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Today, I will talk to you about how to use Python to enhance the three major integration methods and uses of Excel, which may not be well understood by many people. in order to make you understand better, the editor has summarized the following contents for you. I hope you can get something according to this article.

No one can avoid Microsoft Excel-you either love it or hate it. Maybe before graduating from college, Excel only meets a few friends during the exam week, and the relationship is limited to the familiar face. But when the work enters the enterprise, you will find that if Excel disappears for an hour, the whole world will stop working!

Excel can do almost anything. As someone with years of investment banking experience, every time I think I've read all the content, I come across another spreadsheet that someone else has sorted out! the possibilities of Excel are limitless.

However, at present, the main limitation of Excel lies in the larger data set. The larger the dataset, the greater the difficulty in processing with Excel. In a data-driven, instant gratification world, everyone hates waiting for things to be done immediately, constantly breaking boundaries and growing levels of functionality.

At the same time, people hate change. People are used to using Excel and don't want to leave it. Therefore, our job is to provide faster speed, more features, to make the conversion easier, without leaving the spreadsheet. And Excel does not support big data. This is not, this is the opportunity for Python to show his talents.

Integrate Python into Excel to enhance the functionality that Excel provides to users. This allows users to stay in the familiar, easy-to-understand world of Excel, and Python can help with some heavy work. It provides a transition for this data-driven world until Excel and less skilled colleagues catch up.

Explore some available solutions and use Python's superpower to enhance Excel!

Using Excel as the user interface

Transforming the user base from spreadsheets to the 21st century is not easy. It takes time to polish. It is the responsibility of professional IT people to help users tide over the difficulties. This process requires adequate guidance, trust and recognition. First, consider keeping the user interface (UI) consistent, that is, leaving the spreadsheet as is and moving all back-end processing from VBA to Python.

The Python package xlwings seamlessly integrates Excel with Python. Users can continue to use Excel, but each form control button or user-defined Excel function can call the Python script. Xlwings is easy to install and feels great to use.

Looking for a new Excel

With the explosive growth of technology, data, and data science tools, a new type of user has emerged: Power-users. Superusers know the technology, the data, and write code. They need freedom to express and solve problems, and are more than happy to abandon spreadsheets and use new technologies.

So how can they be given such flexibility?

Jupyter Notebook enables users to take advantage of Python and create shareable, Web-based interactive documents that can contain real-time code, visualization, and text, while data can continue to use enterprise data sources and databases.

Input in Excel

People have become accustomed to using Excel and the generated data is likely to continue to exist in spreadsheets. However, as the volume of data to be analyzed increases, users will immediately feel the impending end of Excel. Data manipulation takes a long time, and the data perspective is always changing, as long as the Excel does not crash.

You can quickly load data from a spreadsheet into an pandas DataFrames or SQL database using the popular pandas library. Both of these solutions can make data analysis and exploration fast and easy.

Other libraries that can be considered

Here are some of the popular Python libraries available for Excel. The libraries mentioned above will be able to meet most usage requirements, but if you are looking for Excel-specific features (such as formatting, filters, etc.), you may want to explore the following libraries:

Openpyxl: you can read and write Excel 2010 files, write new worksheets in Excel, edit existing worksheets, and do almost everything you can do with the mouse. It supports almost all extensions to Excel.

Xlrd: a library for reading data and format information in Excel files.

Xlsxwriter: probably the most complete Excel Python library. Formatting, conditional formatting, charts, merging cells, filters, comments, and integration with pandas are just some of the features it provides. If you want to use the full functionality of Excel through Python scripts, you can start with this library!

Excel is an extremely powerful and versatile tool, if you are not familiar with it, you'd better learn it quickly! the main limitation of Excel is big data, and it is estimated that it will not take long for Microsoft to rescue it. Until then, we can use Python to solve some of the problems we may encounter.

After reading the above, do you have any further understanding of the three integration methods and uses of how to enhance Excel with Python? If you want to know more knowledge or related content, please follow the industry information channel, thank you for your support.

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