Numerical Computing with Python

How it works...

By default, the mask method covers up data with missing values. The first parameter to the mask method is the condition which is often a boolean Series such as criteria. Because the mask method is called from a DataFrame, all the values in each row where the condition is False change to missing. Step 3 uses this masked DataFrame to drop the rows that contain all missing values. Step 4 shows how to do this same procedure with boolean indexing.

During a data analysis, it is very important to continually validate results. Checking the equality of Series and DataFrames is an extremely common approach to validation. Our first attempt, in step 4, yielded an unexpected result. Some basic sanity checking, such as ensuring that the ...