條件計數

Question

我有形式，DF的熊貓數據幀=

index,result1,result2,result3 
    0  s  u  s  
    1  u  s  u 
    2  s      
    3  s  s  u 

我想添加其S發生的次數的列表的另一列該行，例如

index,result1,result2,result3,count 
    0  s  u  s  2 
    1  u  s  u  1 
    2  s      1 
    3  s  s  u  2 

我曾嘗試下面的代碼

col=['result1','result2','result3'] 
df[cols].count(axis=1) 

但這回小號

0,3 
1,3 
2,1 
3,3 

所以這個計數元件的數量，然後我試圖

df[df[cols]=='s'].count(axis=1) 

但這返回以下錯誤： 「無法比較[ 'S']與塊值」

任何幫助將不勝感激

Answer 1

對於我的作品投到string由astype數字和NaN列返回您的error：

print (df) 
    index result1 result2 result3 result4 
0  0  s  u  7  NaN 
1  1  u  s  7  NaN 
2  2  s  NaN  8  NaN 
3  3  s  s  7  NaN 
4  4  NaN  NaN  2  NaN 

print (df.dtypes) 
index  int64 
result1  object 
result2  object 
result3  int64 
result4 float64 
dtype: object 

cols = ['result1','result2','result3','result4'] 
df['count'] = df[df[cols].astype(str) == 's'].count(axis=1) 
print (df) 
    index result1 result2 result3 result4 count 
0  0  s  u  7  NaN  1 
1  1  u  s  7  NaN  1 
2  2  s  NaN  8  NaN  1 
3  3  s  s  7  NaN  2 
4  4  NaN  NaN  2  NaN  0 

或者sum只True從boolean mask值：

print (df[cols].astype(str) == 's') 

    result1 result2 result3 result4 
0 True False False False 
1 False True False False 
2 True False False False 
3 True True False False 
4 False False False False 

cols = ['result1','result2','result3','result4'] 
df['count'] = (df[cols].astype(str) =='s').sum(axis=1) 
print (df) 
    index result1 result2 result3 result4 count 
0  0  s  u  7  NaN  1 
1  1  u  s  7  NaN  1 
2  2  s  NaN  8  NaN  1 
3  3  s  s  7  NaN  2 
4  4  NaN  NaN  2  NaN  0 

另外一個不錯的解決方案是從Nickil Maveli - 使用numpy：

df['count'] = (df[cols].values=='s').sum(axis=1)