How to create a pie-chart from pandas DataFrame?

Replace Topic by Other if no top N in Series.where and then aggregate sum with Series.plot.pie:

N = 10
df['Topic'] = df['Topic'].where(df['Count'].isin(df['Count'].nlargest(N)), 'Other')

s = df.groupby('Topic')['Count'].sum()

pie = df.plot.pie(y='Count', legend=False)

#https://stackoverflow.com/a/44076433/2901002
labels = [f'{l}, {s:0.1f}%' for l, s in zip(s.index, s / s.sum())]
plt.legend(bbox_to_anchor=(0.85, 1), loc='upper left', labels=labels)

You need to craft a new dataframe. Assuming your counts are sorted in descending order (if not, use df.sort_values(by='Count', inplace=True)):

TOP = 10
df2 = df.iloc[:TOP]
df2 = df2.append({'Topic': 'Other', 'Count': df['Count'].iloc[TOP:].sum()},
                 ignore_index=True)

df2.set_index('Topic').plot.pie(y='Count', legend=False)

Example (N=10, N=5):

Percentages in the legend:

N = 5
df2 = df.iloc[:N]
df2 = df2.append({'Topic': 'Other', 'Count': df['Count'].iloc[N:].sum()}, ignore_index=True)

df2.set_index('Topic').plot.pie(y='Count', legend=False)
leg = plt.legend(labels=df2['Count'])

output: