擅长:python、mysql、java
<p>使用:</p>
<pre><code>#first sorting data if necessary
df1 = df.sort_values('count', ascending=False)
#then get top 4 rows
df2 = df1.head(4)
#filter column `count` for all values after 4 rows
summed = df1.loc[df1.index[4:], 'count'].sum()
#create DataFrame by another counts
df3 = pd.DataFrame({'useragent':['Other'], 'count':[summed]})
#join together
df4 = pd.concat([df2, df3], sort=False, ignore_index=True)
print (df4)
useragent count
0 iPhone 11298
1 Mac 3206
2 iPad 627
3 SM-N960F 433
4 Other 435
</code></pre>
<p>编辑:</p>
<pre><code>#filter by threshold
mask = df['count'] > 500
#filtered rows by boolean indexing
df2 = df[mask]
#inverted mask - sum by count
summed = df.loc[~mask, 'count'].sum()
#same like above
df3 = pd.DataFrame({'useragent':['Other'], 'count':[summed]})
df5 = pd.concat([df2, df3], sort=False, ignore_index=True)
print (df5)
useragent count
0 iPhone 11298
1 Mac 3206
2 iPad 627
3 Other 868
</code></pre>