Python: Introduction to the most Popular Programming Language

Python is a high-level programming language used for general-purpose software development. Python supports object oriented, structured, and functional programming instances. 

Python is an open-sourced language, and has in recent years increased significantly in popularity due to its use in data science. In fact, Python is considered the number one language for data science.

In addition, Python is developed based on the English language, with the intention of eliminating unnecessary syntax to make it easier to read and write and a simple programming language to get started with and learn quickly.

Python Developers are in high demand tech professionals today. Regardless if Python is a hobby, passion, or way to level up your career, here are 6 reasons to learn programming in Python

Python has a simple syntax and is easy to understand and learn. The learning curve of Python is shorter than that of any other language, such as for example, Java, C, C++, etc.

Python was created with the aim of minimising the complexity and keeping only the necessary.

Python has multiple uses, to name a couple of its most common uses include: Data Mining, Data Science, AI, Machine Learning, Web Development, Embedded Systems, Game development, Network development, Product development, Testing, Automation Scripting, and the list goes on. I think you get what I’m trying to say here; Python is extremely versatile and can be used for a wide range of applications.

One of the reasons why Python is popular among developers is that it has a large collection of libraries that users can work with. Libraries are collections of pre-written code in a certain programming language that anybody can access and use. It contains bundles of code that can be used repeatedly in different programs.

After you’ve grasped the fundamentals of Python, you’ll be able to comprehend and utilise a lot of code created by other programmers. It makes Python Programming simpler and convenient for you as a Python programmer.

According to the PYPL PopularitY of Programming Language Index Python is the most-searched programming language on the internet. Additionally, Stackoverflow.com shows Python as the fastest growing major programming language when measuring the number of visitors vs. questions about a certain topic

When you are facing any Python coding-related, or Data Science issues, you can always seek guidance and help from the Python community. Since it is an open-source language, developers and coders regularly contribute to improving the language with new tools and libraries.

Resulting from the high growth, Python programmers are in high demand. LinkedIn ranks Python as one of the most in-demand programming languages. Python language provides several job opportunities and several of the big and renowned companies use Python for their development.

If we summarise the above, 6 reasons you should consider learning Python

Python is renowned for its broad range of use cases, here are 5 use cases to give you a glimpse of what Python can do

Why are so many data scientists going with Python over other programming languages? Let’s have a closer look at Python in Data Science. Here are 5 reasons why Python is so popular in Data Science

• Readability and Simplicity: Python syntax is easy to follow and write. Python is intuitive and straightforward which makes it easy to get started and readable. 
• Libraries and Tools: Python has an extensive set of powerful libraries and tools that makes working with data really easy. Hence, a data scientist can use a lot of great code created by other developers. You don’t need to know how the library works, just how you can use it to solve your problem. Pandas is a Python that deserves a special mention as Pandas is such an essential tool for Data Scientists. Pandas helps you  to clean and alter your data but also to analyse the data.
• Machine Learning: Python is among the programming languages most preferred for Machine Learning because of its simple syntax and its support of several machine learning libraries.
• Community Support: Python has an active community, and many people use Python to utilize Data Science, so you already have active support to turn to if you get stuck – reach out to fellow data scientists in one of the many communities. Python developers are often very helpful and friendly. 
• Data Visualisations: Python provides various libraries that come with different features for visualising data. Matplotlib in Python is the most basic library for visualising data graphically.

Python’s popularity will only continue to grow as the use of data science and the number of data scientists continue to grow, hence, the use of Python for data science will inevitably continue to grow. Several of the top companies use Python today and have built their technical development based on Python.

There are plenty of free resources available online to learn Python

1. Codecademy

Codecademy is perhaps my favourite resource for learning Python. Codecademy has interactive exercises with immediate feedback. You can run Python code right from your browser. Many of the courses are beginner-friendly and self-paced, giving you the flexibility to learn Python when it suits you. Worth nothing is that Codecademy uses a freemium model where some of their lessons or a course will only be available for paid members

Check out the courses: Learn Python at Codecademy

2. Real Python

Real Python has Python tutorials for developers of all skill levels with courses, articles and exercises. At Real Python you can learn all things Python from the ground up. Everything from the absolute basics of Python, to web development and web scraping, to data visualisation, and beyond

Check out Real Python here

3. freeCodeCamp

freeCodeCamp is another great website to learn Python for free.  freeCodeCamp has one of the most popular courses on Python and it’s completely free. If you are a self-learner, freeCodeCamp is a great place to start learning Python.

Check out freeCodeCamp

4. W3Schools

W3Schools has a text + exercises tutorial that goes through individual Python functions step by step. I think W3Schools has a straightforward and to the point approach with many great exercises and quizzes to learn Python

Check out W3Schools Python

5. Tutorialspoint

Tutorialspoint is very helpful for both beginners and experienced programmers. I like the number of examples on Tutorialspoint and think the walkthrough of different parts of Python are explained clearly and well.

