pandas -给定特定b的条件概率 [英] Pandas - Conditional Probability of a given specific b

问题描述

我有两个带有"a"和"b"列的DataFrame.在给定特定的"b"的情况下，如何找到"a"的条件概率?

I have DataFrame with two columns of "a" and "b". How can I find the conditional probability of "a" given specific "b"?

df.groupby('a').groupby('b')

不起作用.假设我在a列中有3个类别，对于每个特定的类别，我都有5个b类别.我需要做的是为a的每个班级找到b的上班总数.我尝试了Apply命令，但是我想我不知道如何正确使用它.

does not work. Lets assume I have 3 categories in column a, for each specific on I have 5 categories of b. What I need to do is to find total number of on class of b for each class of a. I tried apply command, but I think I do not know how to use it properly.

df.groupby('a').apply(lambda x: x[x['b']] == '...').count()

推荐答案

要为类a的每个实例查找类b的总数，您可以这样做

To find the total number of class b for each instance of class a you would do

df.groupby('a').b.value_counts()

例如，创建如下的DataFrame:

For example, create a DataFrame as below:

df = pd.DataFrame({'A':['foo', 'bar', 'foo', 'bar','foo', 'bar', 'foo', 'foo'], 'B':['one', 'one', 'two', 'three','two', 'two', 'one', 'three'], 'C':np.random.randn(8), 'D':np.random.randn(8)})

     A      B         C         D
0  foo    one -1.565185 -0.465763
1  bar    one  2.499516 -0.941229
2  foo    two -0.091160  0.689009
3  bar  three  1.358780 -0.062026
4  foo    two -0.800881 -0.341930
5  bar    two -0.236498  0.198686
6  foo    one -0.590498  0.281307
7  foo  three -1.423079  0.424715

然后:

df.groupby('A')['B'].value_counts()

A
bar  one      1
     two      1
     three    1
foo  one      2
     two      2
     three    1

要将其转换为条件概率，您需要除以每个组的总大小.

To convert this to a conditional probability, you need to divide by the total size of each group.

您可以与另一个groupby一起使用:

You can either do it with another groupby:

df.groupby('A')['B'].value_counts() / df.groupby('A')['B'].count()

A
bar  one      0.333333
     two      0.333333
     three    0.333333
foo  one      0.400000
     two      0.400000
     three    0.200000
dtype: float64

或者您可以将lambda函数应用于组:

Or you can apply a lambda function onto the groups:

df.groupby('a').b.apply(lambda g: g.value_counts()/len(g))

这篇关于 pandas -给定特定b的条件概率的文章就介绍到这了，希望我们推荐的答案对大家有所帮助，也希望大家多多支持IT屋！