What is Python?
Python is one of the most popular programming languages in 2022. Numerous business fields, including programming, web development, machine learning, and data science, use it extensively. It's not unexpected that Python has surpassed Java as the most popular programming language given its broad usage. The top 10 reasons why you should learn Python are listed in this blog.
Why you should Learn Python?
How come to Python? Python consistently ranks among the top programming languages used by businesses. Like other widely used programming languages, Python didn't become well known until many years after it was first developed. In 1991 and at the end of 2000 Python 2.0 was introduced, thanks to its versatility and widespread use, the language had reached its peak. The majority of the biggest tech companies in the world utilize Python, which is currently in its third version. Python can be learned by a wide range of people, including software developers, data scientists, and cybersecurity specialists.
Top 10 Reasons to Learn Python
1. Python is the simplest language
The primary factor making Python a great choice is because of its simplicity. Beginners, who want to work in the data science or coding fields frequently ask themselves, "Why to study Python?" Why not learn Python is our response to that?
Python is a language that is good for beginners because of its easy and simple syntax (which almost seems like English!) and high readability level. Naturally, Python has a far lower learning curve than any other language (including Java, C, C++, etc.). Additionally, Python enables you to skip the manual and jump right into the research portion.
This is why Python is frequently used for web development, text processing, data analysis, and statistical analysis, among other things, in both development and data science domains.
2. Very adaptable and extensible
Python is highly scalable and extensible, because of its flexibility python allows you to cross-language operations without any problem. You can easily integrate it with Java and .NET components and can easily use python with C\C++ libraries.
Python is supported by almost all of the popular platforms like Windows, Linux, Solaris, Macintosh, etc.,
3. Lots of libraries and Packages
Python has more helpful libraries than any other language. The programming language has the best selection of libraries that are useful for activities related to development and data science. In addition to many other tools, it includes NumPy, SciPy, Scikit-Learn, Matplotlib, Pandas, and StatsModels. Python's features and abilities have greatly increased as a result of the extensive collection and incorporation of libraries over time.
One of the oldest python libraries is Numpy as it incorporates all of the high-level mathematical operations on multi-dimensional arrays and matrices. NumPy can be easily used for scientific computing.
SciPy, is almost scientifically equivalent to NumPy, which allows you to perform numerical integration and analysis of scientific data.
On the other Pandas is another popular library that can be used for data analysis, it was built on top of NumPy.
There are so many libraries like Scikit-Learn, PyBrain, PyLearn2 and PyMC, Whatever the requirement, Python has a library to meet it!
4. Web Development is easy with Python
One of the main reasons to use python is that it makes the process of web development so much easier and more convenient and provides a wide range of variety of web development frameworks such as Django, TurboGears, Web2Py, Flask, Hug, Bottle, CheeryPy, Sanic and FastAPI are some of the popular frameworks.
Frameworks like these help developers to code much faster and in a stable manner. This complete implementation can be done automatically by using frameworks resulting in reducing the development time so that developer can easily focus on logic building. Apart from this python play a major role in Web scraping tasks.
5. Lots of Data Visualization Frameworks
Python offers a solution for any problem. There are many choices included for data visualization. The most well-known Python data visualization tools are Plotly, Altair, Seaborn, Bokeh, Pygal, Geoplotlib, Gleam, and Missingno. Matplotlib, the foundation library from which Pandas Plotting, Seaborn, and ggplot were created, is another.
These frameworks for data visualization make it simple to understand complicated datasets. Not only that, but you can also visualize your results using a variety of representation methods, including graphs, pie charts, graphical plots, interactive plots that are ready for the web, and much more.
6. Python has numerous Numbers of testing frameworks
Python is the best language to use for testing or verifying concepts or goods. It has a number of integrated testing frameworks that aid in process optimization and debugging.
With frameworks like PyTest and Robot, Python provides testing across platforms and browsers. Other testing frameworks include Lettuce, Behave, and UnitTest.
7. Python is best for Enterprise Application Integration (EAI)
Python is an excellent option for EAI. It applies to programs written in various languages and can be smoothly integrated into programs. As an example, Python can directly call from and to Java, C++, or C code in addition to CORBA/COM components. Strong integration ties between the language and Java, C, and C++ make it ideal for application scripting.
The text processing and integration abilities of Python are excellent. It can also be used to create desktop and GUI apps.
8. Scripting can be easily done with the help of Python
Yes, Python is not just a programming language – it can be used for scripting too! The feature that sets scripting languages apart from programming languages is that scripting languages don’t require any compilation; they are directly interpreted. In Python, you can write code in the script and directly execute it.
The machine will read and interpret your code and also perform error checking during runtime itself. Once the code is error-free, you can use it multiple times.
9. An engaged community supports Python
You can rely on Python's vibrant and close-knit community. You can always ask the Python community for assistance if you have any coding- or data-related problems. They are always willing to assist others. Since it is an open-source language, new developments are made every day in the community; programmers and developers frequently add to the language's richness by creating new tools and libraries.
10. High Salaries
You can easily get a high amount of salaries in the industry as python is one of the major programming languages in the development and Data Science field at present, It makes large compensation projections and offers a high growth curve.
According to glassdoor the average annual salary of a Python Developer is around ?4,50000 per year in India.
Additional Features Of Python
Artificial intelligence
The next major advancement in technology is AI. The ability of a machine to think, reason, and make judgments to mirror the human brain is actually possible.
Furthermore, machine learning functionality is added to the mix by libraries like Keras and TensorFlow. It grants the capacity for learning without intentional programming. Additionally, we have libraries like OpenCV that support image recognition or computer vision.
