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Why was Python the top searched programming language on Google in 2020?

December 31, 2020 | Emerging Technologies, Technology
Read Time: 07:00

According to Google’s Year in Search 2020 Report, “How to learn coding” was the top trending thing people searched to learn and Python was the top searched programming language.

Python programming language has had a very, very successful run in 2020, no doubt about that. Python’s popularity keeps growing every year and it refuses to die down. It has been the most-loved programming language for many years now, and why not – it is easy to learn, it is easy to understand, and even if you have only enough time to learn just one programming language, Python will sail your boat just about everywhere.

The latest version – Python 3.9 is breaking cover with its host of new features, while Python 3.5 is going out of support. Python’s 3.9.0rc2 release is the first-ever version of Python to default to the 64-bit installer on the Windows platform.

Let’s take a look at the PYPL Index. The PYPL Index stands for the ‘PopularitY of Programming Language’ Index. This index is formulated by analyzing how often the tutorials for different programming languages have been searched on Google. The more often these tutorials are searched, the more popular the language would logically be. It is a leading indicator of the popularity of programming languages and the data for calculating this index is taken from Google Trends. Here’s a look at the top 10 languages in this index:

Python has consistently received top billings in rankings everywhere primarily because it is one of the easiest programming languages to learn. It is said that Python reads almost like English. This makes Python an excellent choice if you are thinking of learning a programming language. Moreover, the wide range of libraries available in Python makes it the most preferred and most loved programming language of all time as it makes the user’s tasks so much easier to accomplish. 

When did Python originate?

In 1989, after encountering multiple limitations of the language he was working in, Guido van Rossum set out to develop a new programming language that would integrate all the good features of the different programming languages and add in important new features – extensibility and exception. He kept on working on this project, and in 1991, Python 1.0 was launched. In 2000, Python’s core development team moved to Python 2.0 was launched the same year with many improvisations, a useful garbage collector, and support for Unicode. Towards the end of 2008, Python 3.0 was launched that provided backward compatibility and a new design that would help users avoid duplicative constructs and modules.

Python is the perfect multi-paradigm language that offers features like object-orientation, functional programming, and structural programming.

What are the applications of Python?

Some of the most common applications of Python include:

  • GUI based desktop applications:
    • Image processing applications
    • Graphic designing applications
    • Scientific and computational applications
    • Games
  • Web frameworks
  • Web applications
  • Enterprise applications
  • Operating systems
  • Language development
  • Prototyping
  • Data analytics & machine learning 

What are the advantages of using Python?

The benefits of using Python include:

  • The Python Package Index (PyPI):

    The PyPI contains many third-party modules that help Python interact with other languages and platforms with ease.

  • Numerous support libraries:

    As mentioned before, one of the major reasons Python is such a popular programming language is because of the numerous support libraries that the language offers. You could be working in any area – internet protocols, string operations, web service tools, OS interfaces, data science, machine learning, anything – you will find a library that will help you out. A lot of such high-programming tasks have been scripted into the standard library of Python reducing the amount of code you would have to write to accomplish your task significantly.

  • Open-source support:

    The Python programming language has been developed under an OSI-approved open-source license. This makes Python free to use and distribute, even if you would be using it for commercial purposes. Python also has an active community that works together to collaborate for its code and help provide many useful modules for the language.

  • Ease of learning:

    Python is an extremely readable language. Its syntax is also very easy to learn. Moreover, the diverse community of users of Python spread all across the globe has helped create a complete resource bank online which encourages the development and adoption of Python. Anytime you get stuck anywhere, you can reach out to the user community and someone will always be there to guide you.

  • Data structures:

    The built-in list and dictionary structures in Python are super helpful to construct fast run-time data structures. With Python, users also get an option of dynamic high-level data typing with which the length of support code needed decreases drastically.

  • Better productivity and enhanced speed:

    With its clean object-oriented design, Python offers better process control with strong text processing and integration capabilities. It also has its unit testing framework. Together, these features cause Python to offer better productivity and enhanced speed of operation. When you want to build complex multi-protocol network applications, choosing Python is the best decision you would make for the project probably.

Why learn Python?

Python is seeing an increasing demand in the fields of statistics, data visualization, as well as research and operations involving very large data sets. Experts say that if you have an interest in programming, Python would make a valuable first step.

Developers these days very commonly use Python for implementation in the hottest technology trends like machine learning, artificial intelligence, data science, etc. This makes individuals who learn and understand Python highly marketable.

Moreover, Python has a rapid ramp-up time, so individuals can learn to write programs in Python very easily and very quickly with impressive quick visualizations of the results.

In a nutshell, if you want to be highly marketable and sought after in the job market – learn Python.

Where to learn Python for machine learning?

One of the most popular applications of Python is in the field of machine learning. Python has proved highly adept at handling large volumes of data and offers numerous data science and machine learning support libraries which are very useful for the users.

To learn Python for machine learning you need to find the best Python training that would also incorporate the principles of machine learning into its training outline. The best Python training would also have ample practical exercises to provide thorough hands-on exposure to every training participant. And at the end of the training, participants must get a machine learning and Python certification. If this is the kind of Python training you are looking for, you’ve come to the right place.

Cognixia – the world’s leading digital talent transformation company offers a thorough hands-on online instructor-led data science with python training and certification course. This course is delivered by some of the most experienced machine learning and Python trainers. It covers all the important concepts of machine learning as well as Python. The course covers:

  • How to install and import Python libraries
  • How to handle various data like categorical, ordinal, and encoding
  • Data visualization
  • Distinguishing between artificial intelligence, machine learning, and deep learning
  • Working with data in real-time
  • Implementation of machine learning algorithms
  • Implementation of deep learning algorithms
  • Types of time series data – univariate and multivariate
  • Performing text and sentiment analysis
  • Business analytics

After completing the training, Cognixia provides you with a Machine Learning with Python Certificate validating the skills learned during the course. The course also incorporates multiple labs and practical exercises that would help you learn every concept discussed in class thoroughly. You can learn from anywhere with this online data science with python certification course.

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