Python数据持久化-小测验

2018年7月13日考试

1.Python读写csv文件

现有如下图1所示的data.csv文件数据，请使用python读取该csv文件数据，并添加一条记录后输出如图2所示的output.csv文件（10分）

题1.png

import csv 

def printCsv(csvName):
    with open(csvName) as csvFile:
        reader = csv.reader(csvFile)
        for i in reader:
            print(i)

if __name__ == "__main__":
    inCsv = "data.csv"
    outCsv = "output.csv"
    with open(inCsv) as csvFile:
        reader = csv.reader(csvFile)
        data = list(reader)
    print("原csv文件data.csv的数据内容：")
    printCsv(inCsv)
    data.append(['Jack','104'])
    with open(outCsv,'w',
        newline='') as csvFile:
        writer = csv.writer(csvFile)
        writer.writerows(data)
    print("新产生的csv文件output.csv的数据内容:")
    printCsv(outCsv)

上面一段代码的运行结果如下:

原csv文件data.csv的数据内容：
['name', ' stuNo']
['ZhangSan', ' 101']
['LiSi', ' 102']
['WangWu', ' 103']
新产生的csv文件output.csv的数据内容:
['name', ' stuNo']
['ZhangSan', ' 101']
['LiSi', ' 102']
['WangWu', ' 103']
['Jack', '104']

2.Python读写excel文件

如下所示的Excel表格数据，请编写python代码筛选出Points大于5的数据，并按Points进行排序后输出如图2所示的Excel文件结果

题2.png

import xlrd
import xlwt

if __name__ == "__main__":
    excel = xlrd.open_workbook("rank.xlsx")
    sheet = excel.sheet_by_index(0)
    #获取字段列表赋值给field_list,第2个字段大于5的数据列表赋值给data_list
    field_list = sheet.row_values(0)
    data_list = []
    for i in range(1,sheet.nrows):
        if int(sheet.row_values(i)[2]) > 5:
            data_list.append(sheet.row_values(i))
    #利用sorted内置函数排序
    data_list = sorted(data_list,key=lambda x:x[2],reverse=True)
    #将获得的信息存入新表,命名为output.xlsx
    excel_w = xlwt.Workbook()
    sheet_w = excel_w.add_sheet("sheet1")
    for i in range(len(field_list)):
        sheet_w.write(0,i,field_list[i])
    for i in range(len(data_list)):
        for j in range(len(data_list[i])):
            sheet_w.write(i+1,j,data_list[i][j])
    excel_w.save("output.xls")

3.mysql数据库的sql语句

（1） 使用sql创建出如下图所示的数据表，数据库名为movies，表名为movieRank，表中包含MovieName、boxOffice、percent、days、totalBoxOffice五个字段，字段的信息如下图所示：

题3-1.png

创建语句.png

（2）使用sql语句向movieRank表中添加若干条数据（材料中已提供movieData.txt）

insert into movierank values("21克拉", 1031.92, 15.18, 2, 2827.06);
insert into movierank values("狂暴巨兽", 2928.28, 43.07, 9, 57089.20);
insert into movierank values("起跑线", 161.03, 2.37, 18, 19873.43);
insert into movierank values("头号玩家", 1054.87, 15.52, 23, 127306.41);
insert into movierank values("红海行动", 45.49, 0.67, 65, 364107.74);

插入数据的结果如下图所示：

插入结果图示.png

（3）使用sql语句查询movieRank表中的数据并按照totalBoxOffice字段进行排序

select * from movierank order by totalboxoffice;

（4）使用sql语句计算出字段totalBoxOffice字段的总和

select sum(totalboxoffice) from movierank;

4.Python操作mysql数据库

此题接第3题题干，在第三题的基础上完成以下需求：
（1）编写python代码连接mysql数据库，并向movieRank表中新添加两条数据（已提供second.txt）

import pymysql

def getConn(database ="pydb"):
    args = dict(
        host = 'localhost',
        user = 'root',
        passwd = 'Leimysql8',
        charset = 'utf8',
        db = database
    )
    return pymysql.connect(**args)

if __name__ == "__main__":
    conn = getConn("movies")
    cursor = conn.cursor()
    insert_sql = 'insert into movierank values'
    '("犬之岛", 617.35, 9.08, 2, 1309.09),'
    '("湮灭", 135.34, 1.99, 9 , 5556.77)'
    cursor.execute(insert_sql)
    conn.commit()
    conn.close()

（2）编写python代码，查询出所有的电影数据，并输出到一个Excel表movieRank.xlsx中,如下图所示

题4-2.png

import pymysql
import xlwt

def getConn(database ="pydb"):
    args = dict(
        host = 'localhost',
        user = 'root',
        passwd = 'Leimysql8',
        charset = 'utf8',
        db = database
    )
    return pymysql.connect(**args)

if __name__ == "__main__":
    #从mysql数据库中取出数据赋值给data_list，其数据类型为元组
    conn = getConn("movies")
    cursor = conn.cursor()
    select_sql = "select * from movierank "
    cursor.execute(select_sql)
    data_list = cursor.fetchall()
    field_list = [k[0] for k in cursor.description]
    #把data_list中的数据存入新的excel中，并命名为movieRank.xls
    excel = xlwt.Workbook()
    sheet = excel.add_sheet("sheet1")
    for i in range(len(field_list)):
        sheet.write(0,i,field_list[i])
    for i in range(len(data_list)):
        for j in range(len(data_list[i])):
            sheet.write(i+1,j,data_list[i][j])
    excel.save("movieRank.xls")

5.Python操作MongoDB数据库

（1）编写python代码连接MongoDB数据库，并新建一个building库，在building库下新建一个rooms表

from pymongo import MongoClient

if __name__ == "__main__":
    conn = MongoClient("localhost")
    db = conn.building
    rooms = db.create_collection("rooms")

（2）编写python代码读取rooms.csv文件的中的数据，并将数据插入到rooms表中，添加到rooms表中的数据结构如下图所示

image.png

from pymongo import MongoClient
import csv

if __name__ == "__main__":
    with open("rooms.csv") as csvFile:
        reader = list(csv.reader(csvFile))
        field_list = reader[0]
        data_list = reader[1:]
    conn = MongoClient("localhost")
    db = conn.building
    rooms = db.rooms
    insert_list = []
    for data in data_list:
        insert_list.append(
            {key:value for key,value in zip(field_list,data)})
    rooms.insert_many(insert_list)

使用csv.DictReader方法

from pymongo import MongoClient
import csv

if __name__ == "__main__":
    conn = MongoClient("localhost")
    db = conn.building
    rooms = db.rooms
    with open("rooms.csv") as csvFile:
        reader = csv.DictReader(csvFile)
        for row in reader:
            rooms.insert_one(dict(row))