数据分析Python习题系列

缺乏、安全感 2022-11-14 10:29 165阅读 0赞

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## chapter1 ##

### title-1 ###

自定义字符串，完成字符串的索引/切片/find/count/replace/split/乘法/连接操作，并写出输出结果

>>> str='hello'
    >>> print("第二个字符是'{:}'".format(str[1]))
    第二个字符是'e'
    >>> print('{:}'.format(str[0:2]))
    he
    >>> strFind='lo'
    >>> print(str.find(strFind))
    3
    >>> sub='l'
    >>> print(str.count(sub))
    2
    >>> print(str.replace("llo","666"))
    he666
    >>> print(str.split('o',1))
    ['hell', '']
    >>> str*3
    'hellohellohello'
    >>> p=' python'
    >>> str+p
    'hello python'

*  [Python 字符串][Python]
 *  [Python count()方法][Python count]
 *  [Python find()方法][Python find]
 *  [Python replace()方法][Python replace]
 *  [Python split()方法][Python split]

### title-2 ###

打印99乘法表

# 九九乘法表
    for i in range(1, 10):
        for j in range(1, i+1):
            print('{}x{}={}\t'.format(j, i, i*j), end='')
        print()

![Xnip2021-03-28\_22-20-01][Xnip2021-03-28_22-20-01]

### title-3 ###

定义一个函数，函数的参数是分数，把分数转化成A(2%)B(10%)C(70%)D(15%)E(3%)五个等级

def fun(score):
      if score<60:
        print("E")
      elif score<70:
        print("D")
      elif score<80:
        print("C")
      elif score<90:
        print("B")
      else:
        print("A")
    
    >>> fun(10)
    >>> E
    >>> fun(98)
    >>> A

a=eval(input())
    if a<60:
      print("E")
    elif a<70:
      print("D")
    elif a<80:
      print("C")
    elif a<90:
      print("B")
    else:
      print("A")

a=eval(input())
    if a>=90:
      print("A")
    elif 90>a>=80:
      print("B")
    elif 80>a>=70:
      print("C")
    elif 70>a>=60:
      print("D")
    elif a<60:
      print("E")

## chapter2 ##

1、列表和元组的操作和转换

def listMethod():
        print()
        # 列表
        List = ['北1', '清1', 2021, 2023]
        print(List)
        # 列表索引
        print("list[0]: ", List[0])
        # 列表切片
        print("list[0:2]: ", List[0:2])
        # 列表增加元素
        List.append('三')
        # 列表删除元素
        del List[0]
        # 列表修改元素
        List[0] = '京师大学堂'
        # 列表查询元素
        print(List.index('三'))
        print(List[List.index('三')])
        print()
        # 列表遍历
        for i, value in enumerate(List):
            print(i, value)
        print()
        for i in List:
            print(i)
    
    def tupleMethod():
        print()
        # 元组
        Tuple = ('北1', '清1', 2021, 2023)
        print(Tuple)
        # 元组索引
        print("Tuple[0]: ", Tuple[0])
        # 元组切片
        print("Tuple[0:2]: ", Tuple[0:2])
        print()
        # 元组遍历
        for i, value in enumerate(Tuple):
            print(i, value)
        print()
        for i in Tuple:
            print(i)
    
    def transformation():
        print()
        # 元组
        Tuple = ('北1', '清1', 2021, 2023)
        print(Tuple)
        # 列表
        List = ['北1', '清1', 2021, 2023]
        print(List)
        print()
        # 元组转换成列表
        print(list(Tuple))
        # 列表转换成元组
        print(tuple(List))

2、设计一个Member类，类中含有属性name和age，其中，name为公有属性，age为私有属性，并在构造方法中完成name和age的初始化工作。Member类中含有get\_name和get\_age两个方法，分别返回姓名和年龄信息。设计Student类，继承自Member类，其中Student类拥有的属性score，另有方法get\_info,用来返回学生的姓名、年龄、分数。

class Member:
        def __init__(self, name, age):
            # 初始化
            self.name = name
            self.__age = age
    
        # 返回姓名
        def get_name(self):
            return self.name
    
        # 返回年龄
        def get_age(self):
            return self.__age
    
    
    class Student(Member):
        def __init__(self, name, age, score):
            self.name = name
            self.__age = age
            self.score = score
    
        def get_info(self):
            print('姓名：{0} , 年龄：{1} 岁 , 成绩：{2} 分'.format(self.name, self.__age, self.score))
    
    bob = Student('品多多', 99, 89)
    print(bob.get_info())

## chapter3 ##

鸢尾花数据集

# 导入数据集
        from sklearn.datasets import load_iris
        from sklearn.model_selection import train_test_split
        from sklearn.tree import DecisionTreeClassifier
        # 载入数据集
        iris = load_iris()
        X_train,X_test,Y_train,Y_test = train_test_split(iris.data, iris.target, test_size=50)
        
        dtm = DecisionTreeClassifier(criterion="entropy",max_depth=3)
        dtm.fit(X_train,Y_train)
        
        score = dtm.score(X_test, Y_test)
        print(score)```

[Python]: https://www.runoob.com/python/python-strings.html
[Python count]: https://www.runoob.com/python/att-string-count.html
[Python find]: https://www.runoob.com/python/att-string-find.html
[Python replace]: https://www.runoob.com/python/att-string-replace.html
[Python split]: https://www.runoob.com/python/att-string-split.html
[Xnip2021-03-28_22-20-01]: /images/20221022/c8ce24484606459ba007c722833ff92a.png