Use of Python in the field of Data Science
Before beginning in python career as data analyst and data scientist, there is a much striking question hovering over the minds of aspiring data experts ‘Which is the most famous and useable language being utilized in data science industry or by data professionals?’. There are many languages in the row used by data scientists and analysts like Python, R, C, C++ but Python holds a very dominant place among all other languages.
Python is a general purpose high level programming language created by Guido van Rossum in 1991. Python is an object oriented, open source, interpreted, adaptable and simple to learn language. Python comes with the features of high level built-in data structures along with dynamic typing and dynamic binding which makes it very attractive for rapid application development tasks as well as for development of complex numerical and scientific calculations. This type of versatility of Python makes it one of the fastest growing programming language in the world of data analysis field. Moreover, it has a rich collection of libraries and data processing tools which helps data scientists to build up their assignments easily. Additionally, it provides an enormous python community space where data engineers can submit their queries and get answers from others.
Essential features of Python in Data Science
Let’s talk about its benefits in detail in Data Science.
Most of the data science business organizations are now empowering their data professionals with Python skills as they have acknowledged the use of Python in business world.
- Easy to Use and Learn:
Python is very easy language to use and provides a fast learning curve for new data analysts & scientists with its simple utilization & better comprehensibility. It also provides the feature of data mining to handle large scale of datasets in a better way. Easy to use and significant list of libraries are Numpy, Pandas, Tensorflow and many more for different useful purposes.
- Flexibility:
If you want to put some extra creativity which you have never done before, then Python is the best option for you, i.e. it not only lets you give ease of usability but also deals with crucial scientific calculations, computing logical data analysis terms and web development. Python indeed, has become ubiquitous trend on the web dominating over various data analysis fields.
- Ability to Create Better Analytical Tools:
Data analysis is a necessary task for data scientists in big data domain. Python is the first ever choice for data professionals to create best analytical tools which plays a vital role to assess the performance of any business. These tools can easily get knowledgeable insights and examples from large datasets of organization.
- Open Source:
Python is open source language which means it’s completely free & can be used by anyone. It runs on any OS platform Windows, Mac, Linux & Unix.
- Better for Deep Learning:
Python significantly gives the power to help out in terms of deep learning algorithms i.e. it offers a number of packages like Tensorflow, Keras and Theano assisting data analysts and scientists to deep learning algorithms, which helps to manage artificial neural networks. Deep learning neural networks gives the desired results for data professionals.
Conclusion:
By sum up these points of Python, it concludes that both data experts and business stakeholders are frequently improving their decision making vision & mission execution with the help of real time use cases of Python.