Here is the Python Tutorial at Tutorialspoint

6. Programiz

Similar to tutorialspoint, Programiz is useful for both beginners and experienced professionals. The tutorials and the examples are well worked and the site has a good structure to learn Python.

Check out Python Programming at Programiz

7. learnpython.org

I think learnpython.org explains programming in Python in a clear and beginner friendly way. I think learnpython.org has a nice structure and uses a beginner friendly language. There are beginner tutorials, Data Science tutorials, and advance tutorials available.

Get to learnpython.org here

8. Google Python Class

A free class for anyone with a little bit of programming experience who wants to learn Python. The class includes written materials, lecture videos, and lots of code exercises to practice Python coding. Google itself uses Python for a lot of its projects.

Get to Google Python Class

9. CodingBat

On CodingBat, you can practice Python coding and solve problems. The site is exercise based. Although you might need to complement with another book or site, for example Tutorialspoint, to get an introduction to Python, CodingBat is a great place to practice solving coding problems.

Here is the link to CodingBat

10. Sololearn

Sololearn uses a gamification approach to their learning. You will learn the fundamentals of Python. Sololearn also has a great mobile app that you can use in connection with the website.

Check out the Sololearn

Some general advice:

• Free resources online: Start with free Python resources online, they are great. In general, the online resources to learn Python programming, and computer programming in general, are endless. There’s always a tutorial, or blog explanation, that can help you. Then as you progress you can look at the paid resources.
• Take action: Your time and energy should be to start – to take action – not planning and spending too much time decide which resource to use. They majority are good, just pick the one that you think seems nice and you can’t go wrong, and if that would happen, just switch
• Learn by doing. Programming is about solving problems, and the code is your toolbox to solve a problem. To learn how to use that toolbox you must practice, practice and practice, not only watching others do it. So don’t just watch videos and do quizzes, the sooner you start playing with the code, the faster you will learn the given concepts. For example, I had my own project that I used when I learned Python. It was a simple (very simple) game in Python, it was a great way for me to learn Python programming
• Start with fundamentals: Programming fundamentals always need to come first. The better you understand them, the easier it is to learn the more advanced concepts

In Python, a library is a collection of modules that include pre-written code to assist with common tasks. The most popular Python libraries include

Let’s have a short introduction to them. If you want to have a more thorough walkthrough of these libraries, check out our post: Top 10 Python Libraries to Learn and Use

Pandas

Pandas (Python data analysis) contain a large number of functions for data import, export, indexing, and data manipulation. You can use Pandas to reshape, merge, split, and aggregate data

NumPy

NumPy (Numerical Python) is the essential package for numerical computation in Python. NumPy gives you fast, precompiled functions for numerical routines. It has an array-processing package that gives arrays and tools for working with them. NumPy is extensively used in data analysis

Matplotlib

Matplotlib i’s a plotting library with powerful and beautiful visualisations. Matplotlib is extensively used in Python for data visualisation. In addition, it can be used as as a MATLAB replacement, with the benefits of being free and open source

Seaborn

Seaborn is a Python data visualisation library based on Matplotlib. It’s a a library for making statistical graphics in Python. Seaborn integrates closely with pandas data structures. Seaborn is used to explore and understand your data by creating beautiful and intuitive visualisations.

Tensorflow

Tensorflow is an open source framework that has become a standard tool for Machine Learning. TensorFlow has an extensive ecosystem of tools, libraries, and community resources that lets data scientists quickly build and deploy machine learning applications. Main benefit of using TensorFlow is abstraction – allowing you as a data scientist to focus on the overall logic of the application rather than going into too much detail.

Keras

Keras is a popular library that is used extensively for deep learning and neural network modules (similar to TensorFlow). Keras is a powerful and easy-to-use free open source Python library for developing and evaluating deep learning models. Keras supports several backends, for example TensorFlow, and acts as an interface for the TensorFlow library.

SciPy

SciPy (Scientific Python) is a collection of algorithms and functions built on the NumPy extension of Python. SciPy is extensively used for scientific and technical computations, such as linear algebra, optimisation algorithms, solving differential equations and the Fourier transform, and so on.

PyTorch

PyTorch is a scientific computing package that uses the graphics processing units. PyTorch is an open source machine learning framework based on the Torch library. It’s mainly used for developing and training neural network based deep learning models. PyTorch is very popular in research labs.

Scrapy

Scrapy is one of the most popular, fast, open-source web crawling frameworks. Scrapy is used to crawl websites and extract structured data from their pages. Web crawling is the process of going through data on websites by using a program or automated script – in this case Scrapy.

SQLModel

​​SQLModel is a library for interacting with SQL databases from Python code, with Python objects. With SQLModel, instead of writing SQL statements directly, you use Python classes and objects to interact with the database

If you want to have a more thorough walkthrough of these libraries, check out our post: Top 10 Python Libraries to Learn and Use