1、车牌区域划分, 现给出以下车牌. 根据车牌的信息, 分析出各省的车牌持有量.
结果: {‘山东‘: 2, ‘北京‘: 1, ‘黑龙江‘: 2, ‘上海‘: 1}
cars = [‘鲁A32444‘, ‘鲁B12333‘, ‘京B8989M‘, ‘黑C49678‘, ‘黑C46555‘, ‘沪B25041‘] local_s = {‘沪‘: ‘上海‘, ‘黑‘: ‘黑龙江‘, ‘鲁‘: ‘山东‘, ‘鄂‘: ‘湖北‘, ‘湘‘: ‘湖南‘, ‘京‘: ‘北京‘}
area = [] con = {} for a in cars: area.append(a[0]) for i in area: add = local_s.get(i) con.setdefault(add, area.count(i)) print(con)
2、文件a1.txt内容
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name:apple price:10 amount:3 year:2012
name:tesla price:100000 amount:1 year:2013
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? 通过代码，将其构建成这种数据类型：
? [{‘name‘:‘apple‘,‘price‘:10,‘amount‘:3,‘year‘:2012},
? {‘name‘:‘tesla‘,‘price‘:1000000,‘amount‘:1}......]
? 并计算出总价钱。
content_list = [] _list = [] with open(‘a1.txt‘, encoding=‘utf=8‘, mode=‘r‘) as f1: for row in f1: list_row = row.split() _list.append(list_row) for row1 in _list: content_dict = {} for row2 in row1: content = row2.split(‘:‘) if content[1].isdigit(): content[1] = int(content[1]) content_dict[content[0]] = content[1] content_list.append(content_dict) print(content_list) price = 0 for i in range(len(content_list)): price += content_list[i].get(‘price‘) print(price)
4、文件a1.txt内容
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序号 部门 人数 平均年龄 备注
1 python 30 26 单身狗
2 Linux 26 30 没对象
3 运营部 20 24 女生多
.......
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通过代码，将其构建成这种数据类型：
[{‘序号‘:‘1‘,‘部门‘:Python,‘人数‘:30,‘平均年龄‘:26,‘备注‘:‘单身狗‘},
......]
list_new = [] with open(‘a2.txt‘, encoding=‘utf=8‘, mode=‘r‘) as f2: row_1_list = f2.readline().split() for i in range(3): lis1 = f2.readline().strip().split() dict_new = {} for n in range(len(lis1)): dict_new[row_1_list[n]] = lis1[n] list_new.append(dict_new) print(list_new)
原文：https://www.cnblogs.com/XiaoYang-sir/p/14644577.html