python for data analysis 2nd 读书笔记（一）

第一章相对简单，也么有什么需要记录的内容，主要用到的工具的简介及环境配置，粗略的过一下就行了。下面我们开始第二章的学习

CHAPTER 2
2.2Python Language Basics, IPython, and Jupyter Notebooks

when you first meet the python ,you may be confuse by

In [6]: data = {i : np.random.randn() for i in range(7)}

In [7]: data
Out[7]:
{0: -0.20470765948471295,
 1: 0.47894333805754824,
 2: -0.5194387150567381,
 3: -0.55573030434749,
 4: 1.9657805725027142,
 5: 1.3934058329729904,
 6: 0.09290787674371767}

While entering expressions in the shell, pressing the Tab key will search the namespace for any variables (objects,functions, etc.) matching the characters you have typed so far:

In [1]: an_apple = 27

In [2]: an_example = 42

In [3]: an<Tab>
an_apple    and         an_example  any

the 'tab' is very useful ,when you use Ipython or Jupyter,also pycharm, it can compliment your order

Introspection
Using a question mark (?) before or after a variable will display some general infor‐
mation about the object:

In [8]: b = [1, 2, 3]

In [9]: b?
Type:       list
String Form:[1, 2, 3]
Length:     3
Docstring:

In [10]: print?
Docstring:
print(value, ..., sep=' ', end='\n', file=sys.stdout, flush=False)

Prints the values to a stream, or to sys.stdout by default.
Optional keyword arguments:
file:  a file-like object (stream); defaults to the current sys.stdout.
sep:   string inserted between values, default a space.
end:   string appended after the last value, default a newline.
flush: whether to forcibly flush the stream.
Type:      builtin_function_or_method

def add_numbers(a, b):
    """
    Add two numbers together

Returns
    -------
    the_sum : type of arguments
    """
    return a + b
Then using ? shows us the docstring:
In [11]: add_numbers?
Signature: add_numbers(a, b)
Docstring:
Add two numbers together

Returns
-------
the_sum : type of arguments
File:      <ipython-input-9-6a548a216e27>
Type:      function
Using ?? will also show the function’s source code if possible:
In [12]: add_numbers??
Signature: add_numbers(a, b)
Source:
def add_numbers(a, b):
    """
    Add two numbers together

Returns
    -------
    the_sum : type of arguments
    """
    return a + b
File:      <ipython-input-9-6a548a216e27>
Type:      function

you also can use  wildcard (*)  tomatching the expression

In [13]: np.*load*?
np.__loader__
np.load
np.loads
np.loadtxt
np.pkgload

The %run Command

You can run any file as a Python program inside the environment of your IPython
session using the %run command.

In the Jupyter notebook, you may also use the related %load magic function, which
imports a script into a code cell

Executing Code from the Clipboard

In [17]: %paste

Standard IPython keyboard shortcuts  Keyboard shortcut Description
Ctrl-P or up-arrow Search backward in command history for commands starting with currently entered text
Ctrl-N or down-arrow Search forward in command history for commands starting with currently entered text
Ctrl-R Readline-style reverse history search (partial matching)
Ctrl-Shift-V Paste text from clipboard
Ctrl-C Interrupt currently executing code
Ctrl-A Move cursor to beginning of line
Ctrl-E Move cursor to end of line
Ctrl-K Delete text from cursor until end of line
Ctrl-U Discard all text on current line
Ctrl-F Move cursor forward one character
Ctrl-B Move cursor back one character
Ctrl-L Clear screen

About Magic Commands

IPython’s special commands (which are not built into Python itself) are known as“magic” commands. These are designed to facilitate common tasks and enable you to easily control the behavior of the IPython system.

In [20]: a = np.random.randn(100, 100)
In [20]: %timeit np.dot(a, a)
10000 loops, best of 3: 20.9 µs per loop

In [21]: %debug?
Docstring:
::

%debug [--breakpoint FILE:LINE] [statement [statement ...]]

Activate the interactive debugger.

In [22]: %pwd
Out[22]: '/home/wesm/code/pydata-book

Table 2-2. Some frequently used IPython magic commands Command Description
%quickref Display the IPython Quick Reference Card
%magic Display detailed documentation for all of the available magic commands
%debug Enter the interactive debugger at the bottom of the last exception traceback
%hist Print command input (and optionally output) history
%pdb Automatically enter debugger after any exception
%paste Execute preformatted Python code from clipboard
%cpaste Open a special prompt for manually pasting Python code to be executed
%reset Delete all variables/names defined in interactive namespace
%page OBJECT Pretty-print the object and display it through a pager
%run script.py Run a Python script inside IPython
%prun statement Execute statement with cProfile and report the profiler output
%time statement Report the execution time of a single statement
%timeit statement Run a statement multiple times to compute an ensemble average execution time; useful for timing code with very short execution time
%who, %who_ls, %whos Display variables defined in interactive namespace, with varying levels of information/verbosity
%xdel variable Delete a variable and attempt to clear any references to the object in the IPython internals

Matplotlib Integration

In the IPython shell
In [26]: %matplotlib
Using matplotlib backend: Qt4Agg
In Jupyter, the command is a little different 
In [26]: %matplotlib inline

2.3 Python Language Basics

so easy,something about the grammar of python

if not isinstance(x, list) and isiterable(x):
　　x = list(x)

Check if the object is a list (or a NumPy array) and, if it is not, convert it to be

Table 2-3. Binary operators  Operation Description
a + b Add a and b
a - b Subtract b from a
a * b Multiply a by b
a / b Divide a by b
a // b Floor-divide a by b, dropping any fractional remainder
a ** b Raise a to the b power
a & b True if both a and b are True; for integers, take the bitwise AND
a | b True if either a or b is True; for integers, take the bitwise OR
a ^ b For booleans, True if a or b is True, but not both; for integers, take the bitwise EXCLUSIVE-OR

a == b True if a equals b
a != b True if a is not equal to b
a <= b, a < b True if a is less than (less than or equal) to b
a > b, a >= b True if a is greater than (greater than or equal) to b
a is b True if a and b reference the same Python object
a is not b True if a and b reference different Python objects

Most objects in Python, such as lists, dicts, NumPy arrays, and most user-defined types (classes), are mutable.

Others, like strings and tuples, are immutable

Datetime format specification (ISO C89 compatible)
Type Description
%Y Four-digit year
%y Two-digit year

Type Description
%m Two-digit month [01, 12]
%d Two-digit day [01, 31]
%H Hour (24-hour clock) [00, 23]
%I Hour (12-hour clock) [01, 12]
%M Two-digit minute [00, 59]
%S Second [00, 61] (seconds 60, 61 account for leap seconds)
%w Weekday as integer [0 (Sunday), 6]
%U Week number of the year [00, 53]; Sunday is considered the first day of the week, and days before the first Sunday of the year are “week 0”
%W Week number of the year [00, 53]; Monday is considered the first day of the week, and days before the first Monday of the year are “week 0”
%z UTC time zone offset as +HHMM or -HHMM; empty if time zone naive
%F Shortcut for %Y-%m-%d (e.g., 2012-4-18)
%D Shortcut for %m/%d/%y (e.g., 04/18/12)