Handling Missing Data in a Java Data Analysis Application

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I'm working on a Java application for data analysis, and I'm encountering issues with missing data in my dataset. What are the best practices for handling missing data effectively in a Java-based data analysis project? Here's a simplified example of what I'm trying to do. Let's say I have a CSV file containing data, and I'm using the java.util.Scanner class to read it:
Java: 
import java.io.File;
import java.io.FileNotFoundException;
import java.util.Scanner;

public class DataAnalysisApp {
    public static void main(String[] args) {
        try {
            File dataFile = new File("data.csv");
            Scanner scanner = new Scanner(dataFile);

            while (scanner.hasNextLine()) {
                String line = scanner.nextLine();
                // Parse and analyze the data
                // ...
            }
            scanner.close();
        } catch (FileNotFoundException e) {
            e.printStackTrace();
        }
    }
}

How can I handle incomplete or missing data elements in the CSV file in this code effectively? Should I omit these entries, put placeholders in their place, or try another tactic? I attempted this and looked through multiple articles like this one from Scaler on data analysis and Java but was unable to locate the answer. So, could you help let me know what the best Java practices are for handling missing data in a data analysis context?
 
It will depend on what is the type of data being read, or the domain?

I mean if you are doing some sort of aggregate then you can ignore missing or incomplete lines.

If you are focusing on or select specific data then even a single missing or incomplete line should fail the program by throwing an exception.

Can you tell what is the actual domain or type of data being scanned?
 
If you are building a generic library, then I would recommend using defaults for missing data and document the behaviour. Like 0 for numerical, false for boolean, empty string (wouldn’t recommend null here).

And if you want to externalise the decision on how to handle missing data, create an enum called MissingDataBehaviour with values FILL_DEFAULT, IGNORE_ROW. Add this enum as a parameter to your function with default parameter value as FILL_DEFAULT.

And the user can pass IGNORE_ROW if they want to ignore entire row in case of any missing data.
 
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