Intro to Word Clouds & Python

In this hands-on data visualization training, you’ll learn basic data visualization techniques and how to make a word cloud using Python.

Why learn about

word clouds & Python?

Explore your future in tech

Our lessons are the best way to experience if learning data visualization is for you. Explore whether you’re passionate about pursuing data analysis as a career, or if you just want to brush up on some skills.


Prepare for a data science bootcamp

These lessons are the most efficient way to get real hands-on experience and to learn the data analysis basics you’ll need to get into our immersive data science course.

What you’ll learn: data visualization & word clouds using Python

Let’s say that you want to count up how many times each word in a song appears. Without a computer, it would be difficult to organize and time-consuming. You would have to record all of the lyrics on paper, cross out all of the duplicates and then count the number of times each of the words occurs in the lyrics. Additionally, you wouldn’t have the ability to do any visualizations.

Using Python, it’s much easier. Together, we’ll make a list of all the words in a song’s lyrics, create a set of unique words, generate a word frequency table, chart the table on a bar chart, and build a word cloud visualizing higher frequency lyrics.


Other free data science tutorials at Flatiron School

Free Workshop

Intro to Python

Start your data science journey with the popular, beginner-friendly programming language —Python.


Free Workshop

Intro to Binomial Distribution

In this intermediate workshop, use Python to demonstrate how data can optimize hotel profits.

Frequently asked questions about Python

Python is a general-purpose coding language. This means that, unlike some other languages, it can be used for other types of programming than web development alone. Python can be used to manipulate and manage big data sets, and is known for being able to perform complex mathematical computations, which makes Python the most important programming language in data science.

Python is a general-purpose programming language with a broad range, meaning that it can be used for things like software development, writing system scripts, and mobile app development. Python can also be used to read data files and analyze data sets, making it an attractive language in data science.

Further readingThe Best Programming Languages to Learn for Data Science

Compared to some other language, Python is pretty easy to learn, but the answer to this question really depends on what you want to achieve. You can learn some basics in Python in just a few hours, but to really start getting comfortable with Python probably takes a few weeks of intense training.

It is also important to know that even people with years and years of experience don’t know everything about Python and its abilities because Python is a language that keeps evolving.

Python is best used for automation, back-end web and app development, software development, processing big data, system scripts.

Automating tasks is extremely valuable in data science and will ultimately save you a lot of time, and provide valuable data — this is why Python excels.

While Python supports all the basic features of an Object-Oriented Programming Language, Python isn’t strictly an OOP language and has features of aspect-oriented programming as well.

Yes, Learn Python is free, just like the rest of our workshops and tutorials.

If you’re looking to get started with Python for free, you’re in the right place. This Python tutorial for beginners covers Python basics entirely for free.

You should learn Python if you’re interested in writing scripts, app or software development, and data science. If you’re interested in learning Python to analyze data specifically, it’s both a very useful language for those who want to fully change careers and become data scientists and analysts, and those who want to use data analysis in their current job, but want to leverage data skills to push their careers further.