Python 收集数据、计数并返回字典列表，即使数据不存在

假设我有一个像这样的mysql表

[
  {name='cat', count=1},
  {name='dog', count=0},
  {name='fish', count=0},
  {name='bird', count=1}
]

[
  {name='cat', count=0},
  {name='dog', count=1},
  {name='fish', count=1},
  {name='bird', count=0}
]

 [
  {name='cat', count=0},
  {name='dog', count=0},
  {name='fish', count=0},
  {name='bird', count=0}
]

tmp = dict()
for row in queryset:
   tmp.setdefault(row.customer, dict(cat=0, dog=0, fish=0, bird=0))
   if row.sub_type == 'cat':
      tmp[row.customer][row.sub_type] += 1

| id | type | sub | u type |客户|
|1 |动物|猫|约翰|
|2 |动物|狗|结婚|
|3 |动物|鱼|结婚|
|3 |动物|鸟|约翰|

我要做的是按客户收集数据，按子类型统计行数。动物类型有4个子类型（

猫

，

狗

，

鱼

，

鸟

），约翰有两个子类型（

猫

，

鸟

），玛丽也有两个子类型（

狗

，

鱼

）。假设我想得到John的一个结果，它应该是这样的

[
  {name='cat', count=1},
  {name='dog', count=0},
  {name='fish', count=0},
  {name='bird', count=1}
]

[
  {name='cat', count=0},
  {name='dog', count=1},
  {name='fish', count=1},
  {name='bird', count=0}
]

 [
  {name='cat', count=0},
  {name='dog', count=0},
  {name='fish', count=0},
  {name='bird', count=0}
]

tmp = dict()
for row in queryset:
   tmp.setdefault(row.customer, dict(cat=0, dog=0, fish=0, bird=0))
   if row.sub_type == 'cat':
      tmp[row.customer][row.sub_type] += 1

当我想得到关于

mary

的结果时，应该是这样的

[
  {name='cat', count=1},
  {name='dog', count=0},
  {name='fish', count=0},
  {name='bird', count=1}
]

[
  {name='cat', count=0},
  {name='dog', count=1},
  {name='fish', count=1},
  {name='bird', count=0}
]

 [
  {name='cat', count=0},
  {name='dog', count=0},
  {name='fish', count=0},
  {name='bird', count=0}
]

tmp = dict()
for row in queryset:
   tmp.setdefault(row.customer, dict(cat=0, dog=0, fish=0, bird=0))
   if row.sub_type == 'cat':
      tmp[row.customer][row.sub_type] += 1

因此，不在数据库中的sub_类型应该返回

count

为0。假设我想得到

Matthew

的结果。由于没有

Matthew

的数据，因此结果应该如下所示

[
  {name='cat', count=1},
  {name='dog', count=0},
  {name='fish', count=0},
  {name='bird', count=1}
]

[
  {name='cat', count=0},
  {name='dog', count=1},
  {name='fish', count=1},
  {name='bird', count=0}
]

 [
  {name='cat', count=0},
  {name='dog', count=0},
  {name='fish', count=0},
  {name='bird', count=0}
]

tmp = dict()
for row in queryset:
   tmp.setdefault(row.customer, dict(cat=0, dog=0, fish=0, bird=0))
   if row.sub_type == 'cat':
      tmp[row.customer][row.sub_type] += 1

我通常使用

setdefault（）

生成结果。我的代码可能是这样的

[
  {name='cat', count=1},
  {name='dog', count=0},
  {name='fish', count=0},
  {name='bird', count=1}
]

[
  {name='cat', count=0},
  {name='dog', count=1},
  {name='fish', count=1},
  {name='bird', count=0}
]

 [
  {name='cat', count=0},
  {name='dog', count=0},
  {name='fish', count=0},
  {name='bird', count=0}
]

tmp = dict()
for row in queryset:
   tmp.setdefault(row.customer, dict(cat=0, dog=0, fish=0, bird=0))
   if row.sub_type == 'cat':
      tmp[row.customer][row.sub_type] += 1

---

但是，我想知道是否有其他方法或更优雅的方法来实现这一点。

假设您有一个名为“people”的表，其中包含包含条目的字段“name”

name
--------
John
Mary
Mathew

上面提到的表格是一张叫做“宠物”的表格

您可以使用以下查询为每个人构建结果集

select
  A.name as customer,
  (select count(*) from pets where customer=A.name and sub_type='cat') as cat,
  (select count(*) from pets where customer=A.name and sub_type='dog') as dog,
  (select count(*) from pets where customer=A.name and sub_type='fish') as fish,
  (select count(*) from pets where customer=A.name and sub_type='bird') as bird
from people A

结果如下所示

customer    cat     dog     fish    bird
John        1       0       0       1
Marry       0       1       1       0
Mathew      0       0       0       0

添加额外的where子句并筛选我的姓名或提供

---

一次汇总所有结果。

您介意使用

pandas

吗？答案可能取决于

mysql

表类型，因此我在您的问题中添加了该标记，它与使用通用Python无关。是的，我很想使用查询