Question

有一个如下数据框：

 date     id  device    t1    t2       text             y1   y2 
 2010-1-1  1    pc      yes1  I am1     This is a test1    5    3
 2010-1-1  1    smart   yes1  I am1   This is a test1   6    4
 2010-1-1  1    table    yes1  I am1   This is a test1    7    5
 2010-1-1  2    pc       yes2  I am1   This is a test2      8    2
 2010-1-1  2    smart     yes2  I am1   This is a test2   8    3
 2010-1-1  2    table     yes2  I am1   This is a test2   9    4
 2010-1-1  3    pc        yes3  I am3      This is a test3   10   3
 2010-1-1  3    smart     yes3  I am3   This is a tes3    11   2
 ........................

现在我要合并一个新的数据帧：（1）。当id和date，t1，t2，text相同时，将y1和y2相加。（2）。当id和date，t1，t2，text相同时加入设备str。（3）。将公共行（具有相同的id，date，text，t1，t2）合并为一行，
和新的数据框如下：

 date   id  device  t1    t2            text                    y1   y2 
2010-1-1 1  pc,smart,table     yes1  I am1      This is a test1  18  12
2010-1-1  2   pc,smart,table      yes2  I am2      This is a test2 25  9
2010-1-1  3    pc,smart     yes3  I am3      This is a test3    21   5

Answer 1

使用

In [294]: (df.groupby(['date', 'id', 't1', 't2', 'text'], as_index=False)
             .agg({'device': ','.join, 'y1': sum, 'y2': sum}))
Out[294]:
       date  id    t1     t2             text          device  y1  y2
0  2010-1-1   1  yes1  I am1  This is a test1  pc,smart,table  18  12
1  2010-1-1   2  yes2  I am1  This is a test2  pc,smart,table  25   9
2  2010-1-1   3  yes3  I am3  This is a test3        pc,smart  21   5

Answer 2

每个组使用相同值的所有列使用tasks，并使用词典groupby汇总，最后添加agg以获得最终列的相同排序：

df = (df.groupby(['date','id', 't1', 't2', 'text'], as_index=False)
        .agg({'y1':'sum', 'y2':'sum', 'device': ', '.join})
        .reindex(columns=df.columns))
print (df)
       date  id            device    t1     t2             text  y1  y2
0  2010-1-1   1  pc, smart, table  yes1  I am1  This is a test1  18  12
1  2010-1-1   2  pc, smart, table  yes2  I am1  This is a test2  25   9
2  2010-1-1   3         pc, smart  yes3  I am3  This is a test3  21   5

pandas dataframe：基于公共列的多列值和

2 个答案: