Why Python for Data Science

Datamites Team Datamites Team
Jan 24, 2021 Updated: Mar 12, 2024
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Why Python for Data Science
Why Python for Data Science
  • The creator of the popular programming language Python was Guido Van Rossum and it was available in usage by 1991.
  • Python is a general-purpose and flexible language used by data scientists and developers which makes it easy to collaborate across your organization through its simple syntax

Who are all the main users of Python?

  • Programmers who want to explore into data analysis or apply statistical techniques are the users of Python.
  • Python programming has structured ways to do Machine learning, Deep Learning, Artificial Intelligence and Computer Vision which can deal with larger amounts of data.
  • As people shift more to deep learning and Artificial Intelligence the bias has been shifting towards Python.
  • The demand for Data Science professionals will grow high in the future and professionals with Python skills will have an additional advantage.

Python Vs R

Python R

  • Python codes are robust and easier to maintain
  • Python is a general-purpose language which is used for development, deployment and visualization purposes
  • Python has simple English like syntax
  • Python is faster
  • Python is well suited for building new from scratch and building applications

R

  • R codes need more maintenance
  • R Programming is a statistical language and used for visualization purpose
  • R has a definite syntax which is essential to understand
  • R is slower than Python
  • R executes complicated mathematical calculations and statistical tests easier

Python Vs Other Programming Languages

Python is the most used programming language among other languages such as R, Julia, MATLAB, Scala and SQL. This is revealed by Kaggle on a survey of most used Programming languages by Data Scientists.

Python has powerful packages which can solve the complex problems by using these four major steps

  1. Data Collection and Cleaning
  2. Data Exploration
  3. Data Modelling
  4. Data Visualisation

The potent libraries present in Python are Numpy, Pandas, Matplotlib, SciPy, scikit- learn, etc which helps to do statistical and numerical manipulations.

Moreover advanced deep libraries such as Tensorflow, PYBrain, etc give a complete working environment for the Data Scientists in Python.

Additionally, Python features as the default language for Artificial Intelligence and Machine Learning.

Therefore, Python marks as a remarkable language among the other programming languages in the Data Science field.