python学习笔记二 数据类型（基础篇）

时间：2022-02-25 21:50:39

Python基础

　　　　　　　　　对于Python，一切事物都是对象，对象基于类创建

        python学习笔记二 数据类型（基础篇）

不同类型的类可以创造出字符串，数字，列表这样的对象，比如"koka"、24、['北京', '上海', '深圳']

数据类型

1、如何查找数据类型支持的方法

python终端:

name=”koka“

type(name)

<class 'str'>

help(str) #即可显示所有字符串支持的方法
或者
dir(name) #也可以显示对象中的所有特性。

使用Pycharm：

在py文件中输入int或str，选中输入的关键字，按住Ctrl等鼠标变成手指标识，左键单击即可到你想查找的类方法介绍

选中int后按如下操作可以在pycharm的左侧显示int（object）的方法，方便查看

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*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" alt="" />
整数

加法：x.__add__(y) <==> x+y

>>> x=

>>> y=

>>> x.__add__(y)

>>> x+y

abs : 求绝对值，x.__abs__() <==> abs(x)

>>> x=-

>>> abs(x)

>>> x.__abs__()

divmod：相除，得到商和余数组成的元组 x.__divmod__(y) <==> divmod(x, y) #在网页分页操作中使用。

>>> total =

>>> pager =

>>> total.__divmod__(pager)

(, )
>>> divmod(total,pager)
(9, 5)

字符串

格式化字符串
>>> name = "koka"

>>> print("hello %s" %name)

hello koka
注：%s是字符串，%d是整数， %f是浮点数
字段宽度和精度
>>> '%10f' % pi  #字符宽度 10

'  3.141593'

>>> '%10.2f' % pi #字符宽度10，精度2

'      3.14'

>>> '%.2f' % pi #精度2

'3.14'
可以使用*作为字段宽度或者精度（或者两者都使用*），此时数值会从元组参数中读出：
>>> '%.*s' %(5,'Guido van Rossum')

'Guido'
符号、对齐和0填充
- ： 左对齐
+：在转换值之前加上正负号
""：正数之前保留空格
0 ：转换值若位数不够用0填充
>>> '%010.2f' % pi

'0000003.14'

>>> '%-10.2f' % pi

'3.14
字符串方法：
find  字符串中查找子字符串
>>> 'With a moo-moo here'.find('moo')
join   在队列中添加元素
>>> seq = [1,2,3,4,5]

>>> sep = '+'

>>> sep.join(seq)

Traceback (most recent call last):

  File "<pyshell#26>", line 1, in <module>

    sep.join(seq)

TypeError: sequence item 0: expected str instance, int found

>>> seq = ['1','2','3']

>>> sep = '+'

>>> sep.join(seq)

'1+2+3'
lower 返回小写字母 
print('Hello'.lower())
replace 返回一个字符串中替换后的字符串
name = 'lolo lala lola'

print(name.replace('lolo','koka'))
split      分割字符串成序列
>>> '1+2+3'.split("+")

['1', '2', '3']
strip      返回去除两侧空格（不包括内部）的字符串
>>> '   hahaha   '.strip()

'hahaha'
translate 可以替换字符创中的某些部分，只能处理单个字符

capitalize 首字母变大写

>>> name = "python"

>>> name.capitalize()

'Python'

in or __contain__ 包含

>>> name = "python"

>>> name.capitalize()

'Python'

>>> name.__contains__('th')

True

startswith 和 endswith 以xx开头或xx结尾

>>> name = "Gumby"

>>> name.endswith('Gumby')

True

>>> name = "Mr.Gumby"

>>> name.startswith('Mr.')

True

ljust，center，rjust 左对齐，居中，右对齐

>>> print(''.ljust(35,'='))
===================================
>>> print("Shopping List:".center(35,"*"))
***********Shopping List:**********
>>> print(''.rjust(35,'='))
===================================

count 统计字符出现次数

>>> abc = 'asdadqweqjkhwjgfawgdklawda'

>>> abc.count('a')

>>> abc.count('a',,)

encode 编码

>>> name = "下载"

>>> result = name.encode('gbk')

>>> print(result)

b'\xcf\xc2\xd4\xd8'

format 格式化字符串

>>> s = "i am {0},age {1}"
>>> print(s.format('Tang',18))
i am Tang,age 18

>>> s = 'i am {name},age {age}'
>>> print(s.format(name="Tang",age=18))
i am Tang,age 18

更多字符串format的使用参考：http://blog.csdn.net/handsomekang/article/details/9183303

列表

>>> [0,1,2,3,4,5]

[0, 1, 2, 3, 4, 5]
标准操作：
索引[*]、分片[:](含首不含尾)、+、*、in、max、min、赋值、删除元素
>>> ['th'] * 10

['th', 'th', 'th', 'th', 'th', 'th', 'th', 'th', 'th', 'th']

>>> 0 in [0,1,2,3,4,5]

True

>>> num = [0,1,2,3,4,5]

>>> num[:]

[0, 1, 2, 3, 4, 5]

>>> num[0:3]

[0, 1, 2]
列表的方法：
append       列表最后附加元素
>>> lst = [1,2,3]

>>> lst.append(4)

>>> lst

[1, 2, 3, 4]
extend         列表最后追加另一个列表
>>> a = [1,2,3]

>>> b = [4,5,6]

>>> a.extend(b)

>>> a

[1, 2, 3, 4, 5, 6]
pop             移除列表中的一个值(默认最后)，并返回元素值 
>>> a.pop()
count          统计某元素出现的次数
>>> ['a','b','c','a'].count('a')
index          查找某个值第一个匹配项的索引位置
products = ['Car','Iphone','Coffee','Mac','clothers','Bicyle']

print(products.index('Mac'))
insert          在某元素前插入值
prices = [,,,,,]

prices.insert(,)

print(prices)

