R vs Python programming languages
R is a programming language that has a free software environment for statistical computing and graphics boosted by the R foundation for statistical; computing. On the other hand, Python is a popular programming language. Some of the strengths of the R are used for data visualization, and the data can be suitably comprehended than raw numbers. R produces the best outcomes of visualization that can be utilized in study papers. Another R language offers a massive community help with 1000 developers and draws talents of information scientists distribute across the globe. The weaknesses associated with R language are, for the users with no programming knowledge, R language will be a little bit harder as it has a steep learning curve. Another weakness is that deriving right solutions with R programming language can be considered as slow if the codes are written poorly.
The strengths of using Pythons are, enables programmers to think Python coincides with the way programmers think more than R does and hence it translates over to other languages more simply. Python programming is utilized hugely for web development and automation testing. Python has gained vast knowledge and master programming with python to have the results as desired with a defined number of steps. The weakness of the using python is, they are slower in comparison with other programming languages as it as an interpreted language, it requires rigorous testing’s the errors show up in runtime.
The actual study where R was used for data analytics was by Google when it was used in predicting economic activity. It was used to fit autoregressive models to retail sales, automotive sales, homes sales and passenger arrival information. The study pointed out that R was used by Google for the examination of data from set-top boxes, to find the number of viewers for each ad. It was utilized for making online marketing more effective. The study discussed the value and role of R on google. The problem that was the catalyst for the research was the lack of economic activities and acquiring information on online marketing. Many of the methods were used, and they were not efficient. The use of R was the right choice for the problem that was to be solved because it was providing quality results that we’re solving the problem.