Why I’m Learning Python in 2018

Alexus Strong em 12/01/2018 no site Codecademy

Image via Stack Overflow

However, “having a moment” implies that this surge in interest might slow down soon. But is there any reason to believe Python will be any less popular at this time next year? That was the question I set out to answer.

Why? Simply put, I’m in the market for a new programming language. I took a couple of Java courses in college, but I haven’t used it in years. I learned HTML and CSS with Codecademy, but now I’m looking for a language that I can use for more than web development. Most importantly, I want to make sure I’m learning something that’s as relevant today as it will be five years from now.

So, not only for myself, but for any fellow learners, I decided to dig into the rise of Python to understand why so many people are learning the language today, whether those reasons will hold up next year, and what that means for you, me, and our careers.

The Rise of Python

Programming languages have always come and gone. What’s especially fascinating about Python’s recent popularity is that, not long ago, it was thought to already be dead.

In 1999, Larry Wall, creator of the programming language Perl, delivered his third annual “State of the Perl Onion” address to an audience of its die-hard fans. During the address, he charted demand for various languages on the job posting website dice.com:

Image via wall.org

As you can see, Python barely registered at the time. Remarking on the chart, and on Python’s reputation at the time as a niche and strange language, Wall quipped, “Perhaps there's no demand for Python programmers simply because Python programmers are really easy to find without using dice.com.”

Perl has since gone the way of dice.com, but Python is stronger than ever. Last fall, Stack Overflow determined that the volume of visitors to questions about Python on their site is increasing more rapidly than any other, giving Python a claim to being the fastest-growing major programming language in the world.

Enrollment in Codecademy’s free Python course supports this claim—the number of Codecademy users currently studying Python with us is 34% higher than it was at this time last year.

So why has this language, once a literal punchline, gotten so popular so quickly?

Image via languagehealth.com

Why Python?

Stack Overflow boiled it down to one main reason: the rise of Python can be connected to the rise of interest in data science.

Their analysis is fascinating and worth a read, but tl;dr: “Python’s popularity in data science and machine learning is probably the main driver of its fast growth.” It doesn’t take me to tell you that these were two of the biggest trends in tech in 2017.

There’s still an important question here, though. Plenty of other programming languages, like SQL and R, can be useful in the field of data science. Why are so many people choosing Python?

One major factor is Python’s versatility. There are over 125,000 third-party Python libraries. These libraries make Python more useful for specific purposes, from the traditional (e.g. web development, text processing) to the cutting edge (e.g. AI and machine learning). For example, a biologist might use the Biopython library to aid their work with genetic sequencing.

Additionally, Python has become a go-to language for data analysis. With data-focused libraries like pandas, NumPy, and matplotlib, anyone familiar with Python’s syntax and rules can deploy it as a powerful tool to process, manipulate, and visualize data.

Hillary Green-Lerman, our data analysis curriculum developer and principal data scientist at Codecademy, uses these Python libraries every day. As a data scientist, she describes Python’s as a “wonderful, happy medium of everything” she looks for in a programming language.

“If you want to do something simple, it’s probably one line [of code]. If you want to do something really complicated, you also have that very fine level of control.”

Given its versatility and applicability to data analysis, a skill that gets more important every day, it’s become clear to me that Python is here to stay. So if data literacy is one of my priorities, should I get started with Python?

Business Majors Learning Python

Hillary called Python a “wonderful, happy medium” of what she looks for in a programming language because it can do everything she needs it to, but she’s a professional data scientist. I’m not, so my demands are a bit different than hers. Can Python also serve as a “happy medium” for someone like me?

I’m not looking to learn Python to become a data scientist or even a software engineer. Rather, my goal is to improve my grasp of data analysis, use programming skills for web development purposes, and prep for any other technical demands my career might throw my way.

I’m not alone. Increasingly, the people who are seeking out programming knowledge are not looking to become full-time software developers or data scientists. Instead, these are working professionals who are using programming skills to get better at their jobs—marketers, project managers, and entrepreneurs who are looking for an edge, and who simply don’t have time to learn a new language for every purpose.

Python is appealing to those of us in non-technical fields because it puts data analysis, an increasingly important skill in the business world, within arm’s reach, without being too demanding.

“Data driven decision making is increasing in popularity. While in the past years, analysts would use software like Excel to analyze data, while only academics would turn to SPSS, Stata, etc., now things are changing,” according to Forbes.

Even as a content marketer, learning my way around data will make me better at my job according to marketing guru, Andrew Chen.

“The new job title of 'Growth Hacker' is integrating itself into Silicon Valley’s culture, emphasizing that coding and technical chops are now an essential part of being a great marketer. Growth hackers are a hybrid of marketer and coder,” Chen said. “They layer the discipline of direct marketing, with its emphasis on quantitative measurement, scenario modeling via spreadsheets, and a lot of database queries.”

When you read “database queries,” think SQL, Python, and R. Learning Python, it seems, is a step that a lot of people in my position have already taken.

So, next question: can I learn Python? As I mentioned earlier, my coding skills are nothing to write home about. Thankfully, Python’s a great first, second, or third programming language to learn. It’s simple, straightforward, and there’s are a wealth of established, free resources that make it easy to get started.

Its somewhat rigid syntax rules make for consistency, so your code that accomplishes a certain task will look similar to another person’s that accomplishes the same task. It’s also meant to be immediately readable by even the untrained eye.

Let’s say I wanted to print the next paragraph in Python 3. I would write:

print (“On the other hand, if I wanted to print the next paragraph in C++, I would have to write:”)

#include <iostream>

int main() {

std::cout << "All of that’s to say, Python is pretty simple in comparison.\n";

}

The Python community is also welcoming to novice programmers. As Hillary describes it, the language itself and the community surrounding it “have that attitude of, ‘Don’t worry, we’ll protect you if something goes wrong.’”

Even though Python is great for beginners, it has all of the power necessary to get advanced work done. Hillary, who uses Python every day to process and analyze data from millions of Codecademy learners, says, “You really can do everything in Python and there are real, serious people using it.” She continued:

“Python really grows with you. So it’s very easy to get started, but it’s also going to be super relevant some day when you decide you’re going to do natural language processing or machine learning or TensorFlow. You’ll be able to do all of that too because it’s a full language.”

In our 2017 Global Report on the Future of Work, a global survey of Codecademy learners, we found that our learners are gravitating toward Python, and then staying there. A higher proportion of people who’ve learned other languages with Codecademy want to learn Python (40%) than Python learners who want to learn other languages (25-30%). This data seems right in line with Hillary’s point—there’s so much you can do with Python that it might be the only language someone like me needs.

Now what?

It’s become clear to me that Python is the Swiss Army Knife of programming languages—a versatile tool that can useful in just about any career. For that reason, I’m convinced it isn’t going anywhere anytime soon.

It’s ideal for novice software engineers, marketers, business analysts, bankers, and anyone else who wants to do more with data. So, I know which language I’ll be learning next—and it helps that our introductory track only takes 13 hours.

Ready to join me in getting started with Python? Our free Python track will take you from basic syntax through more advanced concepts like iterating over data structures. Like Python itself, the track will let you go as far with the language as you’d like, in whichever direction would be most useful for you and your career.

As I start learning, you can track my progress here, and feel free to yell at me if you catch me slacking.

Interested in applying Python to data science and analytics specifically? In our Introduction to Data Analysis Pro Intensive, you’ll learn how to use the same Python libraries that Codecademy’s Hillary Green-Lerman uses daily—Pandas, Numpy, SciPy, and Matplotlib—to manipulate, analyze, and visualize data.