Attention, Python Coder! What Can You Learn from the StackOverflow 2019 Developer Study?

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The yearly StackOverflow Developer Study is the largest of its kind. Every year, more than 90,000 developers participate by answering a 20-minute questionnaire.

Because of the great insights, the StackOverflow study is a must-read for uprising developers and coding talents. This article gives you a short overview of the key highlights of the survey.

Interestingly, you can also download the survey data set and play around with the data—for example, using the NumPy library (see this NumPy tutorial on my blog to learn everything you need to get started).

Insight #1: Python is the 800-pound Gorilla in the Programming Space

Python is the fourth-largest programming language in the world in terms of popularity (41.7% of the study participants use Python regularly)! Only JavaScript (67%), HTML/CSS (63%), and SQL (54%) are used more often. In the last years, Python bubbled up the ranks at an incredible speed. This year (2019), it just overtook its big competitor Java (41.1%).

On top of that, when programmers are asked about their most-loved programming languages, Python ranks #1 within the major programming languages–with an incredible percentage of 74.1% of Python lovers. Thus, Python is loved more than JavaScript (66.8%), HTML/CSS (62.6%), Java (53.4%) and C++ (52%). Only the relatively small Rust language is loved more with 83.5% because of their strong and small community.

The take-away for you is simple: If you decide now to master Python, you’ll never look back!

Insight #2: Data Science and Machine Learning is on the Rise

No shit, Sherlock. ?

This megatrend is easy to see and widely accepted. It manifests itself in many ways in the StackOverflow data set. For example, the most loved frameworks, libraries, and tools contain a lot of Python frameworks for data science and machine learning: PyTorch (77.1%), Pandas (74.7%), TensorFlow (73.0%) are only a few of them. While there are many other frameworks and libraries in different programming languages, it’s evident that Python frameworks are over-represented in the list of most-loved frameworks.

The global average salary of a data scientist or machine learning specialist is $61,000 (United States: $120,000). This is place 4 and 5 among hundreds of job descriptions!

The takeaway here is that machine learning penetrates into every era in computer science and you simply cannot ignore it (nor it’s sibling data science). So, learn data science now!

Insight #3: DevOps Specialists Lead a Rich and Happy Life

Surprisingly, DevOps specialists “are among the highest paid, most experienced developers most satisfied with their jobs, and are looking for new jobs at the lowest levels” as highlighted in the survey.

Almost 11% of all programmers classify themselves as DevOps specialists. On average, they earn $71,000 per year (worldwide) and $122,000 per year in the United States. This makes them the top earners both in the US and in the world—only surpassed by site reliability engineers (US: $140,000) and engineering managers (US: $152,000).

Furthermore, DevOps engineers are (almost) least likely to search for a job because they are usually happily employed. And to top all of that: DevOps engineers enjoy maximal job satisfaction scores among many professionals with various job descriptions.

What the hell is a DevOps engineer?

DevOps is short for software development (Dev) and IT operations (Ops).

Software development is not only about writing code. Consider the huge code base of the Windows operating system with more than 50 million lines of code. The main challenge is to channel the coding effort of hundreds of thousands of professional developers in time and space. It’s crucial for the success of those companies to use these resources efficiently.

The takeaway here is to start your career as a professional coder now and never stop learning! In a few years, you’ll not only earn six figures easily, you’ll also qualify for the highly loved job description of a DevOps engineer.

Check out my Python freelancer course to get a turbo-boost on Python experience in minimal time.

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