Question

我有一个看起来像这样的数据框。我创建了3个新列，这些列将从其他列中获取值。我希望功能列将各列分开，并为每个用户获取每个功能的总工作时间。

 User         Function          Total hours   Damage Processing problem solve damages sweeper
 schae      Damage Processing      9.36
 Julie      Problem solve          9.70
 John       sweeper                18.9
 Dan       Damages                 1.83
 Dan       Damages                 1.83
 Julie     Damages                 1.83
 Dan       Problem solve           1.83

预期输出看起来像

 User         Function          Total hours   Damage Processing  problem solve damages  sweeper
 schae     Damage Processing       9.36          9.36
 Julie     Problem solve           9.70                            9.70
 John      sweeper                 18.9                                                  18.9
 Dan       Damages                 1.83                                        1.83                                 
 Dan       sweeper                 1.83                                                  1.83
 Julie     Damages                 1.83                                        1.83
 Dan       Problem solve           1.83                            1.83

我想到了pd.melt，但是它抛出了一个错误值var不存在

res = pd.melt(result,id_vars = ['Function'],value_vars=['Total hours'])

Answer 1

这是使用get_dummies和df.assign的方法：

out = (df[['User','Function','Total hours']].assign(**pd.get_dummies(df['Function'])
       .mul(df['Total hours'],axis=0).replace(0,np.nan)))
print(out)

    User           Function  Total hours  Damage Processing  Damages  \
0  schae  Damage Processing         9.36               9.36      NaN   
1  Julie      Problem solve         9.70                NaN      NaN   
2   John            sweeper        18.90                NaN      NaN   
3    Dan            Damages         1.83                NaN     1.83   
4    Dan            Damages         1.83                NaN     1.83   
5  Julie            Damages         1.83                NaN     1.83   
6    Dan      Problem solve         1.83                NaN      NaN   

   Problem solve  sweeper  
0            NaN      NaN  
1           9.70      NaN  
2            NaN     18.9  
3            NaN      NaN  
4            NaN      NaN  
5            NaN      NaN  
6           1.83      NaN

Answer 2

for i in range(len(df)):
    col = df.loc[i]['Function']
    df.at[i, col] = df.xs(i)['Total hours']
    print(col)

试试看！变量col查找您要为其插入值Total hours的列。

根据其他两列将值添加到新列

2 个答案: