How can I handle missing data in my dataset?

How can I handle missing data in my dataset?

There are several techniques for handling missing data, such as imputation, deletion, or using algorithms that support missing values. What type of data are you working with?

I'm working with a dataset containing customer information, and some entries have missing age values.

For missing age values, you could use mean or median imputation, or even predict the missing values using a regression model based on other features. Have you considered any of these methods?

I haven't thought about regression. How would I implement that?

You can create a regression model using the available features to predict age. Split your data into training and testing sets, train the model on the training set, and then use it to fill in the missing age values in the test set.

That sounds great! Are there any libraries you recommend for this?

Yes, libraries like scikit-learn in Python are excellent for building regression models. You can also use pandas for data manipulation and handling missing values.