Plotly sunburst charts are great for visualizing hierarchical data. Is it possible to retrieve the values shown in the chart into a dictionary, or an array or something?
Concretely, assume the following dataframe:
Att1 Att2
A C
A D
B D
B D
B C
px.sunburst(data, ['Att1', 'Att2'])
will generate a chart that in the most inner ring has the value 2 for A
and 3 for B
. Then for A
, it will indicate there is 1 C
and 1 D
. Similarly, for B
it will indicate 2 D
and 1 C
. All those numbers are the ones I am looking to retrieve. Does plotly have such functionality? or is my best bet to use data.groupby
iteratively?
The underlying data from a figure can be accessed and the details can be found here at plotly and summarized below...
Viewing the underlying data structure for any plotly.graph_objects.Figure object, including those returned by Plotly Express, can be done via print(fig) or, in JupyterLab, with the special fig.show("json") renderer. Figures also support fig.to_dict() and fig.to_json() methods. print()ing the figure will result in the often-verbose layout.template key being represented as ellipses '...' for brevity.
Several options are available...
fig.show("json")
is pretty hany if you're in a notebookprint(fig)
is my go to methodSo for this plotly example:
import plotly.express as px
data = dict(
character=["Eve", "Cain", "Seth", "Enos", "Noam", "Abel", "Awan", "Enoch", "Azura"],
parent=["", "Eve", "Eve", "Seth", "Seth", "Eve", "Eve", "Awan", "Eve" ],
value=[10, 14, 12, 10, 2, 6, 6, 4, 4])
fig = px.sunburst(
data,
names='character',
parents='parent',
# values='value',
)
fig.show()
print(fig)
will return:
Figure({
'data': [{'domain': {'x': [0.0, 1.0], 'y': [0.0, 1.0]},
'hovertemplate': 'character=%{label}<br>parent=%{parent}<extra></extra>',
'labels': array(['Eve', 'Cain', 'Seth', 'Enos', 'Noam', 'Abel', 'Awan', 'Enoch', 'Azura'],
dtype=object),
'name': '',
'parents': array(['', 'Eve', 'Eve', 'Seth', 'Seth', 'Eve', 'Eve', 'Awan', 'Eve'],
dtype=object),
'type': 'sunburst'}],
'layout': {'legend': {'tracegroupgap': 0}, 'margin': {'t': 60}, 'template': '...'}
})
And then with some knowledge of tuples you can extract some info, for example...
print(fig.data[0].labels)
will return:
['Eve' 'Cain' 'Seth' 'Enos' 'Noam' 'Abel' 'Awan' 'Enoch' 'Azura']