plotnine.scale_x_discrete
*args, **kwargs) scale_x_discrete(
Discrete x position
Parameters
breaks : bool  list  callable = True

List of major break points. Or a callable that takes a tuple of limits and returns a list of breaks. If
True
, automatically calculate the breaks. expand : tuple = None

Multiplicative and additive expansion constants that determine how the scale is expanded. If specified must be of length 2 or 4. Specifically the values are in this order:
(mul, add) (mul_low, add_low, mul_high, add_high)
For example,
(0, 0)
 Do not expand.(0, 1)
 Expand lower and upper limits by 1 unit.(1, 0)
 Expand lower and upper limits by 100%.(0, 0, 0, 0)
 Do not expand, as(0, 0)
.(0, 0, 0, 1)
 Expand upper limit by 1 unit.(0, 1, 0.1, 0)
 Expand lower limit by 1 unit and upper limit by 10%.(0, 0, 0.1, 2)
 Expand upper limit by 10% plus 2 units.
If not specified, suitable defaults are chosen.
name : str = None

Name used as the label of the scale. This is what shows up as the axis label or legend title. Suitable defaults are chosen depending on the type of scale.
labels : bool  list  callable = True

List of
str
. Labels at thebreaks
. Alternatively, a callable that takes an array_like of break points as input and returns a list of strings. palette : callable = None

Function to map data points onto the scale. Most scales define their own palettes.
aesthetics : list  str = None

list of
str
. Aesthetics covered by the scale. These are defined by each scale and the user should probably not change them. Have fun. drop : bool = True

Whether to drop unused categories from the scale
na_translate : bool = True

If
True
translate missing values and show them. IfFalse
remove missing values. Default value isTrue
na_value : object

If
na_translate=True
, what aesthetic value should be assigned to the missing values. This parameter does not apply to position scales wherenan
is always placed on the right. limits : array_like = None

Limits of the scale. For discrete scale, these are the categories (unique values) of the variable. For scales that deal with categoricals, these may be a subset or superset of the categories.