4.3 Introduction of MATPLOTLIB

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 Introduction of  MATPLOTLIB: -

  • Matplotlib is a popular Python library used for creating visualizations, including plots and graphs.
  • Though Matplotlib is mainly for plotting, it can also help in generating sample data for visualization using functions like numpy integration.
  • Generating data allows you to simulate real-world data for testing and analysis.
  • To use Matplotlib for plotting and data generation, we usually import:

  • numpy is used to generate numeric data like arrays, random numbers, or sequences.

 

Installing MatPlotLib: -

  • Matplotlib can be installed by using command py -m pip install matplotlib

Plotting with PYPLOT: -

  • Matplotlib is a Python library for creating 2D plots and graphs.
  • Pyplot is a submodule of Matplotlib that provides a Matlab-like interface for plotting.
  • Using Pyplot, we can create line plots, scatter plots, bar charts, histograms, and more.
  • To use Pyplot, we import


  • Often, numpy is imported to generate or manage numeric data:



  • Basic plotting can be as follows:

            1. Creating a Simple Line Plot: -

                A line plot can be created using plt.plot( ):



                    plt.show( ) is used to display the plot.

                    We can Titles and axis labels improve plot readability:



                Example: -


                Output: -



                2. Creating multiple Line Plots: -

                        We can plot multiple lines on same axis

                        Example: -

    


                Output: -



               3. Creating Plotting Line Graph: -

                    The line graph is on e of the charts which shows the information as a series of the line.

                    The graph is plotted by the plot( ) function.

                     Example: -


                    Output: -




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