1,用map来处理字符串列表啊,把列表中所有人都变成sb,比方alex_sb
name=['alex','wupeiqi','yuanhao']
name = list(map(lambda str1:str1 + "sb",name))
print(name) #['alexsb', 'wupeiqisb', 'yuanhaosb']
2,用map来处理下述l,然后用list得到一个新的列表,列表中每个人的名字都是sb结尾
l = [{'name':'alex'},{'name':'y'}]
new_l = map(lambda d:d["name"] + "sb",l)
p = map(lambda d:d,l)
t = map(lambda d:{'name':d["name"]+"sb"},l )
print(list(t)) #[{'name': 'alexsb'}, {'name': 'ysb'}]
3,用filter来处理,得到股票价格大于20的股票名字
shares={
'IBM':36.6,
'Lenovo':23.2,
'oldboy':21.2,
'ocean':10.2,
}
f = filter(lambda x:x[-1] > 20,shares.items())
for i in f:
print(i[0])
# oldboy
# Lenovo
# IBM
4,如下,每个小字典的name对应股票名字,shares对应多少股,price对应股票的价格
a.:map来得出一个包含数字的迭代器,数字指的是:购买每支股票的总价格
portfolio = [
{'name': 'IBM', 'shares': 100, 'price': 91.1},
{'name': 'AAPL', 'shares': 50, 'price': 543.22},
{'name': 'FB', 'shares': 200, 'price': 21.09},
{'name': 'HPQ', 'shares': 35, 'price': 31.75},
{'name': 'YHOO', 'shares': 45, 'price': 16.35},
{'name': 'ACME', 'shares': 75, 'price': 115.65}
]
from functools import reduce
m = map(lambda d:d["shares"]*float(d["price"]),portfolio)
o = list(m)
t = map(lambda d:d['name'],portfolio)
print(dict(zip(t,o)))
#{'HPQ': 1111.25, 'FB': 4218.0, 'ACME': 8673.75, 'AAPL': 27161.0, 'YHOO': 735.7500000000001, 'IBM': 9110.0}
b,基于1的结果,用reduce来计算,购买这些股票总共花了多少钱
print(reduce(lambda x,y:x+y ,o))# 51009.75
c.用filter过滤出,单价大于100的股票有哪些
m = filter(lambda d:d["price"]> 100,portfolio)
for i in m:
print(i)
# {'price': 543.22, 'name': 'AAPL', 'shares': 50}
# {'price': 115.65, 'name': 'ACME', 'shares': 75}