I have a list of t-shirt orders along with the corresponding size and I would like to plot them in pie chart for each design showing the percentage in which size sells the most etc.
Design Total
0 Boba L 9
1 Boba M 4
2 Boba S 2
3 Boba XL 5
4 Burger L 6
5 Burger M 2
6 Burger S 3
7 Burger XL 1
8 Donut L 5
9 Donut M 9
10 Donut S 2
11 Donut XL 5
It is not complete clear what you asking, but here is my interpretation:
df[['Design', 'Size']] = df['Design'].str.rsplit(n=1, expand=True)
fig, ax = plt.subplots(1, 3, figsize=(10,8))
ax = iter(ax)
for t, g in df.groupby('Design'):
g.set_index('Size')['Total'].plot.pie(ax=next(ax), autopct='%.2f', title=f'{t}')
Maybe you want:
df = pd.read_clipboard() #create data from above text no modification
dfplot = df.loc[df.groupby(df['Design'].str.rsplit(n=1).str[0])['Total'].idxmax(), :]
ax = dfplot.set_index('Design')['Total'].plot.pie(autopct='%.2f')
ax.set_ylabel('');
Let do groupby.plot.pie:
(df.Design.str.split(expand=True)
.assign(Total=df['Total'])
.groupby(0)
.plot.pie(x=1,y='Total', autopct='%.1f%%')
)
# format the plots
for design, ax in s.iteritems():
ax.set_title(design)
one of the output:
