Fillna
fillna is a pandas method that replaces missing values in a Series or DataFrame with specified or computed values.
Pandas Workout: 200 exercises to make you a stronger data analyst
A pandas method that replaces missing values with a specified value or computed replacement.
- How it is used
- Replaces missing Series or DataFrame values with literal or computed alternatives during data cleaning and transformation.
- How deep it goes
- Explains literal, mean, and mode replacements, returned objects, reassignment, and the tradeoff between filling and dropping values.
- Examples
- Demonstrates filling missing tens digits with zero and imputing Titanic ages with a mean and destinations with a mode.
- What you can do after
- Apply it via pandas to replace missing values with literals or statistics and preserve the result through reassignment.
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Grokking Machine Learning
fillna is a Pandas operation that replaces missing entries with a specified value or computed replacement.
- How it is used
- Preserves useful dataset columns by replacing missing entries during data cleaning.
- How deep it goes
- Demonstrates median and category replacements with executable column assignments, but does not detail fillna options.
- Examples
- Uses Titanic Age values filled with median 28 and Embarked values filled with the category U.
- What you can do after
- Apply it via Pandas to replace numeric or categorical missing values in a cleaned DataFrame.
Related concepts
- nanuses · A special floating-point value representing an undefined, invalid, or unrepresentable numerical result.
- pandasuses · pandas is an open-source Python library that provides labeled data structures and tools for manipulating and analyzing tabular and other structured data.
- missing valueaddresses · A missing value is a marker or condition indicating that an expected data value or reference is absent, unavailable, unknown, or inapplicable.
- medianuses · The median is the middle value of an ordered set of observations, or the mean of the two middle values when the set has an even number of observations.
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