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# Get started with Matplotlib Visualization in Python

## How to create visualizations with matplotlib in Python

In this tutorial, you will get started with Matplotlib visualization in Python. You will learn the object-oriented approach with Matplotlib, this makes it less confusing with the cost of only one more line of code.

In this tutorial, you will:

• Get started with Matplotlib: Learn the basics of Matplotlib, a popular data visualization library in Python.
• Object-Oriented Approach: Explore the object-oriented approach in Matplotlib, which simplifies the process with minimal additional code.
• Clear and Concise Visualization: Create visually appealing and informative plots using Matplotlib’s object-oriented approach.

By the end of the tutorial, you will have a solid foundation in using Matplotlib for data visualization. The object-oriented approach will streamline your workflow and help you create clear and concise visualizations with ease.

## Plot a list of numbers with Matplotlib in Python

Given a list of numbers, how can you make a connected line?

```import matplotlib.pyplot as plt
fig, ax = plt.subplots()
ax.plot([1, 2, 3, 4])
```

Which results in the following output.

The numbers do not need to be in a straight line. But the line will be connected.

## Make a Colored Scatter Plot with Matplotlib in Python

Now you need tree lists.

```import matplotlib.pyplot as plt
x = [1, 2, 3, 4, 5, 6, 4]
y = [2, 3, 2, 1, 6, 10, 3]
c = [1, 1, 2, 2, 3, 4, 4]
fig, ax = plt.subplots()
ax.scatter(x, y, c=c)
ax.set_title("Title")
ax.set_xlabel("X label")
ax.set_ylabel("Y label")
```

This results in the following plot.

Notice that we also added titles and labels to the axis.

This could also be done in the connected line plot above.

## Make a Histogram with Matplotlib

You can make a histogram as follows.

```import matplotlib.pyplot as plt
data = [1, 1, 2, 2, 1, 2, 3, 3, 2, 3, 1, 3, 2]
fig, ax = plt.subplots()
ax.hist(data, bins=4)
ax.set_title("Title")
ax.set_xlabel("X label")
ax.set_ylabel("Y label")
```

This results in the following plot.

## Pie Charts

Pie charts are a very powerful way to represent data.

• Pie charts are easy to understand.
• Pie charts are simple to show how data is divided.

Be sure to check this Pie Chart tutorial for matplotlib in Python.

In the next project you will learn NumPy Basics and Linear Regression with Python

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• 17 video lessons teaching you everything you need to know to get started with Python.
• 34 Jupyter Notebooks with lesson code and projects.
• A FREE eBook to support your Python learning.

See the full FREE course page here.

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