Creating BARPLOT using SEABORN in PYTHON

Bar charts are one of the most common and useful ways to visualize data. They allow us to easily compare different categories or groups by displaying data as rectangular bars with lengths proportional to the values they represent. Bar charts are frequently used in scientific research, business, and other fields to display data in a clear and intuitive way.

In this tutorial, we'll be using the Seaborn library in Python to create a bar chart. Seaborn is a powerful data visualization library that is built on top of Matplotlib, another popular Python library for data visualization. Seaborn provides a high-level interface for creating beautiful and informative statistical graphics, making it an excellent tool for data scientists and analysts who want to create compelling visualizations with minimal code.

Before we dive into the specifics of using Seaborn, let's take a closer look at what a bar chart is and why it's useful. A bar chart is a type of chart that displays data using rectangular bars with lengths proportional to the values they represent. The bars are usually arranged vertically or horizontally, depending on the orientation of the chart. Bar charts are useful for comparing data across different categories or groups, as they make it easy to see which categories have higher or lower values.

There are many different types of bar charts, including stacked bar charts, clustered bar charts, and grouped bar charts. Each type of bar chart has its own strengths and weaknesses, and choosing the right type of chart depends on the specific data and the story you want to tell with your visualization. In this tutorial, we'll be focusing on creating a basic vertical bar chart using Seaborn.

To get started, we'll need to import the Seaborn library and load our data. Seaborn comes with a number of built-in datasets, so we can easily load one of these to use