If R was the mainstream of data academia before 2018, but now Python is slowly replacing R's position in academia.
Python is faster compared to R. Python can directly process the data on G; R can't. When R analyzes data, it needs to convert big data into small data (through goupby) through the database before handing it over to R for analysis. Therefore, it is impossible for R to directly analyze the detailed list of behaviors. Analyze statistical results. So some people say: Python=R+SQL/Hive, it is not unreasonable.
One of the most obvious advantages of Python is the characteristics of its glue language, which is also mentioned in many books. Some low-level algorithms written in C are encapsulated in Python packages with very high performance (the ones in Python's data mining package Orange Canvas). Decision tree analysis of 500,000 users produces results in 10 seconds, and R can’t come out for a few hours, and all 8G memory is full).
Now Python has pandas. pandas provides a standard set of time series processing tools and data algorithms. As a result, you can efficiently process very large time series, easily slice/dice, aggregate, resample periodic/irregular time series, etc. As you might have guessed, most of these tools are especially useful for financial and economic data, but you can of course also use them to analyze server log data. Thus, in recent years, Python has become a great alternative for data processing tasks due to its constantly improving libraries (mainly pandas). You can also add a buttoned skirt to the learning materials: 483546416 You can enter the group to download and study. If you have any questions, you can discuss and share with everyone in the group.
In general, Python is a relatively balanced language, and it can be used in all aspects. Whether it is calling other languages, connecting to data sources, reading, operating systems, or regular expressions and word processing, Python has obvious advantage. Combined with its strength in general-purpose programming, we can build data-centric applications using just one language, Python. ,
Python has become the introductory language for computer programming in a growing number of top universities in the United States. MIT and the University of California, Berkeley, the top computer-ranked universities in the United States, have changed their language of instruction for introductory computer programming to Python.
The three major MOOC providers (edX, Cousera, Udacity) all offer introductory computer programming courses taught in Python. At the same time, professors in different professional fields also advocate the use of Python as an introductory language for teaching.
Using Python as the framework for the entire process, and then calling C functions from the CPU-intensive operation part of the core, the development efficiency and performance are good, so learning Python is an indispensable skill for those who want to engage in big data careers'. '