将值添加到基于其他两列的新列

Question

我有一个看起来像这样的数据框。我创建了 3 个新列，它们将从其他列中获取值 columns.I 希望功能列单独列并为每个用户获取每个功能的总小时数。

 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

预期的输出看起来像

 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 但它抛出一个错误值 var not present

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

Answer 1

这里有一个使用 get_dummies and 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)

试试这个！变量 col 查找要为其插入值 Total hours 的列。

将值添加到基于其他两列的新列

Adding values to a new column based on other two columns

melt

pandas