manual_key Option¶In Lets-Plot, as in ggplot2, legends are automatically generated based on the aesthetic mappings in the plot.
Sometimes, however, this automatic generation doesn't provide the precise control needed for complex visualizations.
The manual_key option allows you to create custom legend entries specific to individual plot layers.
The manual_key option can be used in two ways:
Simple case: pass a string to serve as the label for the legend entry.
Advanced case: use the layer_key() function for more detailed customization:
label - text for the legend elementgroup - key used to group elements in the legendindex - position of the element within its legend groupkwargs - dictionary of aesthetic parameters to be applied in the legendimport pandas as pd
from lets_plot import *
LetsPlot.setup_html()
df = pd.read_csv("https://raw.githubusercontent.com/JetBrains/lets-plot-docs/master/data/mpg.csv")
print(df.shape)
df.head(3)
(234, 12)
| Unnamed: 0 | manufacturer | model | displ | year | cyl | trans | drv | cty | hwy | fl | class | |
|---|---|---|---|---|---|---|---|---|---|---|---|---|
| 0 | 1 | audi | a4 | 1.8 | 1999 | 4 | auto(l5) | f | 18 | 29 | p | compact |
| 1 | 2 | audi | a4 | 1.8 | 1999 | 4 | manual(m5) | f | 21 | 29 | p | compact |
| 2 | 3 | audi | a4 | 2.0 | 2008 | 4 | manual(m6) | f | 20 | 31 | p | compact |
# Default plot
ggplot(df, aes("displ", "hwy")) + \
geom_point(color="#878787") + \
geom_smooth(method='loess', se=False, color="#2166ac") + \
geom_smooth(method='lm', se=False, color="#b2182b")
ggplot(df, aes("displ", "hwy")) + \
geom_point(color="#878787",
manual_key="Observed Data" # label for the legend entry
) + \
geom_smooth(method='loess', se=False, color="#2166ac",
manual_key="LOESS Trend Line") + \
geom_smooth(method='lm', se=False, color="#b2182b",
manual_key="Linear Model Trend Line") + \
ggsize(800, 400)
layer_key() Function¶All constants for the visual representation of the legend key are inherited from the geometry. Use the layer_key() function to override these values. You can also specify the legend group in which the element is displayed and the position of the element within the legend group.
p = ggplot(df, aes("displ", "hwy")) + \
geom_point(color="#878787",
manual_key=layer_key("Observed Data", # <-- label for the legend entry
color='pen', size=8) # <-- override aesthetics
) + \
geom_smooth(method='loess', se=False, color="#2166ac",
manual_key=layer_key("LOESS",
group="Methods", # <-- assign a group (note the same group in the layer below)
index=1, # <-- position of the element
size=4)) + \
geom_smooth(method='lm', se=False, color="#b2182b",
manual_key=layer_key("LM", group="Methods", index=0, size=4)) + \
ggsize(800, 400)
p
p + labs(
manual="Scatter Plot", # <-- "manual" is a default 'key' referring to a custom legend
Methods="Trend Lines" # <-- "Methods" is the group name referring to the second custom legend
)
ggplot(mapping=aes(as_discrete('class', order_by='..y..'), 'hwy')) + \
stat_summary(data=df[df.year == 1999], fun='mean', # <-- 1999
geom='line', size=2, color='#D87093',
manual_key="1999" # <-- label for the legend entry
) + \
stat_summary(data=df[df.year == 1999], fun='mean',
geom='point', size=5, shape=22,
fill='#D87093', color='paper',
manual_key=layer_key("1999", # <-- Using the same label as above results in a composite entry in the legend
size=3)) + \
stat_summary(data=df[df.year == 2008], fun='mean', # <-- 2008
geom='line', size=2, color='#708090',
manual_key="2008") + \
stat_summary(data=df[df.year == 2008], fun='mean',
geom='point', size=7, shape=23, fill='#708090', color='paper',
manual_key=layer_key("2008", size=5)) + \
guides(manual=guide_legend(
override_aes=dict(stroke=0, # <-- remove `stroke` in the "manual" legend
size=1) # <-- update `size` if not specified otherwise in the layer itself
)) + \
ggsize(800, 400) + \
theme(legend_position=[0.9, 0.95], legend_justification=[1, 1],
legend_direction='horizontal',
legend_background=element_rect(size=1, linetype='dotted'))