistical data using points, lines, dots, and other
                 geometrical shapes. The human brain is more comfortable coping with complex and massive amounts of material
                 when it is represented visually.  Data visualisation refers to the graphical or pictorial depiction of data using
                 graphs, charts, and other tools.


                               Task                                                   #Creativity and Innovativeness



                   Visit https://datavizcatalogue.com/ and study the different types of charts available.
                   The Data Visualisation Catalogue is a project developed by Severino Ribecca to create a (non-
                   code-based) library of different information visualisation types. The website serves as a learning
                   and inspiration resource for those working with data visualisation.



                      Introduction to Matplotlib


              The purpose of data visualisation is to simplify the interpretation of complex data. Visualisation in Python can be
              accomplished using the Matplotlib library. This extensive library enables the creation of various plots, such as line
              plots, bar charts, histograms, scatter plots, and more. Matplotlib is highly customisable, giving users detailed control
              over the appearance of the plots. The ‘pyplot,’ submodule of Matplotlib, offers an interface like MATLAB and includes
              numerous convenient functions that simplify the process of creating basic plots.
              Install Matplotlib library in Python by giving the following command:

                pip install matplotlib
                or
                python – m pip install – U matplotlib
              While writing a Python program, we import the pyplot module of matplotlib library by giving the following command:

                import matplotlib.pyplot
              Some of the common functions of Matplotlib library with their descriptions is given below:

                 Function Name                       Description

                 title( )                            Adds title to the chart/graph

                 xlabel( )                           Gives label for x-axis

                 ylabel( )                           Gives label for y-axis
                 xlim( )                             Gives the value limit for x-axis

                 ylim( )                             Gives the value limit for y-axis

                 xticks( )                           Places the tick marks on the x-axis
                 yticks( )                           Places the tick marks on the y-axis

                 show( )                             Displays the graph on the screen

                 savefig("address")                  Saves the graph to the given address
                 figure(figsize = value in tuple   Sets the size of the plot where the graph is drawn. Values should be
                                                          format) supplied in tuple format to the figsize attribute, which is passed as an
                                                     argument.

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