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Data Science


With the massive growth in Data Science and Machine learning there are two programming languages have emerged as the most favorable and suitable language for the data scientists, which is trying to help in their own different ways. Mostly the two are considered almost the same yet different let’s discuss how?
R language is best for statistician as it possesses an extensive catalog of the statistical and graphical method. Python is preferent for its simplicity and high performances, both are free to use and open sourced language and have been introduced to the world in the early 90s. Data Scientists and data analysts look forward to both the languages as they work pretty much the same but even then why some of them work with Python and some with R.
R is a scripting language, with high flexibility with a vibrant resource bank, whereas Python is widely used object-oriented language, which is easy to learn and debug. Below are the comparison parameters between the two-
Ease of Learning- R seems to be more comfortable for the people who already work with programming languages, so it looks difficult to the ones who are from a non-technical background, but ones you get the grip on the language it's not that tough to understand.
Python emphasis on productivity and code readability which makes it one of the simplest languages, it is a preferable language for experience and beginners.
Speed-R is low-level programming languages and requires longer codes for simple procedures, this also reduces speed. python is high-level programming language and it has been the choice for building critical yet fast applications.

Data Handling capabilities- R is convenient for analysis due to the huge number of packages readily usable tests and the advantage of using formulas, but it can also be use for basic data analysis without installing any package. And only Big data Set requires Packages- like datadot table packages.
Python packages for Data were not there, but it has improved with recent versions- NumPy and Panda are used for data analysis in Python. This takes us to the conclusion that both languages are used by data Scientists and parallel computation.
Graphics and Visualization- A picture is a word to 1000 words, visualize data is understood efficiently and effectively than Raw values, R consists of numerous packages that provides advanced graphical capabilities like- ggplot2 is used for customized graphs.
Python also has some amazing visualization library such as C born etc. it has a greater number of libraries as compared to R, but they are more complex and gives a tidy output.
There are more such difference which makes one another a better option to choose from, some choose R, and some go for Python. Data Science has a wide variety of such languages which works as helping hand.


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