Computer Graphics
Most small, large, online, and offline projects use Python. It is utilized to create desktop and GUI applications. It offers a quick and simple approach to constructing apps using the "Tkinter" library.
It is also employed in Game development, where the logic for using the "pygame" module, which is also compatible with Android devices, can be written.
Big Data
Python can easily handle a lot of hassles of data. It has the support of parallel computing as well so you can use python for Hadoop as well.
There is a library called “Pydoop” by using that you can write a MapReduce program in python and can easily process data present in the HDFS cluster.
There are some libraries like ‘Dask’ and ‘Pyspark’ for big data processing. Therefore, Python is widely used for Big data where you can easily process it.
Data Science
The preferred language of many data scientists is Python. When Python numerical engines like "Numpy" and "Pandas" were released, things started to change for academic researchers and independent researchers who had been using the MATLAB language for years.
Python works with tabular, matrix, and statistical data as well, and it even plots it using well-known libraries like "Matplotlib" and "Seaborn."
Machine Learning
Because of its straightforward syntax and support for numerous machine-learning frameworks, Python is one of the computer languages most frequently used for machine learning.
Start Your Career As A Python Developer
The next step is easy now that you are aware of the Top 10 Reasons to Learn Python Programming and how it can advance your career. The thorough Data science with python course from Fingertips teaches you the fundamentals of Python, data operations, shell scripting, conditional expressions, and Django. The curriculum will give you practical development experience and prepare you for a fast-paced and fascinating job in Python programming.
There are some libraries like ‘Dask’ and ‘Pyspark’ for big data processing. Therefore, Python is widely used for Big data where you can easily process it.
Data Science
The preferred language of many data scientists is Python. When Python numerical engines like "Numpy" and "Pandas" were released, things started to change for academic researchers and independent researchers who had been using the MATLAB language for years. Python works with tabular, matrix, and statistical data as well, and it even plots it using well-known libraries like "Matplotlib" and "Seaborn."
Machine Learning
Because of its straightforward syntax and support for numerous machine-learning frameworks, Python is one of the computer languages most frequently used for machine learning.
Start Your Career As A Python Developer
The next step is easy now that you are aware of the Top 10 Reasons to Learn Python Programming and how it can advance your career. The thorough Data science with python course from Fingertips teaches you the fundamentals of Python, data operations, shell scripting, conditional expressions, and Django. The curriculum will give you practical development experience and prepare you for a fast-paced and fascinating job in Python programming.
Conclusion
So these were some of the most popular reasons to learn python programming in 2022. Python has emerged as one of the best programming languages in the industry and
Check out the Data Science with python Course from Fingertips if you're interested in learning Python and want to get your hands dirty with different tools and frameworks.
FAQs
1. What are the 3 benefits of Python?
The 3 benefits of Python are:
Ease of Comprehension Python's ease of use and enjoyment are two of its top advantages. Its syntax reads like English, unlike most computer languages, making it less difficult to learn than other programming languages. It manages complexity well, rather than the difficulties. And to top it all off, it is open-source and free.
Used in Many Industries Python is used in virtually every field because of its many advantages and versatility. The capabilities of new Python programmers extend beyond data science. You might instead work in:
Flexibility Python is not only adaptable but also simple to learn. There are more than 125,000 third-party Python libraries available that let you utilize Python for web processing, machine learning, and even biology. It is preferred in data analysis because it is particularly competent in processing, manipulating, and displaying data thanks to its data-focused modules like pandas, NumPy, and matplotlib.
- Computer science and mathematics
- Website creation
- Administration and system automation
- Digital graphics
- Elementary game creation
- A penetration test for security
- Scripting, both general and application-specific
- Geography and cartography (GIS software)
- Trading and Finance
2. What is the Python Programming Language?
High-level, all-purpose Python is a very well-liked programming language. The most recent version of the Python programming language, Python 3, is utilized for cutting-edge software development projects like web development and machine learning applications. Python is a very good programming language for beginners, as well as for seasoned programmers with experience in other programming languages like C++ and Java.
With subjects ranging from the fundamentals to the more complex (such as web scraping, Django, deep learning, etc.) with examples, this specifically created Python tutorial will assist you in learning Python programming language in the most effective way possible.
The following information regarding the Python programming language:
- Currently, Python is the most popular high-level, multipurpose programming language.
- Python supports procedural and object-oriented programming paradigms.
- Compared to other programming languages like Java, Python programs are typically smaller.
- Programmers have to type comparatively less, and the language's indentation requirement keeps their work always readable.
- Almost all tech organizations, including Google, Amazon, Facebook, Instagram, Dropbox, Uber, and others, employ the Python programming language.
- The vast standard library of Python, which may be used for the following things, is its greatest strength.
3. How Long Does it Take to Learn Python?
Learning the fundamentals of Python typically takes two to six months. However, you can quickly pick up enough knowledge to write your first brief program. Learning how to use Python's extensive collection of libraries can take months or years.
How much Python you need to know to complete your intended task will determine how long it takes you to learn Python, among other things. For instance, you can probably learn Python more rapidly if your goal is to automate a certain task at work rather than learn Python in order to become a data analyst.
Additional elements that may impact how quickly you learn Python include the following:
You need to have previous programming experience:
If you’ve some basic coding experience then you can easily learn python without any hassle.
Learning strategy: Depending on your learning objectives, well-structured courses may help you learn more quickly.
Learning time: How much time can you commit to studying and practicing Python? Generally speaking, setting aside a little time each day is a good idea.
