# 2.1 数据类型和数据结构

### 原始数据类型

Python 有一些原始数据类型：

• 整数
• 浮点数
• 字符串（文本）

### 空类型

email_address = None


None 常用作可选值或缺失值的占位符。它在条件语句中计算为 False

if email_address:


### 数据结构

100 shares of GOOG at \$490.10


• 股票的名称或符号（"GOOG"，字符串）
• 股份数目（100，整数）
• 价格（490.10，浮点数）

### 元组

s = ('GOOG', 100, 490.1)


s = 'GOOG', 100, 490.1


t = ()            # An empty tuple
w = ('GOOG', )    # A 1-item tuple


s = ('GOOG', 100, 490.1)
name = s[0]                 # 'GOOG'
shares = s[1]               # 100
price = s[2]                # 490.1


>>> s[1] = 75
TypeError: object does not support item assignment


s = (s[0], 75, s[2])


### 元组打包

s = ('GOOG', 100, 490.1)


### 元组拆包

name, shares, price = s
print('Cost', shares * price)


name, shares = s     # ERROR
Traceback (most recent call last):
...
ValueError: too many values to unpack


### 元组与列表

record = ('GOOG', 100, 490.1)       # A tuple representing a record in a portfolio

symbols = [ 'GOOG', 'AAPL', 'IBM' ]  # A List representing three stock symbols


### 字典

s = {
'name': 'GOOG',
'shares': 100,
'price': 490.1
}


### 常见操作

>>> print(s['name'], s['shares'])
GOOG 100
>>> s['price']
490.10
>>>


>>> s['shares'] = 75
>>> s['date'] = '6/6/2007'
>>>


>>> del s['date']
>>>


### 为什么使用字典？

s['price']
# vs
s[2]


## 练习

>>> import csv
>>> f = open('Data/portfolio.csv')
>>> next(rows)
['name', 'shares', 'price']
>>> row = next(rows)
>>> row
['AA', '100', '32.20']
>>>


>>> row = ['AA', '100', '32.20']
>>> cost = row[1] * row[2]
Traceback (most recent call last):
File "<stdin>", line 1, in <module>
TypeError: can't multiply sequence by non-int of type 'str'
>>>


### 练习 2.1：元组

>>> t = (row[0], int(row[1]), float(row[2]))
>>> t
('AA', 100, 32.2)
>>>


>>> cost = t[1] * t[2]
>>> cost
3220.0000000000005
>>>


>>> print(f'{cost:0.2f}')
3220.00
>>>


>>> t[1] = 75
Traceback (most recent call last):
File "<stdin>", line 1, in <module>
TypeError: 'tuple' object does not support item assignment
>>>


>>> t = (t[0], 75, t[2])
>>> t
('AA', 75, 32.2)
>>>


>>> name, shares, price = t
>>> name
'AA'
>>> shares
75
>>> price
32.2
>>>


>>> t = (name, 2*shares, price)
>>> t
('AA', 150, 32.2)
>>>


### 练习 2.2：把字典当作数据结构

>>> d = {
'name' : row[0],
'shares' : int(row[1]),
'price'  : float(row[2])
}
>>> d
{'name': 'AA', 'shares': 100, 'price': 32.2 }
>>>


>>> cost = d['shares'] * d['price']
>>> cost
3220.0000000000005
>>>


>>> d['shares'] = 75
>>> d
{'name': 'AA', 'shares': 75, 'price': 32.2 }
>>>


>>> d['date'] = (6, 11, 2007)
>>> d['account'] = 12345
>>> d
{'name': 'AA', 'shares': 75, 'price':32.2, 'date': (6, 11, 2007), 'account': 12345}
>>>


### 练习 2.3: 字典的其它操作

>>> list(d)
['name', 'shares', 'price', 'date', 'account']
>>>


>>> for k in d:
print('k =', k)

k = name
k = shares
k = price
k = date
k = account
>>>


>>> for k in d:
print(k, '=', d[k])

name = AA
shares = 75
price = 32.2
date = (6, 11, 2007)
account = 12345
>>>


>>> keys = d.keys()
>>> keys
dict_keys(['name', 'shares', 'price', 'date', 'account'])
>>>


>>> del d['account']
>>> keys
dict_keys(['name', 'shares', 'price', 'date'])
>>>


>>> items = d.items()
>>> items
dict_items([('name', 'AA'), ('shares', 75), ('price', 32.2), ('date', (6, 11, 2007))])
>>> for k, v in d.items():
print(k, '=', v)

name = AA
shares = 75
price = 32.2
date = (6, 11, 2007)
>>>


>>> items
dict_items([('name', 'AA'), ('shares', 75), ('price', 32.2), ('date', (6, 11, 2007))])
>>> d = dict(items)
>>> d
{'name': 'AA', 'shares': 75, 'price':32.2, 'date': (6, 11, 2007)}
>>>

posted @ 2021-02-20 22:02  codists  阅读(161)  评论(0编辑  收藏  举报