import math
import random
import numpy as np
import pandas as pd
from lets_plot import *
from lets_plot.geo_data import *
LetsPlot.setup_html()
The geodata is provided by © OpenStreetMap contributors and is made available here under the Open Database License (ODbL).
LetsPlot.set_theme(theme(plot_background=element_rect(size=3)))
def dump_plot(plot, display=None):
import json
try:
import clipboard
except:
clipboard = None
from lets_plot._type_utils import standardize_dict
plot_dict = standardize_dict(plot.as_dict())
plot_json = json.dumps(plot_dict, indent=2)
if clipboard:
clipboard.copy('')
clipboard.copy(str(plot_json))
else:
if display is None:
display = True
if display:
print(plot_json)
return plot
n = 450
x_range = np.arange(-2 * math.pi, 2 * math.pi, 4 * math.pi / n)
y_range = np.sin(x_range) + np.array([random.uniform(-.5, .5) for i in range(n)])
df = pd.DataFrame({ 'x' : x_range, 'y' : y_range })
ggplot(df, aes(x='x', y='y')) \
+ geom_point(shape=21, fill='yellow', color='#8c564b') \
+ geom_smooth(method='loess', span=.2, size=1.5, color='#9467bd')
import numpy as np
from lets_plot import *
LetsPlot.setup_html()
n = 500
np.random.seed(42)
x = np.random.uniform(-1, 1, size=n)
y = np.random.uniform(size=n)
dump_plot(
ggplot({'x': x, 'y': y}, aes(x='x', y='y')) + \
geom_point() + coord_fixed()
)
{
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},
"mapping": {
"x": "x",
"y": "y"
},
"data_meta": {},
"theme": {
"plot_background": {
"size": 3.0,
"blank": false
}
},
"coord": {
"name": "fixed",
"ratio": 1.0,
"flip": false
},
"kind": "plot",
"scales": [],
"layers": [
{
"geom": "point",
"mapping": {},
"data_meta": {}
}
],
"metainfo_list": []
}
world = geocode_countries().get_boundaries()
north_america = geocode_countries(['usa', 'canada', 'mexico']).get_boundaries()
australia = geocode_countries('australia').get_boundaries(3)
world_map = ggplot() \
+ geom_map(aes(fill='country'), map=world, size=0.1, show_legend=False, tooltips=layer_tooltips().line("@country"))
north_america_map = ggplot() \
+ geom_map(aes(fill='country'), map=north_america, size=0.1, show_legend=False,
tooltips=layer_tooltips().line("@country")) \
+ coord_map(xlim=[-180, -50])
australia_map = ggplot() \
+ geom_map(aes(fill='country'), map=australia, size=0.1, show_legend=False,
tooltips=layer_tooltips().line("@country")) \
+ coord_map(xlim=[110, None], ylim=[-45, None])
ggplot() + geom_map(aes(fill='country'), map=world, size=0.1, show_legend=False) + coord_map() + ggsize(1000, 800)
np.random.seed(42)
x = np.random.poisson(size=100)
ggplot({'x': x}, aes(x='x')) + geom_histogram() + scale_y_log2()
mpg_df = pd.read_csv('https://raw.githubusercontent.com/JetBrains/lets-plot-docs/master/data/mpg.csv')
annotation = (layer_labels()
# .line('@drv')
.line('@..count..')
.line('@..proppct..')
.format('..proppct..', '{d}%'))
ggplot(mpg_df, aes('class', fill='drv')) \
+ geom_bar(labels=annotation, tooltips='none') \
+ theme(legend_position='none')
Shared axis doesn't work with panning
plot_data = pd.DataFrame.from_records([
("pet", "cat", 5),
("pet", "dog", 10),
("pet", "rabbit", 2),
("pet", "hamster", 1),
("farm_animal", "cow", 500),
("farm_animal", "pig", 100),
("farm_animal", "horse", 700),
])
plot_data.columns = ("animal_type", "animal", "weight")
plot = (
ggplot(plot_data, aes(x="animal", y="weight"))
+ facet_grid(y="animal_type", scales="free_y")
+ geom_bar(stat="identity", size=0.5, color="black")
+ theme_bw()
+ theme(
panel_grid_minor=element_blank()
)
)
plot + ggtitle('Panning renders the ticks useless')
gggrid([
world_map,
gggrid([
north_america_map,
australia_map
])
], ncol=1)
bunch = GGBunch()
bunch.add_plot(world_map, 0, 0, 800, 400)
bunch.add_plot(north_america_map, 0, 400, 400, 300)
bunch.add_plot(australia_map, 400, 400, 300, 300)
bunch.show()
Not yet supported
np.random.seed(0)
cov0=[[1, -.8],
[-.8, 1]]
cov1=[[ 10, .1],
[.1, .1]]
