matplotlib.pyplot.title#

matplotlib.pyplot.title(label, fontdict=None, loc=None, pad=None, *, y=None, **kwargs)[source]#

Set a title for the Axes.

Set one of the three available Axes titles. The available titles are positioned above the Axes in the center, flush with the left edge, and flush with the right edge.

Parameters:

labelstr

Text to use for the title

fontdictdict

Discouraged

The use of fontdict is discouraged. Parameters should be passed as individual keyword arguments or using dictionary-unpacking set_title(..., **fontdict).

A dictionary controlling the appearance of the title text, the default fontdict is:

{'fontsize': rcParams['axes.titlesize'],
 'fontweight': rcParams['axes.titleweight'],
 'color': rcParams['axes.titlecolor'],
 'verticalalignment': 'baseline',
 'horizontalalignment': loc}

loc{'center', 'left', 'right'}, default: rcParams["axes.titlelocation"] (default: 'center')

Which title to set.

yfloat, default: rcParams["axes.titley"] (default: None)

Vertical Axes location for the title (1.0 is the top). If None (the default) and rcParams["axes.titley"] (default: None) is also None, y is determined automatically to avoid decorators on the Axes.

padfloat, default: rcParams["axes.titlepad"] (default: 6.0)

The offset of the title from the top of the Axes, in points.

Returns:

Text: The matplotlib text instance representing the title

Other Parameters:

**kwargsText properties: Other keyword arguments are text properties, see Text for a list of valid text properties.

Notes

Note

This is the pyplot wrapper for axes.Axes.set_title.

Examples using `matplotlib.pyplot.title`#

Interactive functions

Plotting masked and NaN values

Set and get properties

Table Demo

Zorder Demo

Rotating a 3D plot

Text and mathtext using pyplot

Custom scale

The Sankey class

Solarized Light stylesheet

Style sheets reference

Geographic Projections

Multiple subplots

Controlling style of text and labels using a dictionary

matplotlib.pyplot.title#

Examples using matplotlib.pyplot.title#

Examples using `matplotlib.pyplot.title`#