The following editor will bring you an article on how to quickly find the difference in data in two spreadsheets in python. The editor thinks it’s pretty good, so I’ll share it with you now and give it as a reference. Let's follow the editor to take a look. I have just come into contact with python recently. I am looking for some small tasks to practice my skills. I hope that I can continue to exercise my problem-solving ability in practice. There will be such a scenario in the company: there is a spreadsheet whose contents are used by two, three or more departments. These employees will maintain these tables and update some data of their own departments from time to time. Over time, Everyone's data started to fight, which was very unfavorable for management. How to quickly find the differences in data in two or more spreadsheets? Solution: 1. The method that comes with Excel (if you are interested, use Baidu by yourself) 2. Write a small script in python #!/usr/bin/env python # -*- coding: utf-8 -*- #Import module openpyxl import openpyx
1. Introduction to how python can quickly find the difference in data in two spreadsheets
##Introduction: The editor below will bring you an article on how to quickly find the difference in data in two spreadsheets in Python. The editor thinks it’s pretty good, so I’ll share it with you now and give it as a reference. Let’s follow the editor and take a look.
2. Quickly find the differences in the data in the two spreadsheets
Introduction: I have just come into contact with python recently. I am looking for some small tasks to practice my skills. I hope that I can continue to exercise my problem-solving ability in practice.
3. Analysis of the differences between char and varchar in MySQL database and suggestions for their use_MySQL
Introduction: This article mainly introduces It is really good to understand the differences between VARCHAR and CHAR character data in MySQL and the suggestions for using these two character data in projects. Worth a look. The editor feels that I have benefited a lot.
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