[英]How to count unique combinations of variable in a Pandas Dataframe
I'm using pandas to count unique combinations of sets of variables in a dataframe. 我正在使用pandas来计算数据帧中变量集的唯一组合。 I'm currently using the .groupby() function, but I think I'm missing part of it's functionality.
我目前正在使用.groupby()函数,但我认为我缺少它的一部分功能。
Example code: 示例代码:
import pandas
df = pd.DataFrame([['A','C','G'],
['A','C','H'],
['A','D','G'],
['A','D','H'],
['B','E','I'],
['B','F','I']], columns=['a','b','c'])
df
a b c
0 A C G
1 A C H
2 A D G
3 A D H
4 B E I
5 B F I
Say I want to know, for every unique value a, how many different b's does it have? 我想知道,对于每个独特的价值a,它有多少不同的b? In this example, the desired output is A: 2, B:2 because A has two unique b values and B has two unique b values.
在此示例中,所需输出为A:2,B:2,因为A具有两个唯一的b值,B具有两个唯一的b值。
If I were counting the unique c's per a, I would expect A: 2, B: 1. 如果我计算每个的唯一c,我会期望A:2,B:1。
My current code is: 我目前的代码是:
df.groupby(['a','b'],as_index=False).count().groupby(['a'], as_index=False).count()[['a','b']]
a b
0 A 2
1 B 2
df.groupby(['a','c'], as_index=False).count().groupby(['a'],as_index=False).count()[['a','c']]
a c
0 A 2
1 B 1
This gives me the correct result, but I think there should be a way to avoid two sets of groupby() and count(), no? 这给了我正确的结果,但我认为应该有办法避免两组groupby()和count(),不是吗?
How about nunique
? nunique
怎么nunique
?
df.groupby('a')['b'].nunique()
Out[36]:
a
A 2
B 2
Name: b, dtype: int64
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