Note
Go to the end to download the full example code.
Sunburst Plots¶
Sunburst plots, also known as ring charts, can be generated using the fig_sunburst() function, which returns a Plotly Go Figure object.
The plot below was generated using a synthetic dataset of patient enrolment data organised by site and country.
The synthetic dataset is given as a table (which can easily be converted to a CSV).
Site |
Country |
Subject Id |
|---|---|---|
0 |
COL |
21 |
2 |
COL |
25 |
3 |
GBR |
199 |
5 |
CAN |
31 |
6 |
BRA |
156 |
7 |
BRA |
27 |
8 |
BRA |
8 |
9 |
FRA |
174 |
10 |
POL |
89 |
11 |
POL |
30 |
13 |
RWA |
121 |
14 |
KEN |
1 |
15 |
KEN |
15 |
16 |
KEN |
1 |
18 |
NLD |
102 |
The data source can be in any appropriate form, such as, typically, a CSV. Here are the Python steps you need to generate the plot using the fig_sunburst() function:
import io
import pandas as pd
from isaricanalytics.visualisation import fig_sunburst
# Load the CSV data from a string buffer
data = pd.read_csv(
io.StringIO(
"""Site,Country,SubjectID\n
0,COL,21\n2,COL,25\n
3,GBR,199\n
5,CAN,31\n
6,BRA,156\n
7,BRA,27\n
8,BRA,8\n
9,FRA,174\n
10,POL,89\n
11,POL,30\n
13,RWA,121\n
14,KEN,1\n
15,KEN,15\n
16,KEN,1\n
18,NLD,102\n""",
),
skipinitialspace=True,
)
# Create and display the figure
fig = fig_sunburst(
data,
title="Sunburst Plot of Synthetic Patient Enrolment Data Organised by Site and Country",
path=["Country", "Site"],
values="SubjectID",
)
fig.update_layout(autosize=True)
fig
You should see the plot appearing as given above.
Note
Any dataframe or CSV column names, or dictionary field labels, in the example above that are not specific to the dataset must be as given, otherwise the function may throw an exception or return an incorrect figure.
The figure height and width parameters can be set using the height
and width parameters, but it may be more convenient to let Plotly handle
this using the figure layout autosize
parameter. Refer to the fig_sunburst()
function docstring for more information.
Total running time of the script: (0 minutes 2.235 seconds)