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  v   Plotting with pandas: -                     Example: -                     Output: -

Plotly: - Plotly is a powerful and interactive plotting library in Python. Unlike Matplotlib, Plotly allows users to zoom, pan, hover, and interact with plots in real-time. It can create a wide variety of plots: line, scatter, bar, pie, bubble, 3D plots, maps, and dashboards.   Plotly can be installed using pip: py -m pip install plotly Modules of plotly are Plotly Express and Plotly Graph Objects. Plotly Express is a python visualization library for creating interactive and beautiful visualizations. it is used to produce professional and easy plots. Plotly Graph Objects are used to produce more complex plots than that of Plotly Express. Key Features of Plotly: - Interactive plots: Hover over points to see values, zoom into regions, or click legend items. Web-friendly: Plots can be embedded in web apps (e.g., using Dash). Multiple chart types: Supports advanced visualizations like 3D surfaces, choropleth maps, sunburst charts. Integration with Pandas: Directly plot Data...

  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...