数据分析交互工具--使用jupyter

一、启动程序

执行以下命令：

jupyter notebook

[NotebookApp] Serving notebooks from local directory: /home/nanfengpo

[NotebookApp] 0 active kernels

[NotebookApp] The IPython Notebook is running at: http://localhost:8888/

[NotebookApp] Use Control-C to stop this server and shut down all kernels (twice to skip confirmation).

注意以下几点：

• 打开地址为当前bash的目录，默认的根目录
• 浏览器地址为http://localhost:8888/
• 通过control -C终止jupyter程序

几个基本操作：

• 双击D：删除当前cell
• 单击M：转为markdown文档
• markdown文档下运行变为预览模式

二、IPython的帮助文档

1. 使用help()

通过以下命令来获得帮助文档：

help(len)

Help on built-in function len in module builtins:

len(obj, /)
Return the number of items in a container.

help(len)

Help on built-in function len in module builtins:

len(obj, /)
    Return the number of items in a container.

len([1,2,3])

help(list)

Help on class list in module builtins:

class list(object)
 |  list() -> new empty list
 |  list(iterable) -> new list initialized from iterable's items
 |  
 |  Methods defined here:
 |  
 |  __add__(self, value, /)
 |      Return self+value.
 |  
 |  __contains__(self, key, /)
 |      Return key in self.
 |  
 |  __delitem__(self, key, /)
 |      Delete self[key].
 |  
 |  __eq__(self, value, /)
 |      Return self==value.
 |  
 |  __ge__(self, value, /)
 |      Return self>=value.
 |  
 |  __getattribute__(self, name, /)
 |      Return getattr(self, name).
 |  
 |  __getitem__(...)
 |      x.__getitem__(y) <==> x[y]
 |  
 |  __gt__(self, value, /)
 |      Return self>value.
 |  
 |  __iadd__(self, value, /)
 |      Implement self+=value.
 |  
 |  __imul__(self, value, /)
 |      Implement self*=value.
 |  
 |  __init__(self, /, *args, **kwargs)
 |      Initialize self.  See help(type(self)) for accurate signature.
 |  
 |  __iter__(self, /)
 |      Implement iter(self).
 |  
 |  __le__(self, value, /)
 |      Return self<=value.
 |  
 |  __len__(self, /)
 |      Return len(self).
 |  
 |  __lt__(self, value, /)
 |      Return self<value.
 |  
 |  __mul__(self, value, /)
 |      Return self*value.n
 |  
 |  __ne__(self, value, /)
 |      Return self!=value.
 |  
 |  __new__(*args, **kwargs) from builtins.type
 |      Create and return a new object.  See help(type) for accurate signature.
 |  
 |  __repr__(self, /)
 |      Return repr(self).
 |  
 |  __reversed__(...)
 |      L.__reversed__() -- return a reverse iterator over the list
 |  
 |  __rmul__(self, value, /)
 |      Return self*value.
 |  
 |  __setitem__(self, key, value, /)
 |      Set self[key] to value.
 |  
 |  __sizeof__(...)
 |      L.__sizeof__() -- size of L in memory, in bytes
 |  
 |  append(...)
 |      L.append(object) -> None -- append object to end
 |  
 |  clear(...)
 |      L.clear() -> None -- remove all items from L
 |  
 |  copy(...)
 |      L.copy() -> list -- a shallow copy of L
 |  
 |  count(...)
 |      L.count(value) -> integer -- return number of occurrences of value
 |  
 |  extend(...)
 |      L.extend(iterable) -> None -- extend list by appending elements from the iterable
 |  
 |  index(...)
 |      L.index(value, [start, [stop]]) -> integer -- return first index of value.
 |      Raises ValueError if the value is not present.
 |  
 |  insert(...)
 |      L.insert(index, object) -- insert object before index
 |  
 |  pop(...)
 |      L.pop([index]) -> item -- remove and return item at index (default last).
 |      Raises IndexError if list is empty or index is out of range.
 |  
 |  remove(...)
 |      L.remove(value) -> None -- remove first occurrence of value.
 |      Raises ValueError if the value is not present.
 |  
 |  reverse(...)
 |      L.reverse() -- reverse *IN PLACE*
 |  
 |  sort(...)
 |      L.sort(key=None, reverse=False) -> None -- stable sort *IN PLACE*
 |  
 |  ----------------------------------------------------------------------
 |  Data and other attributes defined here:
 |  
 |  __hash__ = None

2. 使用?

