python - 使用 pandas 总结分类问卷数据

Question

从Python开始，我遇到了一个很常见但找不到简单解决方案的问题。我有一些虚构的问卷数据，我想获得有意义的描述。具体来说，对于每个问题，我想知道给出了多少次特定的回答("is"/“也许”/“否”)。

输入:

         Question1   Question2   Question3
Answer1  Maybe       Yes         Yes
Answer2  No          Maybe       Yes
Answer3  Maybe       Maybe       No
Answer4  No          Yes         Maybe

现在，我想大致了解某个问题的特定答案的次数。首选输出如下:

(首选)输出:

           Yes     Maybe    No
Question1  0       2        2
Question2  2       2        0
Question3  2       1        1

我自己的想法是解决方案必须在“groupby”命令中。到目前为止，我还没有成功获得任何有意义的输出:

df.groupby(['Question1']).sum()
      Question2 Question3
Question1                    
Maybe      YesMaybe     YesNo
No         MaybeYes  YesMaybe

我已经生成了虚拟数据:

# Generate data
data = np.array([['','Question1','Question2','Question3'],['Answer1',"Maybe","Yes","Yes"],['Answer2',"No","Maybe","Yes"],['Answer3',"Maybe","Maybe","No"],['Answer4',"No","Yes","Maybe"]])          


# convert to pandas dataframe
df = pd.DataFrame(data=data[1:,1:],index=data[1:,0],columns=data[0,1:])

我知道这肯定是一个简单的挑战，但我们将不胜感激任何帮助。

Answer 1

简单

df.apply(pd.value_counts).fillna(0)


            Question1   Question2   Question3
Maybe       2.0         2.0         1.0
No          2.0         0.0         1.0
Yes         0.0         2.0         2.0

如果需要，可以转置它df.apply(pd.value_counts).fillna(0).T

            Maybe   No    Yes
Question1   2.0     2.0   0.0
Question2   2.0     0.0   2.0
Question3   1.0     1.0   2.0