x0, y0 = np.random.multivariate_normal(mean=[-2,0], cov=cov0, size=200).T
x1, y1 = np.random.multivariate_normal(mean=[0,1], cov=cov1, size=200).T
data = dict(
x = np.concatenate((x0,x1)),
y = np.concatenate((y0,y1)),
c = ["A"]*200 + ["B"]*200
)
p = ggplot(data, aes("x", "y", color="c", fill="c")) + geom_point()
p + ggmarginal("tr", layer=geom_density(alpha=0.3, show_legend=False))
x1 = [0, 0, 40, 40, 0]
y1 = [0, 40, 40, 0, 0]
g1 = ['a'] * len(x1)
x2 = [it + 60 for it in x1]
y2 = y1
g2 = ['b'] * len(x2)
poly = {
'x': x1 + x2,
'y': y1 + y2,
'g': g1 + g2,
}
ggplot() \
+ geom_livemap() \
+ geom_polygon(aes(x='x', y='y', fill='g'), data=poly, tooltips=layer_tooltips().line("^fill"))
ggplot() + geom_livemap() + geom_polygon(aes(fill='country'), size=0, map=world, show_legend=False)
gggrid([
ggplot() + geom_livemap() + geom_polygon(aes(fill='country'), size=0, map=world, show_legend=False, tooltips=layer_tooltips().line("^fill")),
ggplot() + geom_livemap() + geom_polygon(aes(fill='country'), size=0, map=north_america, show_legend=False, tooltips=layer_tooltips().line("^fill")),
])
np.random.seed(0)
cov0=[[1, -.8],
[-.8, 1]]
cov1=[[ 10, .1],
[.1, .1]]
n = 4000
x0, y0 = np.random.multivariate_normal(mean=[-2,0], cov=cov0, size=n).T
x1, y1 = np.random.multivariate_normal(mean=[0,1], cov=cov1, size=n).T
data = dict(
x = np.concatenate((x0,x1)),
y = np.concatenate((y0,y1)),
c = ["A"]*n + ["B"]*n
)
p = ggplot(data, aes("x", "y", color="c", fill="c")) + geom_point()
#p + ggmarginal("tr", layer=geom_density(alpha=0.3, show_legend=False))
dump_plot(p)
def plot(n):
n = int(n / 2)
np.random.seed(0)
cov0=[[1, -.8],
[-.8, 1]]
cov1=[[ 10, .1],
[.1, .1]]
x0, y0 = np.random.multivariate_normal(mean=[-2,0], cov=cov0, size=n).T
x1, y1 = np.random.multivariate_normal(mean=[0,1], cov=cov1, size=n).T
data = dict(
x = np.concatenate((x0,x1)),
y = np.concatenate((y0,y1)),
c = ["A"]*n + ["B"]*n
)
return ggplot(data, aes("x", "y", color="c", fill="c")) + geom_point() + ggtitle('n=' + str(n * 2))
plot(2000)
{
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},
"mapping": {
"x": "x",
"y": "y",
"color": "c",
"fill": "c"
},
"data_meta": {},
"theme": {
"plot_background": {
"size": 3.0,
"blank": false
}
},
"kind": "plot",
"scales": [],
"layers": [
{
"geom": "point",
"mapping": {},
"data_meta": {}
}
],
"metainfo_list": []
}
plot(100)
plot(1000)
plot(10_000)
x1 = [0, 0, 40, 40, 0]
y1 = [0, 40, 40, 0, 0]
g1 = ['a'] * len(x1)
x2 = [60, 80, 100, 60]
y2 = [0, 40, 0, 0]
g2 = ['b'] * len(x2)
x3 = [-120, -100, -80, -100, -120]
y3 = [ 20, 40, 20, 0, 20]
g3 = ['c'] * len(x3)
poly = {
'x': x1 + x2,
'y': y1 + y2,
'g': g1 + g2,
}
p12 = ggplot() \
+ geom_polygon(
aes(
x=x1 + x2,
y=y1 + y2,
fill=g1 + g2
),
tooltips=layer_tooltips().line("^fill")
) \
+ coord_fixed()
p23 = ggplot() \
+ geom_polygon(
aes(x=x2 + x3, y=y2 + y3, fill=g2 + g3),
tooltips=layer_tooltips().line("^fill")
) \
+ coord_fixed()
p13 = ggplot() \
+ geom_polygon(
aes(x=x1 + x3, y=y1 + y3, fill=g1 + g3),
tooltips=layer_tooltips().line("^fill")
) \
+ coord_fixed()
# livemap
lp12 = ggplot() \
+ geom_livemap() \
+ geom_polygon(
aes(x=x1 + x2, y=y1 + y2, fill=g1 + g2),
tooltips=layer_tooltips().line("^fill")
)
lp23 = ggplot() \
+ geom_livemap() \
+ geom_polygon(
aes(x=x2 + x3, y=y2 + y3, fill=g2 + g3),
tooltips=layer_tooltips().line("^fill")
)
lp13 = ggplot() \
+ geom_livemap() \
+ geom_polygon(
aes(x=x1 + x3, y=y1 + y3, fill=g1 + g3),
tooltips=layer_tooltips().line("^fill")
)
p12
p23
gggrid([
p12,
gggrid([
p23, p13
])
], ncol=1)
gggrid([
lp12,
gggrid([
lp23, lp13
])
], ncol=1)
bunch = GGBunch()
bunch.add_plot(p12, 0, 0, 600, 400)
bunch.add_plot(p23, 600, 400, 600, 400)
bunch.show()
livemap_bunch = GGBunch()
livemap_bunch.add_plot(lp12, 0, 0, 600, 400)
livemap_bunch.add_plot(lp23, 600, 400, 600, 400)
livemap_bunch.show()
p12 + facet_wrap('fill', ncol=2, nrow=1)
lp12 + facet_wrap('fill', ncol=2, nrow=1)
lp12 + ggtitle("Multi\nline\ntitle")