或者使用问号：

len?

还可以应用到自定义的变量和自定义的函数上来返回帮助文档

此外，使用两个??可以把函数的源代码显示出来

len??

#上面插入一行
#Jupyter ,代码可以时时进行，没有先后行数的概念
square(101)

10201

square?

square??

#随意定义一个方法
def square(num):
    '''
    该方法，返回数字的平方
    '''
    ret = num*num
    return ret

3. tab自动补全

敲击tab键能自动补全

L.

也可以在import的时候自动补全

import nu

import numpy as np
import time as time

三、IPython魔法命令

1. 运行外部Python文件

使用下面命令运行外部python文件（默认是当前目录，最好加上绝对路径）

%run *.py

例如在当前目录下有一个myscript.py文件：

def square(x):
"""square a number"""
return x ** 2

for N in range(1, 4):
print(N, "squared is", square(N))

我们可以通过下面命令执行它：

%run myscript.py

尤其要注意的是，当我们使用魔法命令执行了一个外部文件时，该文件的函数就能在当前会话中使用

square(5)

#魔法指令，可以拓展我们的Jupyter ，更加强大
#魔法指令，%开头

%run '/home/nanfengpo/Desktop/test.py'

4950

#调用外部文件中定义的方法
calc_sum(1024)

523776

2. 运行计时

用下面命令计算statement的运行时间：

%time statement

#below 下面，自动向下插入一行
%time calc_sum(1024)

CPU times: user 0 ns, sys: 0 ns, total: 0 ns
Wall time: 97.8 µs

523776

用下面命令计算statement的平均运行时间：

%timeit statement

timeit会多次运行statement，最后得到一个更为精准的预期运行时间

#cell 单元前面
%timeit calc_sum(2048)

111 µs ± 7.18 µs per loop (mean ± std. dev. of 7 runs, 10000 loops each)

可以使用两个百分号来测试多行代码的平均运行时间：

`
%%timeit

statement1

statement2

statement3

`

记住：

• %time一般用于耗时长的代码段
• %timeit一般用于耗时短的代码段

%%timeit
calc_sum(1024)
calc_sum(512)
square(100000)

80 µs ± 1.98 µs per loop (mean ± std. dev. of 7 runs, 10000 loops each)

3. 查看当前会话中的所有变量与函数

快速查看当前会话的所有变量与函数名称：

%who

%who

calc_sum	 np	 square	 time	 

查看当前会话的所有变量与函数名称的详细信息：

%whos

a = 1024

%whos

Variable   Type        Data/Info
--------------------------------
a          int         1024
calc_sum   function    <function calc_sum at 0x7f7458114b70>
np         module      <module 'numpy' from '/us<...>kages/numpy/__init__.py'>
square     function    <function square at 0x7f747074b950>
time       module      <module 'time' (built-in)>

返回一个字符串列表，里面元素是当前会话的所有变量与函数名称：

%who_ls

#above
len(ls)

5

ls = %who_ls

4. 执行Linux指令

Linux指令：

$ echo "hello world" # echo is like Python's print function
hello world

$ pwd # pwd = print working directory
/home/jake # this is the "path" that we're sitting in

$ ls # ls = list working directory contents
notebooks projects

$ mkdir mm
/home/jake/projects

$touch txt
!touch /home/nanfengpo/Desktop/xx/hello.txt

在Linux指令之前加上 !，即可在ipython当中执行Linux指令。

注意会将标准输出以字符串形式返回

!cd ..

!pwd

/home/nanfengpo/Documents/data_analysis/1-IPython/softpo

!touch '/home/nanfengpo/Desktop/softpo/python.word'

!mkdir '/home/nanfengpo/Desktop/softpo'

!ls

IPython.ipynb  test.ipynb

!pwd

/home/nanfengpo/Documents/data_analysis/1-IPython/softpo

!echo 'hello'

hello

5. 更多魔法命令

列出所有魔法命令

lsmagic

查看魔法命令的文档:
使用?

