TidyTuesday dataset of October 7, 2025

import pandas as pd
import numpy as np
import matplotlib.pyplot as plt
import matplotlib.image as mpimg
from matplotlib.offsetbox import OffsetImage, AnnotationBbox
import flagpy as fp

euroleague_basketball = pd.read_csv('https://raw.githubusercontent.com/rfordatascience/tidytuesday/main/data/2025/2025-10-07/euroleague_basketball.csv')

euroleague_basketball

	Team	Home city	Arena	Capacity	Last season	Country	FinalFour_Appearances	Titles_Won	Years_of_FinalFour_Appearances	Years_of_Titles_Won
0	Anadolu Efes	Istanbul	Basketball Development Center	10,000	6th	Turkey	5	2	2000, 2001, 2019, 2021, 2022	2021, 2022
1	Barcelona	Barcelona	Palau Blaugrana	7,585	5th	Spain	0	0	NaN	NaN
2	Baskonia	Vitoria-Gasteiz	Buesa Arena	15,431	14th	Spain	0	0	NaN	NaN
3	Bayern Munich	Munich	SAP Garden	11,500	9th	Germany	0	0	NaN	NaN
4	Crvena zvezda Meridianbet	Belgrade	Belgrade Arena	18,386	10th	Serbia	0	0	NaN	NaN
5	Dubai Basketball	Dubai	Coca-Cola Arena	17,000	NaN	United Arab Emirates	0	0	NaN	NaN
6	Fenerbahce	Istanbul	Ülker Sports and Event Hall	13,000	1st	Turkey	7	2	2015, 2016, 2017, 2018, 2019, 2024, 2025	2017, 2025
7	Hapoel IBI Tel Aviv	Tel Aviv	Arena 8888 Sofia \ Arena Botevgrad \ Menora ...	12,373	(EuroCup)	Israel	0	0	NaN	NaN
8	LDLC ASVEL	Villeurbanne	LDLC Arena, Astroballe	12,523, 5,556	15th	France	0	0	NaN	NaN
9	Maccabi Rapyd Tel Aviv	Tel Aviv	Menora Mivtachim Arena	10,383	16th	Israel	0	0	NaN	NaN
10	Monaco	Monaco	Salle Gaston Médecin	5,000	2nd	Monaco	2	0	2023, 2025	NaN
11	Olimpia Milano	Milan	Unipol Forum	12,700	11th	Italy	4	0	1992, 2021	NaN
12	Olympiacos	Piraeus	Peace and Friendship Stadium	12,300	3rd	Greece	14	3	1994, 1995, 1997, 1999, 2009, 2010, 2012, 2013...	1997, 2012, 2013
13	Panathinaikos	Athens	Telekom Center Athens	18,300	4th	Greece	13	7	1994, 1995, 1996, 2000, 2001, 2002, 2005, 2007...	1996, 2000, 2002, 2007, 2009, 2011, 2024
14	Paris Basketball	Paris	Adidas Arena, Accor Arena	8,000, 15,705	8th	France	0	0	NaN	NaN
15	Partizan	Belgrade	Belgrade Arena	18,386	12th	Serbia	3	1	1988, 1992, 1998, 2010	1992
16	Real Madrid	Madrid	Movistar Arena	15,000	7th	Spain	12	6	1995, 1996, 2011, 2013, 2014, 2015, 2017, 2018...	1995, 2015, 2018, 2023
17	Valencia Basket	Valencia	Roig Arena	15,600	(EuroCup)	Spain	0	0	NaN	NaN
18	Virtus Olidata Bologna	Bologna	Virtus Arena, PalaDozza	9,980, 5,570	17th	Italy	0	0	NaN	NaN
19	Zalgiris	Kaunas	Žalgirio Arena	15,415	13th	Lithuania	2	1	1999, 2018	1999

countries = euroleague_basketball['Country'].unique()
countries

array(['Turkey', 'Spain', 'Germany', 'Serbia', 'United Arab Emirates',
       'Israel', 'France', 'Monaco', 'Italy', 'Greece', 'Lithuania'],
      dtype=object)

# save flag for each country
for country in countries:
    if country=='United Arab Emirates':
        continue
    img = fp.get_flag_img(country)
    img.save(f'{country}_flag.png')

df_grp_team = (
            euroleague_basketball.groupby(['Country','Team'])
            .agg({'Titles_Won': 'sum',
                  'Years_of_Titles_Won': lambda x: ', '.join(x.dropna()),
                  })
            .sort_values(by='Titles_Won', ascending=False)
            .reset_index()
)
df_grp_team = df_grp_team[df_grp_team['Titles_Won'] > 0]
df_grp_team

	Country	Team	Titles_Won	Years_of_Titles_Won
0	Greece	Panathinaikos	7	1996, 2000, 2002, 2007, 2009, 2011, 2024
1	Spain	Real Madrid	6	1995, 2015, 2018, 2023
2	Greece	Olympiacos	3	1997, 2012, 2013
3	Turkey	Fenerbahce	2	2017, 2025
4	Turkey	Anadolu Efes	2	2021, 2022
5	Serbia	Partizan	1	1992
6	Lithuania	Zalgiris	1	1999

Plotting

plt.rcParams['font.family'] = 'Segoe UI Emoji'

items = df_grp_team['Years_of_Titles_Won'].to_list()
def comma_newline(s):
    parts = [p.strip() for p in s.split(',')]
    separators = [',' if i % 2 == 0 else '\n' for i in range(len(parts) - 1)]
    return ''.join(p + sep for p, sep in zip(parts, separators)) + parts[-1]
#print(items)
year_won = [comma_newline(s) for s in items]
#print(year_won)

fig, ax = plt.subplots(figsize=(14, 3))#, subplot_kw=dict(polar=True))
plt.scatter(df_grp_team['Team'],[1]*len(df_grp_team['Titles_Won']), s=df_grp_team['Titles_Won']*1500, \
            color='orange', alpha=0)
for ind, (x, y, z) in enumerate(zip(df_grp_team['Team'],[1]*len(df_grp_team['Titles_Won']), year_won)):
    plt.text(x,y,z, fontsize=9, ha='center', va='top', color='black', family='monospace')
    plt.text(x, y,'\U0001F3C0', fontsize=(df_grp_team['Titles_Won'][ind]*10)+30, ha='center', va='center',\
            color='orange',zorder=1, alpha=0.8)
    plt.text(x, y-0.18,x, fontsize=12, ha='center', va='center', color='#333333')
    img = mpimg.imread(f'{df_grp_team["Country"][ind]}_flag.png')
    imagebox = OffsetImage(img, zoom=0.3)  
#    ab = AnnotationBbox(imagebox, (x, y-0.26), frameon=True, bboxprops=dict(edgecolor='lightgray'), zorder=2)  # Higher zorder
    ab = AnnotationBbox(imagebox, (x, y-0.26), frameon=False, zorder=2)  # Higher zorder
    ax.add_artist(ab)
plt.axis('off')
plt.xlim(-0.75,6.5)
plt.ylim(0.70,1.2)
plt.title("EuroLeague Basketball Champions", fontsize=20, family='Serif', color='#333333')
fig.patch.set_facecolor('#FFFDD0')
plt.savefig("euro_bb.png", dpi=300, bbox_inches="tight")
plt.show()

In the data, Real Madrid has six wins but only four years are given.