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This article mainly shows you "what are the advantages of data analysis in Python", the content is simple and clear, and I hope it can help you solve your doubts. Let me lead you to study and learn this article "what are the advantages of data analysis in Python".

Preface

If you have some knowledge of data analysis, you must have heard of some popular data analysis tools, such as Excel, Tableau, PowerBI, etc., which are all right-hand men for data analysis. For example, partners who often use these bases must also have troubles, and the shortcomings are also obvious: tedious operation, poor reusability, and relatively limited and simple functions.

Many partners who often use data analysis will ask if there is a convenient and easy to use tool! There must be, ah, the emergence and popularity of Python can easily change these dilemmas!

How to solve it? -- Python

Python has many advantages, if you can make good use of it in your work, you will find that your work efficiency has been greatly improved, and it is normal for you to raise your salary.

Advantage 1 of Python:

"controllable process and efficient work"

For example, the process of Excel analysis: locate null values, delete null values, modify data format, remove abnormal values, calculate formulas, PivotTable, organize 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.

Excel, Tableau and PowerBI can all do data analysis, so why use Python?

Matplotlib official website: https://matplotlib.org/tutorials/index.html

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:

As you can see, the code can be more efficient, rich and free in data analysis. In fact, the code not only helps analysis, but also helps logical thinking.

Of course, this is only a small suggestion, but many skills do not weigh on the body, there is a need in this area, you can still learn some!

The above is all the contents of the article "what are the advantages of data analysis in Python". Thank you for reading! I believe we all have a certain understanding, hope to share the content to help you, if you want to learn more knowledge, welcome to follow the industry information channel!

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