Python is highly popular, both as a programming language and as a tool for data science. Multiple surveys conducted across the world shows how the popularity of python has been continuously rising over the past few years and how it has slowly but successfully gone past its competitors like Java and C++. Top level organizations like CERN and NASA and tech giants like Google and Netflix use Python as a core programming language and also as a tool for data science!
- SlashData, a leading analyst firm, estimates that approximately 8.2 million users use Python worldwide including 69% data scientists and machine learning experts!
- According to a survey undertaken by Kaggle which is the largest data science community in the world, approximately 81% among the 16000 data professionals (number participants in the survey) reported using Python for data science!
- Python has also been leading the TIOBE index year after year!
- The IEEE spectrum’s ranking also testify that Python is by far the programming language of choice for professionals worldwide!
Interestingly, most surveys also point out to the fact that newcomers in the field of data science are more prone to prefer Python over anything else- A staggering 48% according to CBT Nuggets!
Why is Python so popular among data science
Python is generally known as a general-purpose programming language and frequently criticised for its lack of capabilities on statistical analysis like R. Then what is the reason that most go for Python? Well, there are several:
- Python is simple
One of the top reasons why Python is preferred by newcomers in the field is the fact that Python has by far the easiest learning curve among its competitors like R. The syntax is fairly simple and does not bother users with complicated programming requirements. People even without any prior knowledge can master Python with the help of a suitable training program. Moreover, data science professionals prefer using Python because it is easy to use and they can focus more on data related problems rather than getting bogged down with coding.
- Tailor made data science libraries
Perhaps the biggest reason behind Python’s overwhelming popularity is the fact that it offers dedicated libraries for every possible data science task. With over 72,000 libraries included in the Python Package Index, data scientists can easily find tools on their fingertips. Let us discuss some of those extremely popular and highly advantageous libraries:
- NumPy and SciPy for easy scientific calculations.
NumPy and SciPy are popular python libraries which are instrumental in performing advanced scientific or mathematical calculations with ease. NumPy is also very famous as it enables users to create multidimensional arrays which is vital for handling Big Data.
- Pandas for Data manipulation and analysis
Pandas python library is used for data manipulation, analysis and also for data munging and wrangling. Performing such operations is highly beneficial with Pandas because it offers high level data structures and manipulation tools.
- Matplotlib for data visualization
Data visualization is one of the most important aspects in data science and analytics. It helps to understand data better and professionals use it for communicating with all the stakeholders of a project including non-professionals. And Matplotlib is one python Data science library which is highly useful for data visualization.
- Advantages in ML and DL
Machine Learning (ML) and Deep Learning (DL) are two subsets of artificial intelligence which have emerged as vital tech for data science. Data scientists use ML and DL for automation and also for building sophisticated products like virtual assistants and systems capable of predictive analytics. And Python is extremely preferable when using ML and DL. According to builtwith.com, 45% of tech firms in the world use Python for implementing ML and DL!
Moreover, popular ML and DL libraries like TensorFlow and Keras are built on Python. This is very important because it makes Python essential for aspiring candidates who wish to use such libraries!
So, should you opt for a Python course in India?
There is no doubt that Python skills can be highly beneficial to any aspiring data scientist or analyst. Interestingly, Python is mentioned in more than 60% of data science job postings around the globe.
In India too there is a huge demand for data professionals with Python skills and with a Python course in Delhi, Bangalore or Pune you can easily take advantage of the demand. India is home to a multibillion-dollar analytics industry consisting of major players like Google, Accenture and Fractal analytics. Thus, by going for a Python course in Delhi or any other major Indian city you stand to gain big!