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# How to generate scatter plot using Python and Seaborn package

A scatter plot is a way to visualize data by plotting individual data points on a graph. The x-axis and y-axis of the graph represent the two variables of the data, and the data points are plotted at the intersection of their values. Scatter plots are useful for showing the relationship between two variables and identifying any patterns or trends in the data.

In Python, you can use the Seaborn library to create scatter plots. Seaborn is a data visualization library built on top of matplotlib. It provides a simple and easy-to-use interface for creating a wide range of statistical graphics, including scatter plots.

To generate a scatter plot using Seaborn, you first need to install the library by running `pip install seaborn`

in your command line.

Once Seaborn is installed, you’ll need to import it and other necessary libraries. For example:

`sns.scatterplot(x,y)`

You can also customize your scatter plot using various parameters. For example, you can change the color of the points or add a title to the plot.

```
sns.scatterplot(x, y, hue=x, style=y, size=y*20)
plt.title("Scatter Plot")
```

You can also create scatter plots using `scatter()`

function from matplotlib.pyplot which is the base library of seaborn.

By using these simple steps, you can generate scatter plots using Python and Seaborn package. With Seaborn, you can easily create scatter plots that effectively communicate information about the relationship between two variables in your data.

In this Learn through Codes example, you will learn: How to generate scatter plot using Python and Seaborn package.

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