Last Updated on by Kumar Raja

Typical Reasons Why Python Is the Most Preferred Language for Data Science

Being interdisciplinary in nature, Data Science makes use of multiple techniques, tools, algorithms and technologies to explore the insights from Big Data. The applications of Data Science also rely heavily on the use of coding and Python is considered as the most preferred language in this regard. Most of the Data Scientists and other analytical experts make use of Python for data analytical operations. Having many decent libraries being backed by a large community base, Python has numerous advantages when it comes to analyzing Big Data.

Although there are many programming languages like Java, Scala, MATLAB, R, etc the ones that are having inactive communities would often find it difficult to get updates and this is the main advantage of Python. You can develop master Data Science with Python with our advanced Data Science Training in Hyderabad program. 

Typical Reasons Why Python is Preferred for Data Science:

  • Learning Python is a Lot Easier & Fun

Python script is very elegant and is easy to read and execute coding with Python. Learning Python doesn’t involve any difficulty & its easy learning approach is attracting Data Scientists to prefer learning Python over any other programming language.

  • Backed by Large & Active Community Base

Python is backed by a large community base and it is used not just by Data Scientists but also by a large number of people across other communities as well. The active community base results in frequent updates in terms of libraries and packages.

  • Many Libraries and Packages

Python has a number of libraries and Packages that support analytical operations on Big Data. Pandas, NumPy, SciPy, StatsModels, Scikit-learn, etc are among the most extensively used libraries in Python for Data Science. 

You can learn Data Science with Python by working on multiple projects with Data Science course by Kelly Technologies.

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