Theme Flavors

from IPython.display import Image
import pandas as pd

from lets_plot import *

LetsPlot.setup_html()

mpg_df = pd.read_csv("https://raw.githubusercontent.com/JetBrains/lets-plot-docs/master/data/mpg.csv")
mpg_df

	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
3	4	audi	a4	2.0	2008	4	auto(av)	f	21	30	p	compact
4	5	audi	a4	2.8	1999	6	auto(l5)	f	16	26	p	compact
...	...	...	...	...	...	...	...	...	...	...	...	...
229	230	volkswagen	passat	2.0	2008	4	auto(s6)	f	19	28	p	midsize
230	231	volkswagen	passat	2.0	2008	4	manual(m6)	f	21	29	p	midsize
231	232	volkswagen	passat	2.8	1999	6	auto(l5)	f	16	26	p	midsize
232	233	volkswagen	passat	2.8	1999	6	manual(m5)	f	18	26	p	midsize
233	234	volkswagen	passat	3.6	2008	6	auto(s6)	f	17	26	p	midsize

234 rows × 12 columns

Flavors Demonstration

p = ggplot(mpg_df, aes("cty","hwy", color='drv')) + \
    geom_point(tooltips=layer_tooltips().line('@manufacturer @model'))

p2 = p + facet_grid(y="drv")

def theme_with_flavor(plot, theme, title):
    return gggrid([
        plot + theme + ggtitle(title),
        plot + theme + flavor_darcula()+ ggtitle("darcula"),
        plot + theme + flavor_solarized_light()+ ggtitle("solarized_light"),
        plot + theme + flavor_solarized_dark()+ ggtitle("solarized_dark"),
        plot + theme + flavor_high_contrast_light() + ggtitle("high_contrast_light"),
        plot + theme + flavor_high_contrast_dark() + ggtitle("high_contrast_dark"),
    ], ncol=2) + ggsize(800, 800)

theme_with_flavor(p, theme_minimal2(), "minimal2")

theme_with_flavor(p2, theme_minimal2(), "minimal2 + facet_grid")

theme_with_flavor(p, theme_minimal(), "minimal")

theme_with_flavor(p2, theme_minimal(), "minimal + facet_grid")

theme_with_flavor(p, theme_classic(), "classic")

theme_with_flavor(p2, theme_classic(), "classic + facet_grid")

theme_with_flavor(p, theme_light(), "light")

theme_with_flavor(p2, theme_light(), "light + facet_grid")

theme_with_flavor(p, theme_grey(), "grey")

theme_with_flavor(p2, theme_grey(), "grey + facet_grid")

theme_with_flavor(p, theme_void(), "void")

theme_with_flavor(p2, theme_void(), "void + facet_grid")

theme_with_flavor(p, theme_none(), "none")

theme_with_flavor(p2, theme_none(), "none + facet_grid")

theme_with_flavor(p, theme_bw(), "bw")

theme_with_flavor(p2, theme_bw(), "bw + facet_grid")

Returning to the Theme Defaults with flavor_standard()

Use flavor_standard() to override other flavors or to make defaults explicit.

# A reusable style layer for consistent plots across the project.

proj_theme = (
    theme_classic() +
    theme(
        axis_title=element_text(size=13),
        axis_text=element_text(size=15),
        legend_position="left",
        axis_ticks_length=7,
        panel_grid_major=element_line(color="spring_green"),
        panel_grid_minor=element_blank()
    ) + flavor_darcula()
)

LetsPlot.set_theme(proj_theme)

# A base plot with the common project style

proj_plot = ggplot(mpg_df, aes("cty","hwy", color='drv')) + \
    geom_point(tooltips=layer_tooltips().line('@manufacturer @model')) + \
    ggtitle("Fuel Economy: City and Highway Mileage by Drive Type")
proj_plot

# To restore the theme defaults without affecting other settings, apply flavor_standard(). 
# This can be useful, for example, when exporting the plot for printing.

fullpath_png = ggsave(proj_plot + flavor_standard(), "plot_without_flavor.png", scale=1)

Image(filename=fullpath_png)