TidyTuesday dataset of 2025-08-12

import pandas as pd
import plotly.express as px
import plotly.subplots as sp
import textwrap

attribution_studies = pd.read_csv('https://raw.githubusercontent.com/rfordatascience/tidytuesday/main/data/2025/2025-08-12/attribution_studies.csv')
attribution_studies_raw = pd.read_csv('https://raw.githubusercontent.com/rfordatascience/tidytuesday/main/data/2025/2025-08-12/attribution_studies_raw.csv')

attribution_studies

	event_name	event_period	event_year	study_focus	iso_country_code	cb_region	event_type	classification	summary_statement	publication_year	citation	source	rapid_study	link
0	European summer heatwave	2003	2003	Event	NaN	Europe	Heat	More severe or more likely to occur	"We estimate it is very likely (confidence lev...	2004.0	Stott, P. et al., 2004: Human contribution to ...	Nature	No	https://www.nature.com/nature/journal/v432/n70...
1	Global temperature extremes	since 1950	NaN	Trend	NaN	Global	Heat	More severe or more likely to occur	"Comparing these observations with climate mod...	2005.0	Christidis, N. et al., 2005: Detection of chan...	Geophysical Research Letters	No	https://agupubs.onlinelibrary.wiley.com/doi/fu...
2	Record warm autumn in Europe	2006	2006	Event	NaN	Europe	Heat	More severe or more likely to occur	"Global warming has made a warm autumn like th...	2007.0	Van Oldenborgh, G-J. et al., 2007: How unusual...	Climate of the Past	No	http://www.clim-past.net/3/659/2007/cp-3-659-2...
3	Increasing frequency of 'very warm' Northern h...	1860-2009	NaN	Trend	NaN	Northern hemisphere	Heat	More severe or more likely to occur	"We detect the dominant influence of anthropog...	2007.0	Jones, G. et al., 2007: Human contribution to ...	Journal of Geophysical Research: Atmospheres	No	https://agupubs.onlinelibrary.wiley.com/doi/fu...
4	Moscow summer heatwave	2010	2010	Event	RUS	Europe	Heat	More severe or more likely to occur	"For July temperature in Moscow, we estimate.....	2011.0	Rahmstorf, S. & Coumou, D. 2011: Increase of e...	Proceedings of the National Academy of Sciences	No	http://www.pnas.org/content/108/44/17905.abstract
...	...	...	...	...	...	...	...	...	...	...	...	...	...	...
739	China growing season hot and dry events	mid 1990s	Mid-1990s	Event	CHN	Eastern and south-eastern Asia	Compound	More severe or more likely to occur	"Anthropogenic forcing changes can explain 60%...	2024.0	Su Q. et al., 2024: Anthropogenic Influence on...	Advances in Atmospheric Sciences	No	https://doi.org/10.1007/s00376-023-2319-z
740	China hot-wet events	1979-2014	NaN	Trend	CHN	Eastern and south-eastern Asia	Compound	Decrease, less severe or less likely to occur	"Over the past 40 years, anthropogenic activit...	2024.0	Yao H. et al., 2024: Changes caused by human a...	Communications Earth & Environment	No	https://doi.org/10.1038/s43247-024-01625-y
741	Heat extremes behind bleaching of the Great Ba...	2020, 2024	2017, 2020, 2024	Event	AUS	Australia and New Zealand	Impact	More severe or more likely to occur	"Climate model analysis confirms that human in...	2024.0	Henley B.J. et al., 2024: Highest ocean heat i...	Nature	No	https://doi.org/10.1038/s41586-024-07672-x
742	Heat-related neonatal deaths in low- and middl...	2001-2019	NaN	Trend	NaN	Global	Impact	More severe or more likely to occur	"Climate change was responsible for 32% (range...	2024.0	Dimitrova. A. et al., 2024: Temperature-relate...	Nature Communications	No	https://www.nature.com/articles/s41467-024-498...
743	Hospitalisations in China due to heat	2000-2019	NaN	Trend	CHN	Eastern and south-eastern Asia	Impact	More severe or more likely to occur	"In the 2010s, the heat-related attributable f...	2024.0	Zhou. L. et al,. 2024: Quantification of the H...	Environmental Health Perspectives	No	https://ehp.niehs.nih.gov/doi/10.1289/EHP14057

744 rows × 14 columns

attribution_studies['event_type'].value_counts()

event_type
Heat                207
Rain & flooding     177
Drought             106
Storm                61
Cold, snow & ice     57
Impact               33
Compound             33
Wildfire             31
Oceans               25
Atmosphere            7
Sunshine              4
River flow            3
Name: count, dtype: int64

attribution_studies['event_name'].value_counts()

event_name
Europe heatwave                          13
California drought                        7
Northern Europe summer heatwave           7
Damages from UK flooding                  4
Global temperature extremes               4
                                         ..
Yangtze river extreme rainfall            1
Extreme flooding in Missouri              1
France floods                             1
Storm Desmond heavy rains                 1
Hospitalisations in China due to heat     1
Name: count, Length: 678, dtype: int64

attribution_studies['classification'].value_counts()

classification
More severe or more likely to occur              554
No discernible human influence                    71
Decrease, less severe or less likely to occur     66
Insufficient data/inconclusive                    53
Name: count, dtype: int64

classification_labels = {
    'More severe or more likely to occur': 'More Severe/Likely',
    'Decrease, less severe or less likely to occur': 'Less Severe/Likely',
    'No discernible human influence': 'No human influence',
    'Insufficient data/inconclusive': 'Insufficient Data'
}

# sunburst plots
sunburst_data = attribution_studies.groupby(['study_focus', 'classification', 'event_type']).size().reset_index(name='count')
sunburst_data['classification'] = sunburst_data['classification'].map(classification_labels)

sunburst_data = sunburst_data.dropna(subset=['classification'])

event_focus_count = sunburst_data[sunburst_data['study_focus'] == 'Event']['count'].sum()
trend_focus_count = sunburst_data[sunburst_data['study_focus'] == 'Trend']['count'].sum()

fig = sp.make_subplots(rows=1, cols=2, specs=[[{'type':'domain'}, {'type':'domain'}]],
                       subplot_titles=(f'Event Focus ({event_focus_count})', f'Trend Focus ({trend_focus_count})'))

fig.add_trace(px.sunburst(sunburst_data[sunburst_data['study_focus'] == 'Event'], 
                          path=['classification', 'event_type'], values='count').data[0],
              row=1, col=1)

fig.add_trace(px.sunburst(sunburst_data[sunburst_data['study_focus'] == 'Trend'], 
                          path=['classification', 'event_type'], values='count').data[0],
              row=1, col=2)

fig.update_layout(title_text='Effect of climate change on extreme weather attributions &#8211; <br><span style="color:blue">More severe</span>, <span style="color:green">Less severe</span>, <span style="color:red">No human influence</span>, and <span style="color:purple">Insufficient data</span>.')

# Save figure
fig.write_html('sunburst_plots_by_study_focus.html')
#fig.write_image("weather_attribution.png")
fig.show()

write_image didn’t work. HTML file was processed in inkscape to generate high resolution image.