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https://github.com/apachecn/ailearning.git
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1319 lines
31 KiB
Markdown
1319 lines
31 KiB
Markdown
# Python 入门演示
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## 简单的数学运算
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整数相加，得到整数：
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In [1]:
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```py
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2 + 2
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```
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Out[1]:
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```py
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4
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```
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浮点数相加，得到浮点数：
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In [2]:
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```py
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2.0 + 2.5
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```
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Out[2]:
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```py
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4.5
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```
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整数和浮点数相加，得到浮点数：
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In [3]:
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```py
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2 + 2.5
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```
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Out[3]:
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```py
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4.5
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```
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## 变量赋值
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**Python**使用`<变量名>=<表达式>`的方式对变量进行赋值
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In [4]:
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```py
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a = 0.2
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```
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## 字符串 String
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字符串的生成，单引号与双引号是等价的：
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In [5]:
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```py
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s = "hello world"
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s
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```
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Out[5]:
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```py
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'hello world'
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```
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In [6]:
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```py
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s = 'hello world'
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s
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```
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Out[6]:
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```py
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'hello world'
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```
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三引号用来输入包含多行文字的字符串：
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In [7]:
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```py
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s = """hello
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world"""
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print s
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```
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```py
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hello
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world
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```
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In [8]:
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```py
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s = '''hello
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world'''
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print s
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```
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```py
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hello
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world
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```
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字符串的加法：
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In [9]:
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```py
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s = "hello" + " world"
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s
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```
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Out[9]:
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```py
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'hello world'
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```
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字符串索引：
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In [10]:
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```py
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s[0]
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```
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Out[10]:
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```py
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'h'
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```
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In [11]:
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```py
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s[-1]
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```
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Out[11]:
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```py
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'd'
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```
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In [12]:
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```py
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s[0:5]
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```
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Out[12]:
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```py
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'hello'
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```
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字符串的分割：
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In [13]:
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```py
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s = "hello world"
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s.split()
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```
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Out[13]:
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```py
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['hello', 'world']
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```
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查看字符串的长度：
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In [14]:
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```py
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len(s)
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```
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Out[14]:
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```py
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11
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```
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## 列表 List
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Python用`[]`来生成列表
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In [15]:
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```py
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a = [1, 2.0, 'hello', 5 + 1.0]
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a
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```
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Out[15]:
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```py
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[1, 2.0, 'hello', 6.0]
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```
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列表加法：
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In [16]:
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```py
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a + a
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```
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Out[16]:
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```py
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[1, 2.0, 'hello', 6.0, 1, 2.0, 'hello', 6.0]
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```
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列表索引：
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In [17]:
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```py
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a[1]
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```
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Out[17]:
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```py
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2.0
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```
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列表长度：
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In [18]:
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```py
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len(a)
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```
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Out[18]:
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```py
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4
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```
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向列表中添加元素：
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In [19]:
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```py
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a.append("world")
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a
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```
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Out[19]:
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```py
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[1, 2.0, 'hello', 6.0, 'world']
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```
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## 集合 Set
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Python用{}来生成集合，集合中不含有相同元素。
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In [20]:
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```py
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s = {2, 3, 4, 2}
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s
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```
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Out[20]:
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```py
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{2, 3, 4}
