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This article mainly introduces "what are the advantages of R and Python". In daily operation, I believe many people have doubts about the advantages of R and Python. The editor consulted all kinds of materials and sorted out simple and easy-to-use methods of operation. I hope it will be helpful to answer the doubts about "what are the advantages of R and Python?" Next, please follow the editor to study!

In terms of data analysis and comparison, I think the advantages of R are as follows:

1. Learning is easy before it is difficult, and it will not scare off the rookies.

2. There are many packages in data science.

3. Visualization is special.

R also has many disadvantages:

1. R is updated frequently, and the package you installed before is often not supported after the update. I have installed 10 + R versions in my computer and keep switching.

2. The package and function names in R language are very random. I don't know what the name is for. I can't remember how to let rookies use it.

There are few people in the R language community, so you can only solve the problems by yourself.

4. Even with RStudio, it is still not convenient to write code.

Let's talk about the advantages of python:

1. It is a language that you can read and understand and speak human words. Library name, function name are easy to understand memory, and you look at the code written by others basically know the meaning of this code, do not believe you try.

2. Data acquisition is dominant, and the first step in data analysis is data acquisition. Now a lot of humanities and social sciences data need to be crawled online, but as far as data acquisition is concerned, python is more advantageous. A variety of tutorials, code, a large number of online.

3. There are so many people in the community that you can find almost all the problems you encounter.

Disadvantages of python:

1. It is difficult to learn at the beginning, and the learning curve is just the opposite of R.

2. To be fair, I would like to write that python does not have as many data analysis libraries as R

3. Visualization is not as good as R

In fact, discerning people know at a glance that I prefer python. Tell me about my learning experience in these two languages. I started to study R in September 2015. At that time, I thought I wanted to study consumers in the graduate research network, so I had to collect and analyze data. And R happened to be satisfied, so I learned and learned until December and stopped.

At this point, the study of "what are the advantages of R and Python" is over. I hope to be able to solve your doubts. The collocation of theory and practice can better help you learn, go and try it! If you want to continue to learn more related knowledge, please continue to follow the website, the editor will continue to work hard to bring you more practical articles!

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