EuroLeague Basketball

TidyTuesday dataset of 2025-10-07

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.