matplotlib 3.5.1

Parameters
__init__(self, nbins=None, **kwargs)

Parameters

nbins : int or 'auto', default: 10

Maximum number of intervals; one less than max number of ticks. If the string 'auto', the number of bins will be automatically determined based on the length of the axis.

steps : array-like, optional

Sequence of nice numbers starting with 1 and ending with 10; e.g., [1, 2, 4, 5, 10], where the values are acceptable tick multiples. i.e. for the example, 20, 40, 60 would be an acceptable set of ticks, as would 0.4, 0.6, 0.8, because they are multiples of 2. However, 30, 60, 90 would not be allowed because 3 does not appear in the list of steps.

integer : bool, default: False

If True, ticks will take only integer values, provided at least min_n_ticks integers are found within the view limits.

symmetric : bool, default: False

If True, autoscaling will result in a range symmetric about zero.

prune : {'lower', 'upper', 'both', None}, default: None

Remove edge ticks -- useful for stacked or ganged plots where the upper tick of one axes overlaps with the lower tick of the axes above it, primarily when axes.autolimit_mode is 'round_numbers' . If prune=='lower' , the smallest tick will be removed. If prune == 'upper' , the largest tick will be removed. If prune == 'both' , the largest and smallest ticks will be removed. If prune is None, no ticks will be removed.

min_n_ticks : int, default: 2

Relax nbins and integer constraints if necessary to obtain this minimum number of ticks.

Examples

See :

Local connectivity graph

Hover to see nodes names; edges to Self not shown, Caped at 50 nodes.

Using a canvas is more power efficient and can get hundred of nodes ; but does not allow hyperlinks; , arrows or text (beyond on hover)

SVG is more flexible but power hungry; and does not scale well to 50 + nodes.

All aboves nodes referred to, (or are referred from) current nodes; Edges from Self to other have been omitted (or all nodes would be connected to the central node "self" which is not useful). Nodes are colored by the library they belong to, and scaled with the number of references pointing them


File: /matplotlib/ticker.py#1945
type: <class 'function'>
Commit: