Gain insights into visually representing data with Matplotlib in Python. Explore plotting techniques, control axes, create complex layouts, and draw various plots, enhancing your data science skills.

For data science, Matplotlib is one of the most popular tools for representing data in a visual manner. There are many other tools, but for the Python user, Matplotlib is a must-know.

In this course, you will learn how to visually represent data in several different ways. You will learn how to use figures and axes to plot a chart, as well as how to plot from multiple types of objects and modules.

You will also discover ways to control the spine of an axes and how to create complex layouts for a figure using GridSpec so you can create visually stunning charts.

In the latter half of the course, you will focus on how to draw various types of plots, whether it be a line plot, a stem plot, or a heatmap plot. Overall, this is your no-fuss introduction to creating impactful data charts.

By the end, you will have an important new skill to add to your resume. As any data scientist knows, it is necessary that you be able to show insights found from analyzing data.

Matplotlib for Python: Visually Represent Data with Plots

# What is `pie`?

`Pie` charts are often used to highlight the proportion of categorical data in relation to the overall value of a dataset. Pie charts are shaped like a pie, and each category that takes up a part of the pie is shaped like a slice. The larger the slice, the greater the proportion of the overall values it represents.

Now, let’s learn how to make some delicious pies.



# Plotting a pie chart by using `pie()`

Like with other plot types, the basic function in Matplotlib to plot a pie chart is `pie()`. Below are some of the important parameters we may need:

- `x`: The list of data we want to present for each #concept=Wedge#Wedge#concept#.
- `explode`: Set as `None` or as a `list` of values that are the same length as `x`. Each item in this list indicates how far each wedge deviates from the center of the circle
- `labels`: A sequence of string that provides labels for each wedge.
- `colors`: Set as `None` or as a `list` of colors that are the same length as `x`.
- `shadow`:  Set as True or False. the default values is False. Setting true adds a shadow effect.
- `counterclock`: Set as True or False. The default value is True. Used to specify the direction of the fractions.
- `autopct`: Set as none or as a string to label wedges with their numeric values. The label will be placed inside the wedge.

Below is an example of how to plot a pie chart. We pass values and labels to `pie()` at `line 7`.

In this lesson, we will learn how to represent the proportions of categorical data using the pie plot.

Introduction

How to Draw Various Plot Elements

How to Draw Different Types of Plots

How to Draw a Pie Plot