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```
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集合的长度：
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In [21]:
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```py
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len(s)
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```
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Out[21]:
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```py
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3
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```
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向集合中添加元素：
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In [22]:
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```py
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s.add(1)
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s
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```
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Out[22]:
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```py
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{1, 2, 3, 4}
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```
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集合的交：
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In [23]:
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```py
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a = {1, 2, 3, 4}
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b = {2, 3, 4, 5}
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a & b
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```
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Out[23]:
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```py
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{2, 3, 4}
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```
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并：
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In [24]:
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```py
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a | b
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```
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Out[24]:
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```py
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{1, 2, 3, 4, 5}
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```
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差：
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In [25]:
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```py
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a - b
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```
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Out[25]:
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```py
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{1}
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```
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对称差：
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In [26]:
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```py
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a ^ b
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```
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Out[26]:
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```py
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{1, 5}
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```
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## 字典 Dictionary
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Python用`{key:value}`来生成Dictionary。
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In [27]:
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```py
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d = {'dogs':5, 'cats':4}
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d
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```
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Out[27]:
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```py
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{'cats': 4, 'dogs': 5}
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```
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字典的大小
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In [28]:
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```py
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len(d)
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```
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Out[28]:
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```py
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2
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```
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查看字典某个键对应的值：
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In [29]:
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```py
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d["dogs"]
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```
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Out[29]:
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```py
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5
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```
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修改键值：
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In [30]:
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```py
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d["dogs"] = 2
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d
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```
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Out[30]:
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```py
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{'cats': 4, 'dogs': 2}
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```
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插入键值：
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In [31]:
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```py
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d["pigs"] = 7
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d
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```
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Out[31]:
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```py
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{'cats': 4, 'dogs': 2, 'pigs': 7}
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```
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所有的键：
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In [32]:
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```py
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d.keys()
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```
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Out[32]:
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```py
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['cats', 'dogs', 'pigs']
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```
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所有的值：
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In [33]:
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```py
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d.values()
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```
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Out[33]:
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```py
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[4, 2, 7]
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```
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所有的键值对：
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In [34]:
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```py
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d.items()
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```
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Out[34]:
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```py
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[('cats', 4), ('dogs', 2), ('pigs', 7)]
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```
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## 数组 Numpy Arrays
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需要先导入需要的包，Numpy数组可以进行很多列表不能进行的运算。
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In [35]:
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```py
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from numpy import array
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a = array([1, 2, 3, 4])
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a
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```
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Out[35]:
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```py
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array([1, 2, 3, 4])
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```
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加法：
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In [36]:
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```py
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a + 2
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```
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Out[36]:
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```py
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array([3, 4, 5, 6])
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```
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In [37]:
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```py
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a + a
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```
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Out[37]:
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```py
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array([2, 4, 6, 8])
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```
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## 画图 Plot
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Python提供了一个很像MATLAB的绘图接口。
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In [38]:
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```py
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%matplotlib inline
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from matplotlib.pyplot import plot
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plot(a, a**2)
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```
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Out[38]:
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```py
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[<matplotlib.lines.Line2D at 0x9fb6fd0>]
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```
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## 循环 Loop
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In [39]:
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```py
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line = '1 2 3 4 5'
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fields = line.split()
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fields
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```
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Out[39]:
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```py
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['1', '2', '3', '4', '5']
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```
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In [40]:
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```py
