Handling Missing Data

In a DataFrame, missing values are typically represented by \texttt{NaN}, which stands for "Not a Number." It is used in pandas to denote missing or undefined values. While \texttt{NULL} might be used in databases, and \texttt{0} and \texttt{-1} are numeric values, \texttt{NaN} is the standard representation for missing values in pandas DataFrames. Therefore, the correct answer is \texttt{NaN}.