pandas 大熊猫 value_counts() 主要按降序排序，其次按升序排序
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sort pandas value_counts() primarily by descending counts and secondarily by ascending values
提问by eyaler
When applying value_counts() to a series in pandas, by default the counts are sorted in descending order, however the values are not sorted within each count.
将 value_counts() 应用于 Pandas 中的系列时，默认情况下，计数按降序排序，但不会在每个计数内对值进行排序。
How can i have the values within each identical count sorted in ascending order?
如何将每个相同计数中的值按升序排序？
apples 5
peaches 5
bananas 3
carrots 3
apricots 1
回答by JohnE
The output of value_counts is a series itself (just like the input), so you have available all of the standard sorting options as with any series. For example:
value_counts 的输出本身就是一个系列（就像输入一样），因此您可以像任何系列一样使用所有标准排序选项。例如：
df = pd.DataFrame({ 'fruit':['apples']*5 + ['peaches']*5 + ['bananas']*3 +
['carrots']*3 + ['apricots'] })
df.fruit.value_counts().reset_index().sort([0,'index'],ascending=[False,True])
index 0
0 apples 5
1 peaches 5
2 bananas 3
3 carrots 3
4 apricots 1
I'm actually getting the same results by default so here's a test with ascending=[False,False]to demonstrate that this is actually working as suggested.
我实际上在默认情况下得到了相同的结果，所以这里有一个测试ascending=[False,False]来证明这实际上是按照建议工作的。
df.fruit.value_counts().reset_index().sort([0,'index'],ascending=[False,False])
index 0
1 peaches 5
0 apples 5
3 carrots 3
2 bananas 3
4 apricots 1
I'm actually a bit confused about exactly what desired output here in terms of ascending vs descending, but regardless, there are 4 possible combos here and you can get it however you like by altering the ascendingkeyword argument.
我实际上对这里在升序和降序方面究竟需要什么输出有点困惑，但无论如何，这里有 4 种可能的组合，你可以通过改变ascending关键字参数来获得它。
