- class plotnine.scales.scale_shape_manual(values, **kwargs)[source]¶
Custom discrete shape scale
- valuesarray_like |
Shapes that make up the palette. See
matplotlib.markers.for list of all possible shapes. The values will be matched with the
limitsof the scale or the
breaksif provided. If it is a dict then it should map data values to shapes.
- breaksarray_like or
Major break points. Alternatively, a callable that takes a tuple of limits and returns a list of breaks. Default is to automatically calculate the breaks.
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)
(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, 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 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.
str. Labels at the breaks. Alternatively, a callable that takes an array_like of break points as input and returns a list of strings.
Function to map data points onto the scale. Most scales define their own palettes.
str. Aesthetics covered by the scale. These are defined by each scale and the user should probably not change them. Have fun.
- limitsarray_like, optional
Limits of the scale. For scales that deal with categoricals, these may be a subset or superset of the categories. Data values that are not in the limits will be treated as missing data and represented with the
Whether to drop unused categories from the scale
Truetranslate missing values and show them. If
Falseremove missing values. Default value is
na_translate=True, what aesthetic value should be assigned to the missing values. This parameter does not apply to position scales where
nanis always placed on the right.
- valuesarray_like |