This beginner's guide of Python is prepared to open the doors of the fundamental python world.  Python is extensively used in science and research organizations, it covers a variety of tasks required in data science and it is easy to use. Its understandable syntax makes it easy to adjust for people who even do not have a data science skills background.

What is Python?

Python was launched in 1980. However, with continual improvements, Python was officially launched as a complete programming language in 1989. Python was developed by Guido Van Rossum. Python is an accessible source programming language and can be used for commercial objectives.

Python is the programming language and price itself as a heart of data science. Python is an object-oriented, interpreted, distinguished programming language with dynamic syntactic. It’s high-level established in data structures, mixed with dynamic typing and dynamic binding, make it very fascinating for quick  Application Development, as nicely as for use as a scripting or glue language to connect including factors together. 

Python is incredibly simple and it is effortless to learn given that it requires a special order that concentrates on readability. Developers can examine and translate Python code a good deal less complicated than different languages. In results, it reduces the cost of the program because it lets in teams work collaboratively barring substantial language and trip barriers. Further, Python assists the use of modules and packages, which implies that programs can be formulated in a modular style and code can be reused across a combination of projects. Once you've formulated a module or package you require, it can be measured for use in other projects, and it's manageable to import or export these modules.

We can use Python for purposes such as:

  • Desktop Application and Software development.
  • Processing the big data and for performing mathematical estimations.
  • Writing the system’s scripts.

Role of Python in Data Science

 Python is the most valuable programming language in data science. According to a survey via organization analyst O’Reilly, about 40% of data scientists use Python in their everyday function for computing, analyzing, and reporting of data. Big groups such as NASA, Google, and CERN also use Python for nearly every motive of programming. Python is robust, flexible, and has various characters that seem accurate for data science.

Python plays a compatible role with major platforms and systems. Presently, all python applications assist all major operating systems. Data scientists using interpreters in python to run the source code using particular equipment and platforms. Moreover, it enables to run the same source code on numerous platforms without recompiling the code.

Python functions as a library of different modules, this is the actual influential part of python in data science. Python has various libraries for scientific computing, visualization, data analysis, etc. Some of the library modules are listed:


NumPy is a foundation library of Python for Data Science which stands for ‘Numerical Python’. NumPy is essential for scientific computing, which comprises significant n-dimensional array matters and delivers devices for integrating C, C++, etc.


The pandas is the very useful tool at the Data Scientist disposal, running in Python today. The influential machine learning visualization tools may get all the attention, but pandas are the determination of the most data projects.


Matplotlib is a remarkable visualization library in Python for 2D plots of arrays. Matplotlib is a library of multi-platform data visualization made on NumPy arrays and planned to effort with the broader SciPy stack. It was once brought by the means of  John Hunter in the year 2002.

Guide to Use Python

Understand your interest area

Prior to beginning learning Python, it is imperative to comprehend your interest area with the goal that you remain encouraged. Some areas to explore with Python are Artificial Intelligence, Machine Learning, Robotics, Web Development, App Development, Python script, and so on.

Learn the basic Python syntax –

It is important to get familiar with the fundamental Python syntax before beginning anything. Just a short time is required to get aware of the syntax and you can proceed onward to coding.

Practice coding every day

It is useful to code each day while learning a programming language. This sets up consistency and encourages you to become increasingly acquainted with the language. You can begin little and gradually enhance your coding time as you manage.

Make notes as required

Your notes are good to comprehend the syntax and concepts of Python as they require full attention. Also, they help later if there should be an occurrence of any questions as they contain a great deal of significant data in a similar spot.

Try an online course

Online python courses are a great path to understand Python as they give important data and a way to test it. Also, online courses contain feedback frameworks where you can get help whenever required. Likewise, these courses growth from fundamental to cutting edge ideas which build your insight in an effective way.

Interact with other people –

Python has a big online network and it is simple to connect with others to clear your questions or take an interest in conversations. Likewise, addressing queries on an online forum is very good to expand your own comprehension of Python.

Do small projects

As a learner, little projects are a decent method to comprehend Python correctly and turn out to be increasingly equipped in it. It isn't vital that these projects are helpful as long as they show you something. Some instances of projects that can be created are an alarm clock app, a calculator app, a tic-tac-toe game, and more.

Contribute to open source

Contributing to open-source projects of Python assists with getting a more prominent comprehension of Python. The suggestions and comments received will help you in improving as a developer and become familiar with the procedures for Python.

Teach Python to someone else

It is a say that, you just know something when you can teach it to another person. So teach Python to other people, whether as video recordings, blog posts, live lectures, and so forth. This will increase your own understanding of Python and also show any gaps in your insight that should be filled.