[, , , , , , ]
remove       移除某个值在列表的第一个匹配项
>>> li = [11,22,33,44,55]

>>> li.remove(11)

>>> li

[22, 33, 44, 55]
sort            在原序列进行正向排序，意味着改变原来的列表，从而让其中的元素按顺序排列，而不是简单放回一个已排序的副本而已。
>>> x = [1,3,5,2,6,8]

>>> x.sort()

>>> x

[1, 2, 3, 5, 6, 8]
reverse        反序改变序列，不返回值 
>>> x.reverse()

>>> x

[8, 6, 5, 3, 2, 1]
reversed      反向序列并返回一个迭代器
print(list(reversed([,,,,])))

[, , , , ]
sorted         顺序排列，返回一个正向列表
>>> y = sorted(x)

>>> y

[1, 2, 3, 5, 6, 8]
列表转换为字符串
' '.join(list)

元组

元组不可以改变，元组下的元素是可以改变的。

>>> tu.remove(11)
Traceback (most recent call last):
  File "<pyshell#14>", line 1, in <module>
    tu.remove(11)
AttributeError: 'tuple' object has no attribute 'remove'
>>> 
>>> tu = (,[,],"haha",)

>>> tu[][]=

>>> tu

(, [, ], 'haha', )

count 统计出现次数

>>> tu = (,,,)

>>> tu.count()

index 查找元素出现的位置

>>> tu.index()

>>> tu.index()

字典

{'key':'value'}
字典的方法：
clear 清除字典中所有的项，无返回值或返回None

copy 返回一个具有相同键值对的新字典（这个方法实现的是浅复制，因为值本身就是相同，而不是副本。）

>>> x ={'username':'koka','sx':['it','js',12345]}

>>> y = x.copy()

>>> y['username'] = 'akok'

>>> y['sx'].remove('it')

>>> y

{'username': 'akok', 'sx': ['js', 12345]}

>>> x

{'username': 'koka', 'sx': ['js', 12345]}
fromkeys 使用给定的键建立新的字典，每个键默认对应的值为None；可直接调用dict函数 
{}.fromkeys(['name','age'])

{'age':'None','name':'None'}

dict.fromkeys(['name','age'])

{'age':None,'name':None}

get 访问字典项的方法，一般来说访问字典中不存在的项时会出错。

d={}

print(d['name'])

error

print(d.get('name'))

None
has_key （python3.5已经没有该功能） 检查字典中是否含有给出的键。可以使用表达式k in d实现. 
data = {'name':'koka','age':}

if 'name' in data:

    print("in")

else:

    print("not in")
in

items 和 iteritems

items 将所有的字典项以列表方式返回。iteritems 返回一个迭代器。
>>> database={'koka':'123','wawa':'456'}

>>> for key,value in database.items():

    print(key,value)

wawa 456

koka
pop用来获得对应于给定键的值，将这个键-值对从字典中移除。 
data = {'name':'koka','age':}

name = data.pop('name')

print(name)

koka

popitem 类似与list.pop，后者会弹出列表的最后一个元素。popitem弹出随机的项，可一个接一个的移除项。

setdefault类似于get，能够获得与给定键相关联的值，还能在字典中不含有给定键的情况下设定值。

>>> d = {}

>>> d.setdefault('name','N/A')

'N/A'
update 利用一个字典项更新另一个字典。
data = {'name':'koka','age':}

adds = {'phone':}

data.update(adds)

print(data)

{'phone': , 'name': 'koka', 'age': }
keys 返回字典的key值的一个视图（view），而不在是list;iterkeys返回键的迭代器
>>> dct = {'a':1,'b':2}

>>> print(type(dct.keys()))

<class 'dict_keys'>
values 返回字典的value值的一个视图（view），而不在是list;itervalues返回值得迭代器
>>> d={}

>>> d[1]=1

>>> d[2]=2

>>> d[1]=1
>>> d.values()

dict_values([1, 2])
>>> print(type(d.values()))
<class 'dict_values'
格式化字典
>>> phonebook={'tr':'1234'}

>>> print("tr's phone number is %(tr)s." %phonebook)

tr's phone number is 1234.
dict函数
通过其他映射（比如其他字典）或者（键，值）这样的序列对建立字典。
>>> items=[('name','koka'),('age',18)]

>>> d=dict(items)

>>> d['name']

'koka'

dict函数也可以通过关键字参数来创建字典

>>> d = dict(name='koka',age=18)

>>> d

{'name': 'koka', 'age': 18}

练习：元素分类
有如下值集合 [11,22,33,44,55,66,77,88,99,90...]，将所有大于 66 的值保存至字典的第一个key中，将小于 66 的值保存至第二个key的值中。
即： {'k1': 大于66 , 'k2': 小于66}

a = [,,,,,,,,]

b = {}

for item in a:

    if item >= :

        if 'k1' in b:

            b['k1'].append(item)

        else:

            b['k1'] = [item,]

    else:

        if 'k2' in b:

            b['k2'].append(item)

        else:

            b['k2'] = [item,]

print(b)

"""

for i in a:

    if i >=:

        b.setdefault('k1',[]).append(i)

    else:

        b.setdefault('k2',[]).append(i)

print(b)

"""
"""
import collections
values = [11, 22, 33,44,55,66,77,88,99]
newvalues = collections.defaultdict(list)

for i in values:
    if i >= 66:
        newvalues['k1'].append(i)
    else:
        newvalues['k2'].append(i)
print(newvalues)
"""

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