from plotnine import (
ggplot,
aes,
theme_matplotlib,
theme_set,
geom_tile,
scale_fill_continuous,
coord_cartesian
)
from plotnine.data import faithfuld
# Set default theme for all the plots
theme_set(theme_matplotlib())
scale_fill_continuous(
cmap_name="viridis",
*,
name=None,
breaks=True,
limits=None,
labels=True,
expand=None,
guide="colorbar",
na_value="#7F7F7F",
aesthetics=(),
rescaler=rescale,
oob=censor,
minor_breaks=True,
trans=None
)alias of scale_fill_cmap
Init Parameters
Parameter Attributes
name: str | None = None-
The name of the scale. It is used as the label of the axis or the title of the guide. Suitable defaults are chosen depending on the type of scale.
breaks: ContinuousBreaksUser = True-
Major breaks
limits: ContinuousLimitsUser = None-
Limits of the scale. Most commonly, these are the minimum & maximum values for the scale. If not specified they are derived from the data. It may also be a function that takes the derived limits and transforms them into the final limits.
labels: ScaleLabelsUser = True-
Labels at the
breaks. Alternatively, a callable that takes an array_like of break points as input and returns a list of strings. expand: (
tuple[float, float]
| tuple[float, float, float, float]
| None
) = 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.
guide: Literal["legend", "colorbar"] | None = "colorbar"na_value: str = "#7F7F7F"-
Color of missing values.
aesthetics: Sequence[ScaledAestheticsName] = ()-
Aesthetics affected by this scale. These are defined by each scale and the user should probably not change them. Have fun.
rescaler: PRescale = rescale-
Function to rescale data points so that they can be handled by the palette. Default is to rescale them onto the [0, 1] range. Scales that inherit from this class may have another default.
oob: PCensor = censor-
Function to deal with out of bounds (limits) data points. Default is to turn them into
np.nan, which then get dropped. minor_breaks: MinorBreaksUser = True-
If a list-like, it is the minor breaks points. If an integer, it is the number of minor breaks between any set of major breaks. If a function, it should have the signature
func(limits)and return a list-like of consisting of the minor break points. IfNone, no minor breaks are calculated. The default is to automatically calculate them. trans: TransUser = None-
The transformation of the scale. Either name of a trans function or a trans function. See
mizani.transformsfor possible options.
Examples
Simple heatmap
Map data to color gradient
Without specifically calling scale_fill_continuous(), a default scale is applied to geom_tile().
faithfuld.head()| eruptions | waiting | density | |
|---|---|---|---|
| 0 | 1.600000 | 43.0 | 0.003216 |
| 1 | 1.647297 | 43.0 | 0.003835 |
| 2 | 1.694595 | 43.0 | 0.004436 |
| 3 | 1.741892 | 43.0 | 0.004978 |
| 4 | 1.789189 | 43.0 | 0.005424 |
(
ggplot(faithfuld, aes("waiting", "eruptions", fill="density"))
+ geom_tile()
)
Notice that adding scale_fill_continuous() will not change the default plot.
(
ggplot(faithfuld, aes("waiting", "eruptions", fill="density"))
+ geom_tile()
+ scale_fill_continuous()
)
The scale aesthetics can be edited to other color maps. Use the cmap_name argument to specify an alternative palette. Find other available color maps in the matplotlib documentation.
# Gallery, tiles
(
ggplot(faithfuld, aes("waiting", "eruptions", fill="density"))
+ geom_tile()
+ scale_fill_continuous(cmap_name="plasma")
+ coord_cartesian(expand=False)
)