AI engineering glossary · NumPy pandas visualization
What is missing data?
Missing data (also called null values, isna): Values that are absent from a dataset, shown in pandas as NaN, None or NaT. Pandas methods such as isna, fillna and dropna detect and handle them, and most summaries skip them by default. How they are handled directly affects the results of any analysis.
Missing data: an example
df.isna().sum() counts blank cells per column, for example 12 missing phone numbers out of 500 customers.
Related terms
More NumPy pandas visualization terms
Where you learn it
Missing data is part of the AI Engineering Program, which teaches it with notes, a hands-on lab and an exam. The first lesson is free.