Missing Data

Just like pandas has built-in settings for handling missing data or NaN values, the .plot() method also has default settings for how each type of plot handles missing data.

Plot Type	NaN Handling
Line	Leaves gaps
Stacked line	Fills 0s
Bar	Fills 0s
Scatter	Drops missing values
Histogram	Drops missing values (column-wise)
Box	Drops missing values (column-wise)
Area	Fills 0s
Kernel density (KDE)	Drops missing values (column-wise)
Hexbin	Drops missing values
Pie	Fills 0s

To customize or alter these default settings, you would use .fillna() or .dropna() to filter the DataFrame before generating the plot.

Additional Resources

For more on plotting with pandas and matplotlib:

• pandas, Tutorials, “Plotting”

• pandas, “Plotting tools”

• pandas, “Plot formatting”

• pandas, “Plotting directly with matplotlib”