Never before has the ‘Data’ been considered a highly valuable commodity. Today we are generating 2.5 Quintillion bytes of knowledge per day. One would be ready to comprehend the mammoth size of this number by realizing the particular incontrovertible fact that 90 per cent of the prevailing worldwide data has been created within the past two years. And to cover the rapidly growing $189 Billion Global data industry, certain specialized tools are required. Here, we are talking about Python as a programming tool within the world of Data Science.
If you’re looking to form a career as a data Scientist professional, then you’d possibly be considering a good Python from a reputable Institute like PST Analytics. It’ll surely assist you to kick start a rapidly growing career in this field.
Go ahead and skim this post to hunt out the explanations on why Python is preferred over other Data Science tools.
Data Science with Python is easy
Today, we can use many tools for data Science. However, Python outruns them in most aspects. Python’s features and comparatively efficient and lightweight code makes it a preferred tool for processing large data sets. Let us give you an example, Python is compatible with Hadoop because of its multiprocessing capabilities.
One more useful aspect of data science is in Machine Learning that ultimately is the driving factor behind AI.
Easy and simple to learn
It can become tiring to spot open or close curly braces within the code if one is employing a typical language like C++ or Java. Also, personnel are often excellent with numbers but not with coding. For the beginner Data Science professionals, all these points are already addressed. Firstly, Python resembles English which makes it familiar to the person. Secondly, it’s an outsized support community over the world and a package index with 1,30,000+ projects to serve any programming need. As a fresher into data science or analyst, you can expect to start out using Python in lifestyle within a couple of days of coaching from a reputed training institute.
Inbuilt libraries and functions
This beautiful language has many inbuilt libraries that are nothing but a gaggle of codes and scripts which may be used for any Data science or analytics need. Sort of the highly useful packages that have made Python popular are numpy, panda, django etc.
Data Visualization is also possible
Today data visualization is powering modern-day enterprises with informed decisions. Visualizing the data is nothing but the representation of numbers and thus the correlations between them as graphics for easier interpretation. Though there’s a debate on whether ‘R’ or ‘Python’ is best for programming, Python certainly has improved its Data Visualization game within the past years. So, we have libraries such as ggplot, Matplotlib, Pygal, NetworkX, etc. and API like Plotly, this language is becoming a well-liked choice for Visualizing Data.
Python is flexible in use
Python has been labelled as a flexible tool by the programming community across the earth. Python could even be a one-stop solution for Developers and is certain to grow manifolds within the approaching years. It’s employed with equal suitability for AI, ML, Big Data, Web Development, etc. Moreover, Python is the first choice of individuals for DIY Projects, Startups, Medium-Sized Companies and Giant corporates alike. Its code is straightforward to compile, analyze and scale. The code is additionally lightweight and highly scalable. One more useful part of python is its ability to ‘Automate.’ Python is the foremost preferred language for automating simple or complex computing operations. Python allows you to run ‘Scripts’ which are collections of codes which may check themselves for Runtime errors.
So, if you want to learn python now for data science, then you can check the PST Analytics website to know more.