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}
原文：http://www.cnblogs.com/hongyongshang/p/6705912.html