This article is a summary of what I consider to be the most important concepts of the book Domain-Driven Design, by Eric Evans. I tried to condense the most important ideas in a single article for anyone interested in the topic. I attempted to pack in as much information as
I recently started working on a couple of side projects that require a bit more attention and time than I expected, so I decided to put the article schedule on hold for a while so that I can focus on finishing them.
I expect to be back with
We have already covered most of the fundamentals of working with data using the Pandas library. There is one more topic I'd like to discuss before concluding the series: The Apply function.
In the previous article, we learned how to create subgroups of data using the groupby function. This is
Sometimes you need to perform operations on subsets of data. Your rows might have attributes in common or somehow form logical groups based on other properties. Common operations like finding the average, maximum, count, or standard deviation of values from groups of data is a really common task, and Pandas
Merge/join operations in Pandas let you gather information from many tables into a single dataframe for further processing or analysis. This is another important skill that you will probably use a lot when working with data.
If you have some experience with relational databases you can recognize the analogous