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This article mainly explains "what are the advantages of using Python to do data analysis". The content of the article is simple and clear, and it is easy to learn and understand. Please follow the editor's train of thought to study and learn "what are the advantages of using Python to do data analysis".

Advantage 1 of Python:

"controllable process and efficient work"

For example, the Excel analysis process: locate null values-delete null values-modify data format-remove abnormal values-formula calculation-data toushi table-collate data-insert charts-adjust results.

Every tedious step comes from a mouse click, and if one step is wrong, many steps need to be readjusted, wasting a lot of time.

Use Excel for simple description and statistical analysis, and each change of data needs to be operated again.

But it is very convenient to use Python to write every step of the process, and the unified language brings the unity of recording methods. When the analysis process needs to be modified or reused, only the set parameters need to be adjusted.

Using Python code, you can quickly call data, calculate requirements, and record each step for easy modification.

If you want to make a variety of good-looking charts, you can use Python visualization tools, a few lines of code, save time and effort, but also have interactive functions. If you need to adjust, just modify the code, do not bother to redraw the picture.

Python advantage number two:

"rich tool library"

The super popularity of Python has brought a large number of great gods, and the Python tool library is available, which has laid an excellent foundation for a wide range of uses of Python.

Take data analysis. Take matplotlib, the basic Python visualization library, as an example. Official gallery alone has 26 categories and 527 styles, which can crush most of the same functional software on the market in terms of quantity and quality.

Advantage 3 of Python:

"Xiaobai is friendly and easy to use."

Hearing Python, people think it is a programming language, many people will have such concerns: I am a non-computer-related professional background, do I miss learning Python programming? Do I spend a lot of time learning computer programming?

There is no need to worry about this. Nowadays, all kinds of industries need data analysis ability, all kinds of industries need Python, and the grammar of Python is very close to English, and it is very friendly to rookie learners. Reading Python code is like reading an article. Let's take a look at a piece of code that uses Python to create a word cloud map, which is very easy to understand:

From pyecharts import WordCloudname = data_10 ['keyword'] .tolist () value = data_10 ['occurrence frequency'] .tolist () wordcloud = WordCloud (width=1300, height=620) wordcloud.add ("", name, value, word_size_range= [20,100]) wordcloud.render ('. / reference case HTML/ keyword statistics word cloud map .html') wordcloud

Import the word cloud toolkit-set keywords and occurrence frequency-set parameters such as the size of text and pictures, and you can get a word cloud image:

Thank you for reading, the above is the content of "what are the advantages of using Python to do data analysis". After the study of this article, I believe you have a deeper understanding of what the advantages of using Python to do data analysis have, and the specific use needs to be verified in practice. Here is, the editor will push for you more related knowledge points of the article, welcome to follow!

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