我正在编写一个代码,需要将多个NamedTuple
映射到一个列表中。
下面是代码示例-我的主要问题是关于对偶NamedTuple
PeopleName
和PeopleAge
的List
的映射-我不清楚如何做到这一点。这应该分为两个步骤,1/将整行提取到泛型NamedTupe
,然后2/将记录拆分为不同的NamedTuple
PeopleName
和PeopleAge
from typing import NamedTuple, List
import pandas as pd
data = [["tom", 10, "ab 11"], ["nick", 15, "ab 22"], ["juli", 14, "ab 11"]]
people = pd.DataFrame(data, columns=["Name", "Age", "PostalCode"])
PeopleName = NamedTuple("PeopleName", [("Name", str)])
PeopleAge = NamedTuple("PeopleAge", [("Age", int)])
PeoplePC = NamedTuple("PeoplePC", [("PostalCode", str)])
# The code below is not correct
Demography = NamedTuple(
"Demography", [("names", List[(PeopleName, PeopleAge)]), ("postalcodes", PeoplePC)],
)
def to_nested_tuple(k, g):
peoples = list(
g["Name"].to_frame().itertuples(name="Person", index=False),
# rec["Age"].to_frame().itertuples(name="PeopleAge", index=False),
)
return Demography(peoples, PeoplePC(k))
d = [to_nested_tuple(*item) for item in people.groupby("PostalCode")]
print(d)
使用
list(df.itertuples())
,其中df
是您的数据帧。你知道吗这个注解
List[(PeopleName, PeopleAge)]
抛出TypeError: Too many parameters for typing.List; actual 2, expected 1
。你知道吗具有两种不同类型的元组也应该用
typing.Tuple
注释:但是,要注释参数,最好使用抽象集合类型,如
Sequence
或Iterable
:我不会对每一组应用
to_nested_tuple
,而是直接按以下方式进行:现在,结果将打印为:
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