As already stated in the comments, the best way to do this is probably to do the manipulations before plotting. Here's a way how to do it:
import pandas as pd
from matplotlib import pyplot as plt
import numpy as np
countries = [
'Albania',
'Brazil',
'Denmark',
'France',
'Mexico',
'Nigeria',
'Spain',
'Germany',
'Finland',
]
#the full dataframe
df = pd.DataFrame(
data = {'country': countries, 'value' :np.random.rand(len(countries))},
).sort_values('value', ascending = False)
#the top 5
df2 = df[:5].copy()
#others
new_row = pd.DataFrame(data = {
'country' : ['others'],
'value' : [df['value'][5:].sum()]
})
#combining top 5 with others
df2 = pd.concat([df2, new_row])
#plotting -- for comparison left all countries and right
#the others combined
fig, axes = plt.subplots(nrows = 1, ncols = 2, figsize = (9,4))
df.plot(kind = 'pie', y = 'value', labels = df['country'], ax = axes[0])
df2.plot(kind = 'pie', y = 'value', labels = df2['country'], ax = axes[1])
axes[0].set_title('all countries')
axes[1].set_title('top 5')
plt.show()
The result looks like this.
Hope this helps.
与恶龙缠斗过久,自身亦成为恶龙;凝视深渊过久,深渊将回以凝视…