Are you interested in data science or data analysis as a new career? Perhaps you are a marketer who wants to present your findings on customer behavior to your team.
Matplotlib, a plotting library for Python, can help you support your points. The library, for example, is used by researchers to better understand current health trends so they can give policymakers an easy way to understand data points like infection rates and location of a disease outbreak.
Whatever your data visualization ambitions are, Matplotlib can help you achieve them. This guide gives you tips on how to use the Python library.
What is Matplotlib?
Matplotlib is a Python library that creates charts, graphs, and animations to help you visualize your data. A library is a set of functions, or actions, already written out in code. Using a library means that you don’t have to re-write code every time you want to perform a particular function, or task.
With Matplotlib, you can use plots, like line plots, bar plots, and scatter plots to represent your data.
By visualizing your data, you can better understand patterns and correlations between pieces of information. These patterns can help point you to relationships of cause and effect, which can then help you make better decisions.
For example, perhaps you are in sales and you notice people tend to purchase a subscription to your online service during a certain month. This may lead you to market your service more aggressively leading up to that month.
This visualization of data is often the first step of statistical or machine learning analysis. Matplotlib allows you to save your data visualizations as files so you can share them with others.
What is Matplotlib Used for?
Matplotlib is used to visualize data in Python. Data visualization is a key component of making decisions in an organization. You can take your data set, visualize it using Matplotlib, analyze your data, and make a document containing the visualization to share with others. You can also adjust the data set to more accurately show the information you need.
Visualizing data with Matplotlib can be helpful in many sectors, including:
- Finance. Matplotlib allows you to represent data about stock prices in a chart to decide which ones you should invest in.
- Business. Use Matplotlib to visualize customer buying behavior to help you make better inventory and marketing decisions.
- Social justice. Use Matplotlib to visualize data about issues such as homelessness and employment rates.
- Health. Use Matplotlib to visualize data about infection rates, affected populations, and vaccination rates.
If you are a Python developer, data analyst, or data scientist, Matplotlib is a great tool to learn. It can also be a good skill if you are in any field that requires data visualization.
So, how should you learn how to use Matplotlib?
Why Should I Learn Matplotlib?
There are many reasons why you should learn how to use Matplotlib. Data analysts and scientists need to visualize the data from a data set.
Matplotlib is a common Python library
A library is a collection of code that you can use so you don’t have to re-write your code every time you want to use it. Python is an easily readable language and has a lot of libraries for data analysis, making it commonly used by professionals. Learning Matplotlib will position you well for a range of Python data science challenges you may encounter in your career.
Matplotlib is easy to get started with
Matplotlib is so popular because it is fairly easy to get started. If you already have Python installed on your machine and have your code editor set up, follow these steps: First, download Matplotlib.
Then, open a new code file and import Matplotlib. Finally, write some code to create your chart, graph, or other visual. If you have ever created a visual in Microsoft Excel, using Matplotlib is a similar concept.
Matplotlib is popular
Matplotlib is one of the most popular Python libraries for data analysis. If you want to learn how to use this tool, you will find lots of resources for how to learn it. You can also talk with people in the data analysis community about this tool.
As of this writing, there are over 400 job postings on LinkedIn that mention Matplotlib (for jobs in the United States). These jobs include titles like “Data Visualization Engineer”, “Data Analyst” and “Growth Engineer”.
Of course, you can use Matplotlib even if the job description used to hire you doesn’t explicitly mention the term. That’s why it’s helpful to look for specific job postings that involve analytics in general. If you change the search term on LinkedIn from “Matplotlib” to “Data Analyst”, there are over 36,000 job postings.
And if you change the search term to “Marketing Analyst” there are over 21,000 results. Of course, these numbers are likely to fluctuate. Still, this data strongly suggests that there is a high demand for people with data visualization skills.
How Long Does It Take to Learn Matplotlib?
It will take you two to three weeks at one to two hours a day to learn Matplotlib, assuming that you already understand Python. If you don’t know Python yet, check out this comprehensive guide on learning Python.
If you want to become a data analyst or data scientist, you will need to continually improve your skills. There are additional libraries built on top of Matplotlib, like Seaborn, so you should become familiar with those as well once you have the basics of Matplotlib.
Is It Hard to Learn Matplotlib?
It is not difficult to learn how to use Matplotlib if you already know how to use Python. There are many resources available to learn how to use Matplotlib. Make sure to use these resources once you have downloaded it and are ready to start creating your data visualizations.
In addition to understanding at least the basics of how Python works, you will also need to know how to use a code editor. A code editor is referred to as an Integrated Development Environment (IDE). This is where you will write your code.
There are many IDEs available. Some of them include Visual Studio Code, which is produced by Microsoft; Sublime, and Atom. There are even IDEs built specifically for coding in Python. PyCharm is a code editor built for coding in Python.
How to Learn Matplotlib: Step-by-Step
Before you learn how to use Matplotlib, make sure you have a basic understanding of Python. Once you know some basic Python, it isn’t difficult to get started with Matplotlib. In fact, you can use Matplotlib as your first Python library if you want. The more Python you know, the more complex visualizations you can make. This is especially true if you also know how to use other tools like Pandas and Jupyter.
