Pandas 非常简单 来自 Group by 的总大小百分比
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Pandas Very Simple Percent of total size from Group by
提问by horatio1701d
I'm having trouble for a seemingly incredibly easy operation. What is the most succint way to just get a percent of total from a group by operation such as df.groupby['col1'].size(). My DF after grouping looks like this and I just want a percent of total. I remember using a variation of this statement in the past but cannot get this to work now: percent = totals.div(totals.sum(1), axis=0)
我遇到了一个看似非常简单的操作的麻烦。通过诸如df.groupby['col1'].size(). 分组后我的 DF 看起来像这样，我只想要总数的百分比。我记得过去使用过此语句的变体，但现在无法使其正常工作：percent = totals.div(totals.sum(1), axis=0)
Original DF:
原始DF：
A B C
0 77 3 98
1 77 52 99
2 77 58 61
3 77 3 93
4 77 31 99
5 77 53 51
6 77 2 9
7 72 25 78
8 34 41 34
9 44 95 27
Result:
结果：
df1.groupby('A').size() / df1.groupby('A').size().sum()
A
34 0.1
44 0.1
72 0.1
77 0.7
Here is what I came up with so far which seems pretty reasonable way to do this:
到目前为止，这是我想出的似乎很合理的方法：
df.groupby('col1').size().apply(lambda x: float(x) / df.groupby('col1').size().sum()*100)
采纳答案by horatio1701d
Getting good performance (3.73s) on DF with shape (3e6,59) by using:
df.groupby('col1').size().apply(lambda x: float(x) / df.groupby('col1').size().sum()*100)
通过使用以下命令在形状为 (3e6,59) 的 DF 上获得良好的性能 (3.73s)：
df.groupby('col1').size().apply(lambda x: float(x) / df.groupby('col1').size().sum()*100)
回答by Roman Pekar
I don't know if I'm missing something, but looks like you could do something like this:
我不知道我是否遗漏了什么，但看起来你可以做这样的事情：
df.groupby('A').size() * 100 / len(df)
or
或者
df.groupby('A').size() * 100 / df.shape[0]
回答by Alexander
How about:
怎么样：
df = pd.DataFrame({'A': {0: 77, 1: 77, 2: 77, 3: 77, 4: 77, 5: 77, 6: 77, 7: 72, 8: 34, 9: None},
'B': {0: 3, 1: 52, 2: 58, 3: 3, 4: 31, 5: 53, 6: 2, 7: 25, 8: 41, 9: 95},
'C': {0: 98, 1: 99, 2: 61, 3: 93, 4: 99, 5: 51, 6: 9, 7: 78, 8: 34, 9: 27}})
>>> df.groupby('A').size().divide(sum(df['A'].notnull()))
A
34 0.111111
72 0.111111
77 0.777778
dtype: float64
>>> df
A B C
0 77 3 98
1 77 52 99
2 77 58 61
3 77 3 93
4 77 31 99
5 77 53 51
6 77 2 9
7 72 25 78
8 34 41 34
9 NaN 95 27
