Python 将df1列中值的两个数据帧合并为df2列中逗号分隔的值

输入：包含以下数据的两个数据帧： df1：（注意EmployeeID是由逗号分隔的值组成的字符串）

df2：

我想在df1.EmployeeID中的ID列表中合并df2.EmployeeID上的df1和df2

输出：

| Employee Name | EmployeeID | Hours |
|---------------|------------|-------|
| John          | 2,22       | 8     |
| Kim           | 3          | 10    |

---

如果需要匹配多个值，如

EmployeeID=2,3,22

到

Hours=8+10

在理解中使用字典映射

split

和

sum

：

#converted to strings for match splitted values
df2['EmployeeID'] = df2['EmployeeID'].astype(str)
d = df2.set_index('EmployeeID')['Hours'].to_dict()

f = lambda x: sum(d[y] for y in x.split(', ') if y in d)
df1['Hours'] = df1['EmployeeID'].apply(f)
print (df1)
  Employee Name EmployeeID Hours
0          John      2, 22     8
1           Kim          3    10

通过整数匹配的另一个想法：

d = df2.set_index('EmployeeID')['Hours'].to_dict()

f = lambda x: sum(d[int(y)] for y in x.split(', ') if int(y) in d)
df1['Hours'] = df1['EmployeeID'].apply(f)

---

如果

EmployeeID

为

2,3,22

，则

Hours

为

8,10

？否，为8+10

#converted to strings for match splitted values
df2['EmployeeID'] = df2['EmployeeID'].astype(str)
d = df2.set_index('EmployeeID')['Hours'].to_dict()

f = lambda x: sum(d[y] for y in x.split(', ') if y in d)
df1['Hours'] = df1['EmployeeID'].apply(f)
print (df1)
  Employee Name EmployeeID Hours
0          John      2, 22     8
1           Kim          3    10

d = df2.set_index('EmployeeID')['Hours'].to_dict()

f = lambda x: sum(d[int(y)] for y in x.split(', ') if int(y) in d)
df1['Hours'] = df1['EmployeeID'].apply(f)