Thanks very much, in chemycal proccess 
1 Like
Hi Ester,
The way the pie chart interacts on hover is nice.
2 Likes
Hi @Ester
I think the message on your topcards would be stronger if you would convert it into something like:
180/500 = 36% of the households in the top-5 cat?-countries owns a cat.
Love the colors.
2 Likes
I didn’t want to put too much time into this as work is getting busy. But, I took a sec to make a figure. Ideally, I would like to have put charts on a map. But, for now, I settled for putting emoji symbols as annotations on the map. I scaled the symbol with fontsize as the percent ownership to a small exponent.
I then played with the hoverdata to give some information.
import plotly.graph_objects as go
import pandas as pd
import numpy as np
petdata = pd.read_csv('https://raw.githubusercontent.com/plotly/Figure-Friday/refs/heads/main/2025/week-16/pet_ownership_data_updated.csv')
petdata.loc[petdata['Country'] == 'USA','Country'] = 'United States'
petdata.loc[petdata['Country'] == 'UK','Country'] = 'United Kingdom'
petdata.loc[petdata['Country'] == 'Russia','Country'] = 'Russian Federation'
petdata = petdata.iloc[0:-1,:] #Drop the last row
petdata = petdata.sort_values(['Country'])
petdata = petdata.reset_index(drop=True)
countriesdf = pd.read_csv('https://raw.githubusercontent.com/gavinr/world-countries-centroids/refs/heads/master/dist/countries.csv')
#Append data for Hong Kong
new_row = pd.DataFrame(
{
"longitude": [114.16993426713121],
"latitude": [22.318764728315433],
"COUNTRY": ['Hong Kong'],
'ISO': ['HK'],
'COUNTRYAFF': ['Hong Kong'],
'AFF_ISO': ['HK'],
}
)
countriesdf = pd.concat([countriesdf, new_row], ignore_index=True)
#Drop the rows of countriesdf that we don't care about
countriesdf = countriesdf.loc[countriesdf['COUNTRY'].isin(petdata['Country']),:]
countriesdf = countriesdf.sort_values(['COUNTRY'])
countriesdf = countriesdf.reset_index(drop=True)
petdata = pd.concat([petdata,countriesdf],axis=1)
petsymbols = {
'Bird': "🐦",
'Fish': "🐟",
'Dog': "🐕",
'Cat': "🐈"
}
fig = go.Figure()
for index, countryrow in petdata.iterrows():
thepets = countryrow[['Dog','Cat','Fish','Bird',]].sort_values(ascending = False)
thesymbols = [petsymbols[pet] for pet in thepets.keys()]
thesizes = [pct**1.26 for pct in thepets]
country = countryrow.loc['Country']
for i in range(4):#order the row
petpct = thepets.iloc[i]
thepet = thepets.keys()[i]+'s'
if thepet == 'Fishs':
thepet = 'Fish'
textstring = f'{petpct}% of people own {thepet}'
fig.add_trace(
go.Scattergeo(
lon=[countryrow['longitude']],# - (0.5*np.random.random(size=1)[0]-0.5)],
lat=[countryrow['latitude'] - 0.75*float(i)],# - (2*np.random.random(size=1)[0]-0.5)],
mode = "text",
text = thesymbols[i], #["🐦", "🐟", "🐕", "🐈"], #order is bird, fish, dog, cat
textfont = {'size': thesizes[i]},
hovertemplate = "<b>"+country+":</b><br>"+textstring + "<extra></extra>"
)
)
fig.update_layout(
showlegend = False,
geo = dict(
#resolution = 50,
showland = True,
showcountries = True,
showocean = True,
showlakes=False,
countrywidth = 0.5,
landcolor = 'rgb(253, 236, 199)',
oceancolor = 'rgb(163, 213, 231)',
projection = dict(
type = 'orthographic',
rotation = dict(
lon = 0,
lat = 40,
roll = 0
)
),
center=dict(
lat=45,
lon=10,
),
lataxis_range=[30,60],
lonaxis_range=[-15,30],
),
height = 1000,
width = 1000,
)
fig.show()
6 Likes
what a creative way of showing pet ownership stats! Nice job, @ranknovice .
2 Likes
@marieanne I fixed what you wrote me in KPIs and I changed the yellow colors for blue. 
3 Likes
I just saw your nice images and flags:)