Mastering pandas - Second Edition

Data collection

This entails the data points that are not available or are difficult to collect. Suppose you are surveying 100,000 people for the type of electric car they own. In this case, if we encounter someone who doesn't own an electric car, we would have a missing value for that person's car type.

Missing values originating because of data extraction, in theory, can be rectified if we are able to identify the issue that led to the missing value and rerun the extraction process. Missing values originating from data collection issues are difficult to rectify.

How do you know your data has missing values? The easiest way to find this out is to run a summary of the dataset, which gives a count of rows as well. Since the rows containing ...