Why python is the most widely used language in data science?


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Why python is the most widely used language in data science?

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Python is a pure object-oriented language.

Key points that make python better than other languages

  • Problems with C, CPP, and Java in Data Science
  • It is an interpreted language
  • Huge library support
  • Easy to adapt/learn
  • Less Development Time
  • Availability of Special IDE for Data Science like Jupyter and Spyder


In data science we have to perform so many tasks like web scraping, data cleaning, machine learning for that c, cpp, and java don’t have that much support from libraries to perform such kinds of tasks efficiently. The code size will be very large and the compiler will run the whole code once so to check a particular portion we have to run the whole code again and again. Unnecessarily we have to waste our time.

As python is an interpreted language. An interpreter directly executes code by converting it into byte code. It executes code line-by-line and gives correct information of error if any. In the jupyter notebook, we can run part of the program separately instead of running the whole script, which is not possible in other languages.

Python has huge library support like pandas, NumPy,matplotlib,plotly, etc. With the help of those, a large line of code can be reduced to few lines. For example Gradient descent in regressioncan be possible in 2 or 3 lines of code in python wherein cpp takes more than 100 lines of code. We can easily visualize data very efficiently. Also, we have so many frameworks available for python.

Syntax in python is very easy, compared to other languages. for example no need for curly braces, no semicolon needed, we don’t have to mention data type while declaring a variable and so many things.

This is how simple it is:

As everything already available in python you can spend more time on building your project. which will lead to less time to develop.

There are powerful IDE’s for Data Science like Jupyter and Spyder. Which allows us to run our code in separate portions. We can run a particular function and can check its functionality.

If you learn python then learning the R language will not be any difficult task for you because python is the superset of the R.


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