擅长：python、mysql、java
<p>您可以尝试以下方法：</p>
<pre><code># sort dataframe
df.sort_values(by=['count'], inplace=True)
# recreate the index of your rows to make sure that 0 corresponds to the one with the higher count
df.reset_index(drop=True, inplace=True)
# add your new row to your dataset
df.append({'useragent': 'Others', 'count': df.loc[5:]['count'].cumsum()}, inplace=True)
# drop the rows you don't need anymore
df.drop([5:len(df.index.values.tolist())-1], inplace=True)
</code></pre>
<p>虽然我不能完全确定，但值得一试。我希望它能给你们一些想法</p>
