In the past few posts, we’ve discussed how to read your data into pandas, and then manipulate it via calculations. At this point, we’ve come to the stage of deriving insights. To begin, this post discusses how to filter a DataFrame. Through filtering, you can focus on the part of your data that answers a
Tag: Filter
Filtering the data you want: The “WHERE” clause
Why is SQL necessary and useful? In essence, we have huge amounts of data and SQL enables us to extract what we need for specific business insights. So, filtering with the “WHERE” clause is a crucial part of using SQL. This Kaggle notebook contains all the code for following along with the examples. Run cells