How to Use Conditional Expressions With NumPy where()
The NumPy where() function is a powerful tool for filtering array elements in lists, tuples, and NumPy arrays. It works by using a conditional predicate, similar to the logic used in the WHERE or HAVING clauses in SQL queries. It’s okay if you’re not familiar with SQL—you don’t need to know it to follow along with this tutorial.
You would typically use np.where() when you have an array and need to analyze its elements differently depending on their values. For example, you might need to replace negative numbers with zeros or replace missing values such as None or np.nan with something more meaningful. When you run where(), you’ll produce a new array containing the results of your analysis.