使用Python進行數據分析熊貓

Question

我是熊貓圖書館的新手，需要一些幫助。我有兩列這樣的：

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

現在，我需要找到不合格，合格的總數，並從「測試結果」欄略過，我能夠做到這一點。但是，我還需要從「風險評級」列中將「測試結果」列的「失敗」總數與「低」進行比較。同樣，總數失敗與中等等。我的最終結果應該如下所示：

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 

我該怎麼做？任何幫助，將不勝感激。

Answer 1

我想你需要groupby由兩列和彙總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 

也許更好的數據透視表與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與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