I'm trying to achieve the following o/p from bokeh which is deprecated now. In the new structure, I need to layer everything like working in HTML. Is there any simplified example like this bokeh pie chart(deprecated) ?
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I'm not aware of a single "combined" example but there is a basic Pie chart example here (https://docs.bokeh.org/en/latest/docs/examples/topics/pie/pie.html) and a Donut chart example here (https://docs.bokeh.org/en/latest/docs/examples/topics/pie/donut.html) so you would more or less just combine those two examples to get a chart like the one above. – bigreddot Jan 09 '23 at 20:09
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@bigreddot Thanks for the reply. I thought about that. But it's not an easy one like before. That's why I tried here. – ArulRulzz Jan 10 '23 at 02:02
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Well, the "easy on from before" was part of `bokeh.charts` which was barely functional and did not have a maintainer, so it had to be jettisoned from the main library. If you want to simplify things, it's probably possible to use `annular_wedge` with `inner_radius=0` for the inner wedges, so that all levels can be created consistently. There might be higher level tools (e.g. holoviews or pandas-bokeh) that offer a multi-level pie chart, but I'm not sure. – bigreddot Jan 10 '23 at 17:08
1 Answers
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You can combine wegde
and annular_wedge
The example code below creates this figure:
Example code
Pandas
Lets say we have this data table for the medals of a sport event.
import numpy as np
import pandas as pd
df = pd.DataFrame({
'Country':['Fra', 'Deu', 'Can', 'USA'],
'Gold': [0,1,2,3],
'Silver': [1,2,2,2],
'Bronze':[3,2,1,3]
})
>>> df
Country Gold Silver Bronze
0 FRA 0 1 3
1 GER 1 2 2
2 CAN 2 2 1
3 USA 3 2 3
Now we have to calculate the angles to use the bokeh wedges. We use a copy to not overwrite the original data.
# get a copy and calculate the angles
_df = df.copy()
_df['Country_total'] = _df[['Gold', 'Silver', 'Bronze']].sum(axis=1)
total_sum = _df['Country_total'].sum()
_df["End"] = _df['Country_total'].div(total_sum).mul(2 * np.pi).cumsum().round(6)
_df["Start"] = _df["End"].shift(1).fillna(0)
_df['Color'] = ['blue', 'red', 'green', 'magenta']
_df
Bokeh
Here we loop over all rows of the DataFrame and draw the annular wedge first and then the inner wedge to get the correct color in the legend.
from bokeh.models import Legend
from bokeh.plotting import show, figure, output_notebook
output_notebook()
p = figure(width=400, height=300, match_aspect=True, x_range=(-2.2,2.2), y_range=(-2.2,2.2))
p.add_layout(
Legend(
click_policy="hide",
margin=1,
),
"right",
)
p.rect(x=0, y=0, width=2, height=2, alpha=0)
wedges = []
for i, item in _df.iterrows():
start = item["Start"]
end = item["End"]
start_angle = start
end_angle = start
for value, color in zip(['Gold', 'Silver', 'Bronze'], ['gold', 'silver', '#bf8970']):
angle = np.round(item[value] / total_sum * 2 * np.pi, 6)
end_angle += angle
p.annular_wedge(
x=0,
y=0,
inner_radius=1,
outer_radius=2,
start_angle=start_angle,
end_angle=end_angle,
color=color,
line_color='white',
legend_label=item['Country'],
)
start_angle += angle
p.wedge(
x=0,
y=0,
radius=1,
start_angle=start,
end_angle=end,
color=item["Color"],
line_color='white',
legend_label=item['Country'],
)
p.xgrid.visible = False
p.ygrid.visible = False
show(p)
Comment
I hope this is close tou your wanted solution.

mosc9575
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thanks for your reply. I'm expecting something similar to the previous one. As I said earlier, Here we're doing everything like a designer. Instead, if we have a codebase like the previous one, it'll be easy to use. – ArulRulzz Jan 16 '23 at 02:49