使用Python进行数据分析熊猫

Question

我是熊猫图书馆的新手，需要一些帮助。我有两列这样的：

Test Result  Risk Rating 
    Fail    Low     
    Pass    Medium 
    Skip    High 
    Pass    Low     
    Fail    Medium 
    Pass    High 
    Skip    Low     
    Fail    Medium 
    Fail    High 

现在，我需要找到不合格，合格的总数，并从“测试结果”栏略过，我能够做到这一点。但是，我还需要从“风险评级”列中将“测试结果”列的“失败”总数与“低”进行比较。同样，总数失败与中等等。我的最终结果应该如下所示：

Fail (Low Risk Rating) = 1 
Fail (Medium Risk Rating) = 2 
Fail (High Risk Rating) = 1 
Pass (Low Risk Rating) = 1 
Pass (Medium Risk Rating) = 1 
Pass (High Risk Rating) = 1 
Skip (Low Risk Rating) = 1 
Skip (Medium Risk Rating) = 0 
Skip (High Risk Rating) = 1 

我该怎么做？任何帮助，将不胜感激。

Answer 1

我想你需要groupby由两列和汇总size：

df = df.groupby(['Test Result', 'Risk Rating']).size().reset_index(name='counts') 
print (df) 
    Test Result Risk Rating counts 
0  Fail  High  1 
1  Fail   Low  1 
2  Fail  Medium  2 
3  Pass  High  1 
4  Pass   Low  1 
5  Pass  Medium  1 
6  Skip  High  1 
7  Skip   Low  1 

也许更好的数据透视表与unstack：

df = df.groupby(['Test Result', 'Risk Rating']).size().unstack(fill_value=0) 
print (df) 
Risk Rating High Low Medium 
Test Result     
Fail   1 1  2 
Pass   1 1  1 
Skip   1 1  0 

或者slowier溶液crosstab：

df = pd.crosstab(df['Test Result'], df['Risk Rating']) 
print (df) 
Risk Rating High Low Medium 
Test Result     
Fail   1 1  2 
Pass   1 1  1 
Skip   1 1  0 

如果需要mi与0 ssing值添加stack：。

df = df.groupby(['Test Result', 'Risk Rating']) 
     .size() 
     .unstack(fill_value=0) 
     .stack() 
     .reset_index(name='counts') 
print (df) 
    Test Result Risk Rating counts 
0  Fail  High  1 
1  Fail   Low  1 
2  Fail  Medium  2 
3  Pass  High  1 
4  Pass   Low  1 
5  Pass  Medium  1 
6  Skip  High  1 
7  Skip   Low  1 
8  Skip  Medium  0