Sets
Setsarecollections that have no duplicate elements. While you can use them for set theory operations, in practice they often help you to get the unique values of a list or a tuple. You create sets by using curly braces:
{element1,element2,}
To get the unique objects in a list or a tuple, usethe setconstructor like so:
In[79]:set(["USD","USD","SGD","EUR","USD","EUR"])Out[79]: {'EUR', 'SGD', 'USD'}

Code Blocks and the pass Statement
A code blockdefinesa section in your source code that is used for something special. For example, you use a code block to define the lines over which your program is looping or it makes up the definition of a function. In Python, you define code blocks by indenting them, not by using keywords like in VBA or curly braces like in most other languages. This is referred toas significant white space.

The for and while Loops
Ifyou need to do something repeatedly like printing the value of ten different variables, you are doing yourself a big favor by not copy/pasting the print statement ten times. Instead, use a forloop to do the work for you. forloops iterate over the items of a sequence like a list, a tuple, or a string (remember, strings are sequences of characters). As an introductory example, let’s create a forloop that takes each element of the currencieslist, assigns it to the variable currencyand prints it—one after another until there are no moreelements in the list:
In[89]:currencies=["USD","HKD","AUD"]forcurrencyincurrencies:print(currency)USD
HKD
AUD
As a side note, VBA’s For Eachstatement is close to how Python’s forloop works. The previous example could be written like this in VBA:
DimcurrenciesAsVariantDimcurrAsVariant'currency is a reserved word in VBAcurrencies=Array("USD","HKD","AUD")ForEachcurrIncurrenciesDebugPrintcurrNext
In Python, if you need a counter variable in a forloop, the rangeor enumeratebuilt-ins can help you with that. Let’s first look at range, which provides a sequence of numbers: you call it by either providing a single stopargument or by providing a startand stopargument, with an optional stepargument. Like with slicing, startis inclusive, stopis exclusive, and stepdetermines the step size, with 1being the default:
range(stop)range(start,stop,step)
rangeevaluates lazily, which means that without explicitly asking for it, you won’t see the sequence it generates:
In[90]:range(5)Out[90]: range(0, 5)
Converting the range to a list solves this issue:
In[91]:list(range(5))# stop argumentOut[91]: [0, 1, 2, 3, 4]In[92]:list(range(2,5,2))# start, stop, step argumentsOut[92]: [2, 4]
Most of the time, there’s no need to wrap rangewith a list, though:
In[93]:foriinrange(3):print(i)

List, Dictionary, and Set Comprehensions
List, dictionary, and set comprehensions are technically a way to create the respective data structure, but they often replace a forloop, which is why I am introducing them here. Assume that in the following list of USD currency pairs, you’d like to pick out those currencies where USD is quoted as the second currency. You could write the following forloop:
In[101]:currency_pairs=["USDJPY","USDGBP","USDCHF","USDCAD","AUDUSD","NZDUSD"]

Conclusion
This chapter was a packed introduction to Python. We met the most important building blocks of the language, including data structures, functions, and modules. We also touched on some of Python’s particularities like meaningful white space and code formatting guidelines, better known as PEP 8. To continue with this book, you won’t need to know all the details: as a beginner, just knowing about lists and dictionaries, indexing and slicing, as well as how to work with functions, modules, forloops, and ifstatements will get you far already.

NumPy is the core package for scientific computing in Python, providing support for array-based calculations and linear algebra. As NumPy is the backbone of pandas, I am going to introduce its basics in this chapter: after explaining what a NumPy array is, we will look into vectorization and broadcasting, two important concepts that allow you to write concise mathematical code and that you will find again in pandas. After that, we’re going to see why NumPy offers special functions called universal functions before we wrap this chapter up by learning how to get and set values of an array and by explaining the difference between a view and a copy of a NumPy array. Even if we will hardly use NumPy directly in this book, knowing its basics will make it easier to learn pandas in the next chapter.

