Both ython and r have huge user support. According to the survey in 20 17, nearly 45% of data scientists use Python as their main programming language. On the other hand, 1 1.2% of data scientists use R language.

The differences between python and R language are as follows:

Advantages of Python:

1.python contains richer data structures than R to achieve more accurate data access and memory control. Most deep learning research is done in Python.

Python is faster than R, and Python can directly process G data; R can't When analyzing data, R needs to convert big data into small data through the database (through groupby), and then give it to R for analysis, so R can't directly analyze the behavior list, only analyze the statistical results.

3. Another advantage of 3.Python over R is to deploy the model to other parts of the software. Python is a universal language, and the process of writing applications (including Python-based models) in Python is seamless.

4.Python is a relatively balanced language, which can be used in all aspects. Whether calling other languages, connecting and reading data sources, operating systems, regular expressions and word processing, Python has obvious advantages, especially in computer programming and web crawler.

Advantages of r language:

1.r is a more efficient independent data analysis tool in statistical analysis. Do a lot of statistical modeling research in R, and have a wider range of model classes to choose from. If you have questions about modeling, R is the most appropriate.

Another skill of 2. R is easy to create dashboard using Shiny. Python also has Dash as an alternative, but it is not mature enough.

3.r's function is developed for statisticians, so it has advantages in certain fields, such as powerful data visualization function. Ggplot2 was founded by Hadley Wickham, the chief scientist of R Studio, and is now one of the most popular data visualization software packages in R history.

Ggplot2 allows users to customize drawing components at a higher level of abstraction. I personally like the various functions and customization of ggplot2. More than 50 kinds of images provided by ggplot2 are suitable for various industries.