fillna

fillna is a method commonly found in data manipulation libraries, particularly in Python's pandas library, used to fill missing values in a dataset. Missing values, often represented as NaN (Not a Number) or None, can cause problems in data analysis and machine learning models. The fillna method provides a straightforward way to handle these missing entries.

When using fillna, users can specify how to replace the missing values. Common strategies include filling with a specific scalar value, such as 0 or a mean value calculated from the existing data. Another option is to fill using the previous valid observation (forward fill) or the next valid observation (backward fill). This method can be applied to entire DataFrames or Series, or selectively to specific columns. The choice of fill strategy depends heavily on the nature of the data and the goals of the analysis. Proper handling of missing data using methods like fillna is a crucial step in data preprocessing.