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total = 0
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for field in fields:
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total += int(field)
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total
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```
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Out[40]:
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```py
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15
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```
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Python中有一种叫做列表推导式(List comprehension)的用法：
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In [41]:
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```py
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numbers = [int(field) for field in fields]
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numbers
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```
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Out[41]:
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```py
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[1, 2, 3, 4, 5]
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```
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In [42]:
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```py
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sum(numbers)
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```
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Out[42]:
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```py
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15
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```
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写在一行：
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In [43]:
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```py
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sum([int(field) for field in line.split()])
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```
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Out[43]:
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```py
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15
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```
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## 文件操作 File IO
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In [44]:
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```py
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cd ~
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```
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```py
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d:\Users\lijin
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```
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写文件：
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In [45]:
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```py
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f = open('data.txt', 'w')
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f.write('1 2 3 4\n')
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f.write('2 3 4 5\n')
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f.close()
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```
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读文件：
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In [46]:
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```py
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f = open('data.txt')
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data = []
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for line in f:
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data.append([int(field) for field in line.split()])
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f.close()
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data
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```
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Out[46]:
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```py
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[[1, 2, 3, 4], [2, 3, 4, 5]]
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```
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|
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In [47]:
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```py
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for row in data:
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print row
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```
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```py
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[1, 2, 3, 4]
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[2, 3, 4, 5]
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```
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删除文件：
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In [48]:
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```py
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import os
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os.remove('data.txt')
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```
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## 函数 Function
|
||
|
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Python用关键词`def`来定义函数。
|
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|
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In [49]:
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```py
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def poly(x, a, b, c):
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y = a * x ** 2 + b * x + c
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return y
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x = 1
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poly(x, 1, 2, 3)
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```
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Out[49]:
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||
|
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```py
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6
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```
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|
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用Numpy数组做参数x：
|
||
|
||
In [50]:
|
||
|
||
```py
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x = array([1, 2, 3])
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poly(x, 1, 2, 3)
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|
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```
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Out[50]:
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|
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```py
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array([ 6, 11, 18])
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```
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可以在定义时指定参数的默认值：
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|
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In [51]:
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|
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```py
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from numpy import arange
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def poly(x, a = 1, b = 2, c = 3):
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y = a*x**2 + b*x + c
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return y
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|
||
x = arange(10)
|
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x
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array([0, 1, 2, 3, 4, 5, 6, 7, 8, 9])
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|
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```
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Out[51]:
|
||
|
||
```py
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array([0, 1, 2, 3, 4, 5, 6, 7, 8, 9])
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```
|
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|
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In [52]:
|
||
|
||
```py
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||
poly(x)
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||
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||
```
|
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||
Out[52]:
|
||
|
||
```py
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||
array([ 3, 6, 11, 18, 27, 38, 51, 66, 83, 102])
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||
```
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|
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In [53]:
|
||
|
||
```py
|
||
poly(x, b = 1)
|
||
|
||
```
|
||
|
||
Out[53]:
|
||
|
||
```py
|
||
array([ 3, 5, 9, 15, 23, 33, 45, 59, 75, 93])
|
||
```
|
||
|
||
## 模块 Module
|
||
|
||
Python中使用`import`关键词来导入模块。
|
||
|
||
In [54]:
|
||
|
||
```py
|
||
import os
|
||
|
||
```
|
||
|
||
当前进程号：
|
||
|
||
In [55]:
|
||
|
||
```py
|
||
os.getpid()
|
||
|
||
```
|
||
|
||
Out[55]:
|
||
|
||
```py
|
||
4400
|
||
```
|
||
|
||
系统分隔符：
|
||
|
||
In [56]:
|
||
|
||
```py
|
||
os.sep
|
||
|
||
```
|
||
|
||
Out[56]:
|
||
|
||
```py
|
||
'\\'
|
||
```
|
||
|
||
## - 类 Class
|
||
|
||
用`class`来定义一个类。 `Person(object)`表示继承自`object`类； `__init__`函数用来初始化对象； `self`表示对象自身，类似于`C` `Java`里面`this`。
|
||
|
||
In [57]:
|
||
|
||
```py
|
||
class Person(object):
|
||
def __init__(self, first, last, age):
|
||
self.first = first
|
||
self.last = last
|
||
self.age = age
|
||
def full_name(self):
|
||
return self.first + ' ' + self.last
|
||
|
||
```
|
||
|
||
构建新对象：
|
||
|
||
In [58]:
|
||
|
||
```py
|
||
person = Person('Mertle', 'Sedgewick', 52)
|
||
|
||
```
|
||
|
||
调用对象的属性：
|
||
|
||
In [59]:
|
||
|
||
```py
|
||
person.first
|
||
|
||
```
|
||
|
||
Out[59]:
|
||
|
||
```py
|
||
'Mertle'
|
||
```
|
||
|
||
调用对象的方法：
|
||
|
||
In [60]:
|
||
|
||
```py
|
||
person.full_name()
|
||
|
||
```
|
||
|
||
Out[60]:
|
||
|
||
```py
|
||
'Mertle Sedgewick'
|
||
```
|
||
|
||
修改对象的属性：
|
||
|
||
In [61]:
|
||
|
||
```py
|
||
person.last = 'Smith'
|
||
|
||
```
|
||
|
||
添加新属性，d是之前定义的字典：
|
||
|
||
In [62]:
|
||
|
||
```py
|
||
person.critters = d
|
||
person.critters
|
||
|
||
```
|
||
|
||
Out[62]:
|
||
|
||
```py
|
||
{'cats': 4, 'dogs': 2, 'pigs': 7}
|
||
```
|
||
|
||
## 网络数据 Data from Web
|
||
|
||
In [63]:
|
||
|
||
```py
|
||
url = 'http://ichart.finance.yahoo.com/table.csv?s=GE&d=10&e=5&f=2013&g=d&a=0&b=2&c=1962&ignore=.csv'
|
||
|
||
```
|
||
|
||
处理后就相当于一个可读文件：
|
||
|
||
In [64]:
|
||
|
||
```py
|
||
import urllib2
|
||
ge_csv = urllib2.urlopen(url)
|
||
data = []
|
||
for line in ge_csv:
|
||
data.append(line.split(','))
|
||
data[:4]
|
||
|
||
```
|
||
|
||
Out[64]:
|
||
|
||
```py
|
||
[['Date', 'Open', 'High', 'Low', 'Close', 'Volume', 'Adj Close\n'],
|
||
['2013-11-05', '26.32', '26.52', '26.26', '26.42', '24897500', '24.872115\n'],
|
||
['2013-11-04',
|
||
'26.59',
|
||
'26.59',
|
||
'26.309999',
|
||
'26.43',
|
||
'28166100',
|
||
'24.88153\n'],
|
||
['2013-11-01',
|
||
'26.049999',
|
||
'26.639999',
|
||
'26.030001',
|
||
'26.540001',
|
||
'55634500',
|
||
'24.985086\n']]
|
||
```
|
||
|
||
使用`pandas`处理数据：
|
||
|
||
In [65]:
|
||
|
||
```py
|
||
ge_csv = urllib2.urlopen(url)
|
||
import pandas
|
||
ge = pandas.read_csv(ge_csv, index_col=0, parse_dates=True)
|
||
ge.plot(y='Adj Close')
|
||
|
||
```
|
||
|
||
Out[65]:
|
||
|
||
```py
|
||
<matplotlib.axes._subplots.AxesSubplot at 0xc2e3198>
|
||
```
|
||
|
||
 |