Basic Data Analysis with MySQL Shell Python mode

I recently watched a fantastic Python Pandas library tutorial series on YouTube. Without a doubt, Pandas is great for all sorts of data stuff. On the same token, MySQL Shell in Python mode is quite powerful in the sense that Python and the MySQL Shell (version >= 8.0) are somewhat united in the same environment. Although Pandas is in a league all its own when it comes to data analysis, between the power of MySQL and Python, we can also perform some basic analysis easily in MySQL Shell Python mode. In this blog post, I will cover some basic data analysis using Python mode in the MySQL Shell. Continue reading to see examples…

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MySQL Shell Python mode blog posts compilation

Over the last few months, I have written numerous blog posts on different features of the MySQL Shell ranging from basic CRUD to aggregate functions and DDL. As a part of the MySQL version 8 release, MySQL Shell is a powerful and alternative environment that you can manage and work with your data in using a choice of 3 languages: Python, Javascript, or SQL. So this blog post is a simple compilation of all the Python mode related posts, in one easy-to-access location…

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ALTER TABLE ADD COLUMN – MySQL Shell Python style

We all know as SQL professionals that a common use of the ALTER TABLE command is that we can change a tables’ structure in a myriad number of ways. And, that’s a good thing too because chances are, you won’t always nail down the initial structure. Due to changing business or application requirements, you may even have to add additional columns that were not considered during the schema design phase. Suppose you have many tables that are structured similarly and they all need a specific column added to their already-existing design. Under certain circumstances, using the MySQL Shell in Python mode (\py), can reduce the number of manual ALTER TABLE statements you have to type. Continue reading to see examples in the MySQL Shell…

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