There’s no single “best way” to learn how to use Matplotlib. It all depends on how you learn and if you are already familiar with Python. Some people prefer to watch a lot of tutorials or read a lot of articles first before they try writing any code. This helps them to feel like they know what they are doing. Others prefer to get just a basic introduction and then jump into writing code.
From a high level, here are the basic steps you can follow to learn how to use Matplotlib:
- Determine your learning goals. Decide why you want to learn how to use Matplotlib. Is there a work project that would benefit from some objective data visualization? Are you passionate about a cause and need to present data to your local community? Knowing your learning goals will help determine the specific skills you need to learn. It will also help you with the questions you ask your online learning communities and the resources you search for.
- Get the basics down. Get familiar with your code editor and get at least a basic understanding of Python and what libraries are.
- Start creating. Arguably, the best way to learn anything is to start doing it. Come up with a basic project to use Matplotlib for, like plotting how many treats your cat eats in a day.
- Join a programming community. Talking to others about their experiences with Matplotlib is a great way to expand your own knowledge and help others as well. You’ll find out what you actually know as you have to articulate your questions and answers in online communities like the Python community. StackOverflow is a great place to ask questions after giving a fair shot to figuring out the answers yourself.
- Apply your knowledge to a real problem. Once you have done a few basic data visualization projects, expand your knowledge. Try out your skills on a real work or personal problem. For example, maybe you own a business and need to figure out what months have seen the lowest sales so you can come up with a strategy for upping your profits.
The Best Matplotlib Courses
There are many online courses you can take to learn how to use Matplotlib. Most of these resources assume that you have some basic knowledge of Python. Below we have listed some of the best courses for learning how to use Matplotlib.
edX: Visualizing Data with Python
Price: Free (Certificate is $99)
This course, taught by an iBM data scientist, introduces you to key elements of data visualization with Python. It allows you to make better decisions for your business or organization. The course takes five weeks to complete with two to four hours of learning per week. The Python Basics for Data Science and Analyzing Data with Python course is required as a prerequisite.
This course kicks off with how to work with Matplotlib. You’ll learn about the basic visualization tools that Matplotlib offers, like area plots, histograms, and bar charts. Then you’ll learn about specialized and advanced visualization tools.
W3Schools Matplotlib Tutorial
Price: Free ($95 for certification)
W3Schools offers a Matplotlib tutorial that includes examples and exercises so you can practice. The first tutorial page assumes you know how to install Matplotlib via Git, or that you have installed Anaconda, a data science platform that has Matplotlib built-in.
PythonProgramming.net’s Harrison Kinsley offers an engaging, friendly approach to learning Matplotlib. This crash course features a step-by-step approach to getting started with Matplotlib, complete with helpful videos, graphics, and textual explanations. This course does presuppose that you already have Matplotlib installed and have some experience using the Python import command.
‘Python Data Science Handbook’ by Jake VanderPlas
The digital version of this book is available for free on Github. It’s a great introduction to Python’s data science libraries, including Matplotlib. If you’re also interested in some of Python’s other libraries, like NumPy (stands for “Numerical Python” and is used for mathematical operations), Pandas (used for data manipulation and analysis), and Sci-kit-learn (used for machine learning), this is a great book for you.
‘Python for Data Analysis: Data Wrangling with Pandas, NumPy, and IPython’ by Wes McKinney
This book is available for free at this Github link. Matplotlib is just one skill you’ll want to have in your data analysis toolkit: You should also be familiar with other technologies like Pandas (a Python library for data manipulation and analysis), NumPy (stands for “Numerical Python” and is a Python library used for mathematical operations), and Jupyter (a web application used for data cleaning). This book offers you a fantastic introduction to all of these skills.
‘Mastering matplotlib’ by Duncan M. McGreggor
This book teaches you how to go beyond the basics of Matplotlib and explore ways to visualize more complex data. You should have experience working with Matplotlib and be ready to go beyond the basics.
Online Matplotlib Resources
In addition to courses and books, there are many other resources that you can use to help you learn Matplotlib.
This is one of the best resources for learning Matplotlib. Maplotlib.org includes resources like documentation, installation instruction, and tutorials to help you master this valuable Python library.
The Matplotlib community interacts online on this forum. This is a great place to ask questions and see what other users are doing with their projects. Matplotlib also has a Twitter account, so you can stay up-to-date on recent changes and what’s happening in the data visualization world.
This online guide has lots of tips for making the most of Matplotlib. There’s a section on Pylab, Pandas, and even an interactive mode where you can try out some of your skills.
This PDF’s fifth chapter covers Matplotlib. “SciPy” stands for “Scientific Python”. It’s an ecosystem of open-source software for mathematics, science, and engineering, and Matplotlib is one of its packages.
If you are interested in data analysis for any reason—whether you are a data analyst or data scientist, or because you have other business or personal uses for visualizing data—you should learn how to use Matplotlib. It is an easy tool to learn how to use, especially if you already know Python.
You can create graphs, charts, and animations that help you understand data on a deeper level. Doing so will help you recognize patterns in data, and more easily persuade your team, policymakers, or other stakeholders. After all, a picture is worth a thousand words.
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