Rocket science resembles something very tough to understand. Python and R are not rocket science. If you are a beginner in data science with no prior knowledge in programming it will need the same effort to learn R and Python. If you are from a statistical background with no programming knowledge, R is a good choice for you. In terms of data science, both the languages are extremely effective and to become a skilled data professional you must know the use of both R and Python.
They are the two widely-used data analytics tools to execute the day-to-day activities of data scientists. However, there is a doubt or confusion about which language is better than other. It is a hot topic today in the world of data science as both the tools have their pros and cons.
How can a beginner understand which one is good for him or her? It is a challenging task to understand the fact. So, it is better to go through the features of both the languages
Features of R
1. HYPERLINK “https://handson.teachable.com/”R is an open-source language thus, highly available. You can install and use it as per your choice and needs. It is easy to upgrade.
- R can handle large and multifaceted data sets
- It supports many new statistical developments as it is very flexible and resourceful. You can perform the most precise statistical tasks on Psychometrics, Genetics, and even on Finance with R
- It is an excellent data visualization tool for data scientists.
- As there are already-written packages over there, a wide community supports R. It helps you hugely in your tricky analytical jobs.
- Usually, it is used for academic and research data analysis purposes.
- It is easy to learn R. Once you learn the basics of R, you can easily grasp the higher concept of this language.
- R packages are exclusively designed to make data analytical and statistical jobs easy. However, some find R processing as a bit slower.
Features of Python
1. Python is a purposeful programming language and persons with familiar programming knowledge can easily code with Python. It is coupled with comprehensible features like code readability, easy structure, and trouble-free execution. Python gives users a scope to less code.
- With its strong correcting and less-coding features, Python is an excellent option for programmers to step into the data science field.
- Python is open-source software hence, cost-effective.
- Because of its high-performing ability, it is a good alternative to solve critical business scenarios.
- Python is the perfect tool for Machine Learning, Deep Learning, and other Data Science courses.
- It has a scripting feature. So, you can use it in business applications as well for scientific computing intention. Furthermore, industries widely use this language for data-centric application development.
- Python offers many functional data analysis packages.
- Python is effective for visualization purposes.
In case of popularity, Python is more popular than R. It is because R is used by data scientists only where python offers a range of jobs from developer to data scientists with high salary profile. From a data analytics perspective, R is popular but more and more people today are learning Python for its versatile usability and easy syntax. Tech-giant companies such as NASA, Google, Youtube choose Python for its flexible and dynamic features.
To become a skilled data professional or to become an expert Machine Learning professional, Hands-On is the ultimate destination. This data science organization provides several courses and a great learning atmosphere for interested individuals.