Question

我有两个pandas数据帧：

DF1

   id        type    NY    PA    MD
0  90  superurban   0.1   0.1  0.08
1  88       urban   0.1  0.08  0.08
2  75    suburban  0.06  0.04  0.04
3  60       rural  0.04  0.02  0.02

DF2

  name  item
0   NY  1000
1   PA   500
2   MD   250

如何根据状态缩写在df2中使用df1浮点值多个“item”值？输出应为：

   id  type         NY    PA   MD
0  90  superurban   100   50   20
1  88  urban        100   40   20
2  75  suburban      60   20   10
3  60  rural         40   10    5

Answer 1

我们可以这样做：

In [112]: d1[['NY','PA','MD']] *= d2.set_index('name')['item']

In [113]: d1
Out[113]:
   id        type     NY    PA    MD
0  90  superurban  100.0  50.0  20.0
1  88       urban  100.0  40.0  20.0
2  75    suburban   60.0  20.0  10.0
3  60       rural   40.0  10.0   5.0

或much better variant from @JohnGalt：

In [118]: d1[d2['name']] *= d2.set_index('name')['item']

In [119]: d1
Out[119]:
   id        type     NY    PA    MD
0  90  superurban  100.0  50.0  20.0
1  88       urban  100.0  40.0  20.0
2  75    suburban   60.0  20.0  10.0
3  60       rural   40.0  10.0   5.0

Answer 2

或者您可以使用mul;

df1[['NY','PA','MD']]=(df1[['NY','PA','MD']].T.reset_index().drop('index',1)).mul(df2.item,axis='index').T

Out[888]: 
   id        type     NY    PA    MD
0  90  superurban  100.0  50.0  20.0
1  88       urban  100.0  40.0  20.0
2  75    suburban   60.0  20.0  10.0
3  60       rural   40.0  10.0   5.0

乘以两个pandas数据帧

2 个答案: