Filling Missing Values

Replace missing values with meaningful data using fillna() and other methods.

Fill with a Constant

Replace all NaN with a single value:

Fill with Column-Specific Values

Use a dictionary for different fill values:

Fill with Statistics

Use mean, median, or mode:

Forward and Backward Fill

Propagate previous or next values:

Interpolation

Fill based on surrounding values:

Limiting Fill

Limit how many consecutive NaN to fill:

Exercise: Fill with Mean

Exercise: Forward Fill

Key Points

• fillna(value) replaces NaN with constant
• Use dict for column-specific fill values
• Fill with statistics: fillna(df['col'].mean())
• ffill() propagates last valid value forward
• bfill() propagates next valid value backward
• interpolate() fills based on surrounding values
• limit= restricts consecutive fills