Data is a new growth engine and data science help enterprises to extract meaningful information and make tactical decisions and visualization. There are various languages like C, C++, Java and JavaScript are being used but the most popular languages is R and Python provide great value and become a popular data science tool. But still python and R is case sensitive language. Its originated from C language.
Python
Python can do the same tasks as R: data wrangling, engineering, feature selection web scrapping, app and so on. Python is a tool to position and implement machine learning at a large-scale. Python codes are easier to maintain and more robust than R. Python provides cutting-edge for machine learning or Artificial Intelligence and there are so many python libraries ,commonly used library NumPy, Pandas, SciPy, matplotlib, Scikit-learn and Seaborn.
Python makes replicability and accessibility easier than R. In fact, if you need to use the results of your analysis in an application or website, Python is the best choice.
R
R is one of richest ecosystems to perform data analysis and 12000 packages available in CRAN (open-source repository). The rich variety of library makes R the first choice for statistical analysis, especially for specialized analytical work.
The cutting-edge difference between R and the other statistical products is the output. R has fantastic tools to communicate the results. R studio comes with the library knit. Xie Yihui wrote this package.
Many Tech giants like Google, Netflix and Facebook and Khan Academy are using python as the most prominent language. It easily integrates with cloud and multiprocessing for parallel computing, Python can also be extended with modules written in C/C++. Following are the features which make it a market leader.
- Easy to learn
- Scalability
- Choice of data science libraries
- Python community
- Graphics and visualization
Data science fields is changing rapidly and there are various tools used for extracting value from data science and R and Python which has become the most popular language in the data science world.
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