%lsmagic

Available line magics:
%alias  %alias_magic  %autocall  %automagic  %autosave  %bookmark  %cat  %cd  %clear  %colors  %config  %connect_info  %cp  %debug  %dhist  %dirs  %doctest_mode  %ed  %edit  %env  %gui  %hist  %history  %killbgscripts  %ldir  %less  %lf  %lk  %ll  %load  %load_ext  %loadpy  %logoff  %logon  %logstart  %logstate  %logstop  %ls  %lsmagic  %lx  %macro  %magic  %man  %matplotlib  %mkdir  %more  %mv  %notebook  %page  %pastebin  %pdb  %pdef  %pdoc  %pfile  %pinfo  %pinfo2  %popd  %pprint  %precision  %profile  %prun  %psearch  %psource  %pushd  %pwd  %pycat  %pylab  %qtconsole  %quickref  %recall  %rehashx  %reload_ext  %rep  %rerun  %reset  %reset_selective  %rm  %rmdir  %run  %save  %sc  %set_env  %store  %sx  %system  %tb  %time  %timeit  %unalias  %unload_ext  %who  %who_ls  %whos  %xdel  %xmode

Available cell magics:
%%!  %%HTML  %%SVG  %%bash  %%capture  %%debug  %%file  %%html  %%javascript  %%js  %%latex  %%markdown  %%perl  %%prun  %%pypy  %%python  %%python2  %%python3  %%ruby  %%script  %%sh  %%svg  %%sx  %%system  %%time  %%timeit  %%writefile

Automagic is ON, % prefix IS NOT needed for line magics.

lsmagic

Available line magics:
%alias  %alias_magic  %autocall  %automagic  %autosave  %bookmark  %cat  %cd  %clear  %colors  %config  %connect_info  %cp  %debug  %dhist  %dirs  %doctest_mode  %ed  %edit  %env  %gui  %hist  %history  %killbgscripts  %ldir  %less  %lf  %lk  %ll  %load  %load_ext  %loadpy  %logoff  %logon  %logstart  %logstate  %logstop  %ls  %lsmagic  %lx  %macro  %magic  %man  %matplotlib  %mkdir  %more  %mv  %notebook  %page  %pastebin  %pdb  %pdef  %pdoc  %pfile  %pinfo  %pinfo2  %popd  %pprint  %precision  %profile  %prun  %psearch  %psource  %pushd  %pwd  %pycat  %pylab  %qtconsole  %quickref  %recall  %rehashx  %reload_ext  %rep  %rerun  %reset  %reset_selective  %rm  %rmdir  %run  %save  %sc  %set_env  %store  %sx  %system  %tb  %time  %timeit  %unalias  %unload_ext  %who  %who_ls  %whos  %xdel  %xmode

Available cell magics:
%%!  %%HTML  %%SVG  %%bash  %%capture  %%debug  %%file  %%html  %%javascript  %%js  %%latex  %%markdown  %%perl  %%prun  %%pypy  %%python  %%python2  %%python3  %%ruby  %%script  %%sh  %%svg  %%sx  %%system  %%time  %%timeit  %%writefile

Automagic is ON, % prefix IS NOT needed for line magics.

四、notebook的快捷键

1、命令模式

• Enter : 转入编辑模式 
• Shift-Enter : 运行本单元，选中下个单元
• Ctrl-Enter : 运行本单元，选中下个单元
• Alt-Enter : 运行本单元，在下面插入一单元

• Y : 单元转入代码状态
• M :单元转入markdown状态

• A : 在上方插入新单元
• B : 在下方插入新单元

2、编辑模式 ( Enter 键启动)

• Tab : 代码补全或缩进
• Shift-Tab : 提示

print('hello')

hello

• Ctrl-A : 全选
• Ctrl-Z : 复原

============================================

练习：

在Jupyter上实现以前的代码，包括：

• 简单代码
• 分支
• 循环
• 函数
• 类

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