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 above was generated using a synthetic dataset of patient enrolment at clinical sites filtered by country. Click the image to view the full interactive and fully annotated Plotly Go figure.

The synthetic dataset used for this plot is given as a table (which can easily be converted to a CSV).

Synthetic dataset for patient enrolment at clinical sites filtered by country

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 above using the fig_sunburst() function:

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 by Site",
    path=["Country", "Site"],
    values="SubjectID",
    height=600
)
fig.show()

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.

Also, the height parameter, which is optional with a default of 430, can be used to customise the plot height. Refer to the fig_sunburst() function docstring for more information.