Python Programming for Newbies

​Chapter 1: Introduction to Python

To introduce Python to a beginner, it can be defined as a popular and widely used general-purpose, high level programming language. It was created by an individual called Guido van Rossum, and the first version of this language was released back in the year 1991, and was further developed by the Python Software Foundation.

This language is open source and is free for anyone with a curious mind to start to learn programming. It is genuinely designed to be simple and straightforward to implement in apps or just in everyday programming life.

This language is for those programmers who may convey their ideas in less code because of its syntax, which was created with code readability in mind. Python is such a programming language that enables quick work and more effective system integration.

Python 2 and Python 3 are the two most popular versions of this language. Both are really different.

​1.1 Why Python?

Python is an excellent place to start for anyone wishing to move jobs into the IT industry through coding. It is utilized in a range of domains, including Data Science, Machine Learning, Game Design, and is remarkably adaptable and easy to master.

It is more versatile than other programming languages like JavaScript, HTML, CSS etc.. and may be also applied outside of the field of web development. Below are the key reasons why you should develop your programming skills via Python. They are:

​1.1.1 Python is great for New Beginners

If you are new to coding, then Python is a great place to start. The effort of learning a new language that doesn't look anything like what they are used to reading and writing is one of the largest obstacles for prospective programmers. Python, on the other hand, has English syntax and was created to be short and simple to read, making it more approachable for new programmers than many other languages.

Being an interpreted programming language, Python is also simple to learn. This entails that you may run each line of code as soon as you have finished writing it, enabling you to review it right away and make improvements if necessary – a huge assistance to individuals who are still learning and a time-saver for developers all over the world.

​1.1.2 Python has flexibility

Python is incredibly flexible. It has applications in a variety of fields, from its more well-known ones in data science and software engineering to ones like mobile app development, artificial intelligence, and machine learning. It may be used for both simple and difficult tasks. Due to the broad variety of Python modules available, this use has many different applications (over 125,000, to be specific). Once you have mastered the fundamentals of Python, you will probably be able to comprehend and use a significant amount of code created by other programmers. Libraries are collections of pre-written code in a given language that anybody can access.

Python's compatibility with various programming languages is a crucial component of its adaptability. Jython (Python combined with Java) and CPython are a few typical instances of Python implementation with other languages (Python integrated with C). Last but not least, Python has cross-platform capabilities, so whether you are using Windows, Linux, or macOS, it will work perfectly.

​1.1.3 Demand for Python Developer is rising

Due to the widespread use of Python by big businesses like Dropbox, Netflix, and Facebook, there is always a significant demand for developers. Even Google has created a style manual for Python. Jobs as Python developers can be rather rewarding as its demands keep growing. Python is the fourth-most lucrative programming language, earning an average income of $108,391 for developers, after Ruby ($120,174), C++ ($114,000), and JavaScript ($111,623). According to StackOverflow, Python coders can also make a good wage with little to no expertise.

​1.1.4 Supportive Community

You can have full confidence that you have a community of programmers who you can ask questions to when a problem arises when you are learning a new programming language, especially after you have finished your bootcamp course or degree.

With 1.5 million GitHub repositories, Python is the second-largest community on the platform, which demonstrates the strength and support of its online community. Python enthusiasts frequently plan meetups across the world to build community and knowledge bases. Python also has its own network of powerful community forums where users can access and discuss everything from workflow to software development.

​1.1.5 Huge Growth perspective

The statistics don't lie when it comes to Python's popularity and growth rate. Python is currently the most searched-for programming language online, according to the PYPL Popularity of Programming Language Index, and this trend doesn't appear to be changing anytime soon. Python is the fastest-growing programming language, according to Stack Overflow, and TIOBE awarded it the 2020 Programming Language of the Year award because it did so more quickly than any other language.

Python's utility in the field of data science contributes to some of its popularity; as the need for experts in areas like machine learning, data modeling, and AI increases, so does the need for those with knowledge of Python. All of this indicates that Python is a smart choice if you're wanting to learn a new programming language or make the crossover into the profession of programming.

​1.2 Where Python is applied?

In the 21st century, this versatile programming language can be marked as a leader in sectors that are highly innovative. Python is frequently used for creating websites and applications, automating repetitive tasks, and analyzing and displaying data. Python has been used by many non-programmers, including accountants and scientists, for a variety of routine activities including managing finances since it is very simple to learn.

​1.2.1 Data Science

Python is a popular language in the field of data science due to its ease of use, flexibility, and a vast array of libraries and frameworks specifically designed for data analysis and visualization. The key libraries in Python for data science include NumPy, Pandas, Matplotlib, Seaborn, and Scikit-Learn.

●  NumPy provides support for large, multi-dimensional arrays and matrices of numeric data and is used for mathematical and logical operations.

●  Pandas is a library for data manipulation and analysis and is widely used for cleaning, transforming, and aggregating data.

●  Matplotlib and Seaborn are visualization libraries that allow for the creation of various types of graphs and charts to help understand and interpret data.

●  Scikit-Learn is a machine learning library that provides algorithms and tools for modeling, training, and testing predictive models.

Python's data science libraries and its ability to integrate with other technologies make it a valuable tool for solving real-world problems and uncovering insights from data. Whether you're working with large datasets, building predictive models, or visualizing data, Python has the tools and libraries you need to get the job done.

​1.2.2 Machine Learning

Python helps simplify sophisticated prediction technologies like AI algorithms and machine learning models. The ability to turn attention away from language and toward machine learning algorithms