Using plt.scatter() to Visualize Data in Python (Overview)
An important part of working with data is being able to visualize it. Python has several third-party modules you can use for data visualization. One of the most popular modules is Matplotlib and its submodule pyplot, often referred to using the alias plt
. Matplotlib provides a very versatile tool called plt.scatter()
that allows you to create both basic and more complex scatter plots.
In this course, you’ll learn how to:
- Create a scatter plot using
plt.scatter()
- Use the required and optional input parameters
- Customize scatter plots for basic and more advanced plots
- Represent more than two dimensions on a scatter plot
For more information about concepts covered in this lesson, you can check out:
- Python Plotting With Matplotlib (Guide) | Real Python Article
- NumPy Tutorial: Your First Steps Into Data Science in Python | Real Python Article
00:00
Visualizing Data in Python Using plt.scatter()
.
00:06
An important part of working with data is being able to visualize it. Python has several third-party modules you can use for data visualization. One of the most popular modules is Matplotlib and its submodule pyplot, often referred to using the alias plt
.
00:24
Matplotlib provides a very versatile tool called plt.scatter()
that allows you to create both basic and more complex scatter plots.
00:34
In this course, you’ll walk through several examples that will show you how to use the function effectively. You’ll learn how to create a scatter plot using plt.scatter()
, use the required and optional input parameters, customize scatter plots for basic and more advanced plots, and represent more than two dimensions on a scatter plot. To get the most out of this video course, you should be familiar with the fundamentals of Python programming and the basics of NumPy and its ndarray
object.
01:06 You don’t need to be familiar with Matplotlib to follow this course, but if you’d like to learn more about the module, then check out Python Plotting With Matplotlib.
01:16 Now that you know what you’ll be covering, let’s get started.
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