Text mining recruitment

These two tools are very convenient, do not need very advanced programming ability, are suitable for algorithm development, and there are a large number of packages for you to use.

Python is relatively easy to use, while R is relatively difficult (purely personal feeling, depending on your previous experience, you may have different experiences).

R is still a little weak in text mining. Of course, its advantage is that the function is written for you, and you only need to know the form of the parameter. Sometimes, even if the parameters are in the wrong form, R can "intelligently" help you adapt. This simple software is suitable for people who want to focus on their business.

Python can do almost anything, with more functions and faster speed than R. It is a language, and R is more like a software, so Python can develop more flexible algorithms.

Python is suitable for processing large amounts of data, and R has many difficulties in this respect. Of course, the premise of this is that for children's shoes with a relatively general programming foundation, for Daniel, if vectorization programming is used flexibly, the speed of R will not be too bad.

In performance, Python is between C/C++/Java and R language. Although its performance is not as good as those of high-level languages, ordinary daily data can basically be realized in Python, which is enough for people who are not picky about performance requirements.

Python

You need to install numpy, pandas, scipy, cython, statsmodels, matplotlib.

It is necessary to install a series of packages such as python in an interactive environment, and there is no functional support for quantitative analysis and statistics directly using Python. Based on statistical analysis, R is slightly inferior to python in performance and efficiency. The advantage of R is that it is superior to python in statistics and data calculation and analysis.

Python language programming code is readable, overall beautiful, simple and rude, and a small amount of code can realize complex functions in a short time; R's grammar is very strange, all kinds of packages do not follow the grammatical norms, and it is often painful to use; In the end, the R program doesn't look as simple and beautiful as Python.

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On the whole, I think Python is really better than R. Whether it is calling other languages, connecting to read data sources, operating systems, regular expressions or word processing, Python has its own advantages.

A clear advantage. After all, python itself appeared as a computer programming language, while R itself only originated from statistical calculation. Therefore, from the perspective of language comprehensiveness, there are significant differences between the two.

Python is a machine

People in the field of learning use it more. As far as I know, doing market research, econometrics,

Statisticians hardly use python.

Reference from: blog.sina.com.cn/s/blog _ 8813ae01kloc-0/e631.