有翻译吗

什么是 Python？
Python 是一种解释型、交互式、面向对象的编程语言。它包含了模块、异常、动态类型、高层级动态数据
类型以及类等特性。在面向对象编程以外它还支持多种编程范式，例如过程式和函数式编程等。Python
结合了超强的功能和极清晰的语法。它带有许多系统调用和库以及多种窗口系统的接口，并且能用 C 或
C++ 来进行扩展。它还可用作需要可编程接口的应用程序的扩展语言。最后，Python 非常易于移植：它
可以在包括 Linux 和 macOS 在内的许多 Unix 变种以及 Windows 上运行。

什么是 Python 软件基金会？
Python 软件基金会（Python Software Foundation，简称 PSF）是一个独立的非盈利组织，它拥有 Python
2.1 及以上各版本的版权。PSF 的使命是推进与 Python 编程语言相关的开源技术，并推广 Python 的使用。

使用 Python 是否存在版权限制？
你可以任意使用源码，只要你保留版权信息并在你基于 Python 的产品文档中显示该版权信息。如果你遵
守此版权规则，就可以将 Python 用于商业领域，以源码或二进制码的形式（不论是否经过修改）销售
Python 的副本，或是以某种形式包含了 Python 的产品。当然，我们仍然希望获知所有对 Python 的商业使
用。

创造 Python 的最初理由是什么？
以下是有关最初缘起的一份 非常简短的摘要，由 Guido van Rossum 本人撰写:
我在 CWI 的 ABC 部门时在实现解释型语言方面积累了丰富经验，通过与这个部门成员的协
同工作，我学到了大量有关语言设计的知识。这是许多 Python 特性的最初来源，包括使用缩
进来组织语句以及包含非常高层级的数据结构（虽然在 Python 中具体的实现细节完全不同）。
我对 ABC 语言有过许多抱怨，但同时也很喜欢它的许多特性。没有可能通过扩展 ABC 语言
（或它的实现）来弥补我的不满——实际上缺乏可扩展性就是它最大的问题之一。我也有一
些使用 Modula-2+ 的经验，并曾与 Modula-3 的设计者进行交流，还阅读了 Modula-3 的报告。
Modula-3 是 Python 中异常机制所用语法和语义，以及其他一些语言特性的最初来源。
我还曾在 CWI 的 Amoeba 分布式操作系统部门工作。当时我们需要有一种比编写 C 程序或
Bash 脚本更好的方式来进行系统管理，因为 Amoeba 有它自己的系统调用接口，并且无法方
便地通过 Bash 来访问。我在 Amoeba 中处理错误的经验令我深刻地意识到异常处理在编程语
言特性当中的重要地位。
我发现，某种具有 ABC 式的语法而又能访问 Amoeba 系统调用的脚本语言将可满足需求。我
意识到编写一种 Amoeba 专属的语言是愚蠢的，所以我决定编写一种具有全面可扩展性的语
言。
在 1989 年的圣诞假期中，我手头的时间非常充裕，因此我决定开始尝试一下。在接下来的一
年里，虽然我仍然主要用我的业余时间来做这件事，但 Python 在 Amoeba 项目中的使用获得
了很大的成功，来自同事的反馈让我得以增加了许多早期的改进。
到 1991 年 2 月，经过一年多的开发，我决定将其发布到 USENET。之后的事情就都可以在
Misc/HISTORY 文件里面看了。

Python 适合做什么？
Python 是一种高层级的多用途编程语言，可用于解决许多不同门类的问题。
该语言附带一个庞大的标准库，涵盖了字符串处理（正则表达式，Unicode，比较文件间的差异等），因
特网协议（HTTP，FTP，SMTP，XML-RPC，POP，IMAP，CGI 编程等），软件工程（单元测试，日志
记录，性能分析，Python 代码解析等），以及操作系统接口（系统调用，文件系统，TCP/IP 套接字等）。
请查看 library-index 的目录以了解所有可用的内容。此外还可以获取到各种各样的第三方扩展。请访问
Python 包索引 来查找你感兴趣的软件包。