Discover the power of one of the fastest growing programming languages in the world with this insightful new resource. The Python Book delivers an essential introductory guide to learning Python for anyone who works with data but does not have experience in programming. 

The Python Book

Preface

Welcome to The Python Book , over the following pages you will be given an insight into the Python language. The genesis of this book has come from my experience of using and more importantly teaching Python over the last 10 years. With my background as a Data Scientist, I have used a number of different programming languages over the course of my career and Python being the one that has stuck with me. Why Python? For me I enjoy Python because its fast to develop with and covers many different application allowing me to use Python for pretty much everything. However for you the reader, Python is a great choice of language to learn as its easy to pick up and fast to get going with which means that for the novice programmers they can feel like they are making progress. This book is not just for complete novices, if you have some experience with Python, then this book is a great reference. The fact that you can pick up Python quickly means that many users skip the basics. This book looks to cover all the basics giving you the building blocks to do great things with the language. What this book is not intended to do is over complicating anything. Python is beautiful in its simplicity and this book looks to stick to that approach. Concepts will be explained in simple terms and examples will be used to show how to practically use the introduced concepts.

Introduction

For the purposes of this book, we want you to install the Anaconda distribution of Python that is available at https://www.anaconda.com . Here, you have distributions for Windows, Mac, and Linux, which can be easily installed on your computer. Once you have the Anaconda installed, you will have access to the Anaconda navigator as shown in Figure 2.1.

Getting Started

We have discussed packages without really describing what they are so let's look at packages and how it sits within the general setup of Python. As mentioned previously, Python is object orientated which means that everything is an object, you'll get to understand this in practice, however there are a few important builtin functions which aren't objects and they are worth mentioning here as they will be used within the book. These builtin types will be used throughout the book so keep an eye out for them. Below we show some useful ones, for a full list refer to https://docs.python.org/3/library/functions.html .

Packages and Builtin Functions

The next concept of Python that we will introduce is data types and in this chapter we will introduce a number of these and show how they behave when applied to some basic operators. We first start by introducing integers which are a number without a decimal point, written as follows:

Data Types

The previous chapter introduced data types and some basic operators but in this chapter we build on this by introducing a number of key operators that are important to understand. As shown in our introductory examples in the previous chapter, we can define a variable as follows:

Operators

In the previous chapters we covered some of the main data types in Python but one thing that is quite important is dates. For anyone who has worked with dates they can be tricky things, there are different ways to format them and they can be hard to manipulate, however Python has you covered. If we want to create a datetime object we do so as follows (we earlier showed how to import the datetime package):

Dates

In this chapter we will cover lists, not the kind you write down your food shop but a really important part of Python. Lists are the first of the storage types we consider from core Python, the others being Tuples, Dictionaries, and Sets. Fundamentally lists allow us to store things, let's say we want to have a variable containing the numbers 1–10, we can store them in a list as follows:

Lists

The good thing about covering lists is that it then makes tuples much easier to cover. Tuples are essentially lists. You access them in exactly the same way and many things we covered in lists are relevant to tuples, the big difference is tuples can't be modified. Why would you want something that cannot be modified? Well its actually more useful than you would think, it prevents you from accidentally changing something that you may rely on in your code.

Tuples

When we say dictionary in Python, we aren't speaking of the Oxford variety. Dictionaries are used to contain data in a very specific way as they hold key value pairs. What do we mean by key value pairs? For example, we could have a key as first name and a value as Rob. We could also have a key as wins and the value as 21. The key to dictionaries (pun intended) is that to access values we need to have a key associated with it. Let us start with an example about personal details, we may have the following fields: first name, surname, gender, favourite food. This could be written in the form of a dictionary as follows:

Dictionaries

In this chapter, we cover the last object for data collection and that is set. Perhaps the best use for sets is that they cannot contain duplicate values so can be useful for storing unique values. They are also unordered and cannot be changed. Let's start by creating a set.

Sets

This chapter is now going to cover the following important aspects of programming namely loops, if, else, and while statements. These statements are the key components of programming and allow us to operate on our objects. We have covered aspects of logic earlier when we considered comparison and equality and that is key when we look at if statements which is the first aspect we will consider here. The key to an if statement is that we need a statement that returns a true or false value. So let's consider the following statement:

Loops, if, Else, and While

Python is good at many things, I may be biased but I believe it's true, however one thing that its particularly good at is dealing with strings and string manipulation. This chapter will expand what we already know about strings showing how powerful Python is at dealing with them. So let's begin with looking at what a string is:

Strings

An extension to dealing with strings is the concept of regular expressions. The broad concept is that we can do advanced searches beyond the simple ones.

Regular Expressions

Thus far we have gone through what you can do with Python and the examples given have revolved around simple examples. In reality we want to work on data of some kind and as such we need to get it into Python. Now, we can obtain our data from a variety of sources such as databases, web API's but a common way to obtain data is through a good old fashioned file. So in this section, we will use a lot of what we have learnt so far to deal with reading data from and writing to files.

Dealing with Files

In this chapter, we are going to introduce the concepts of functions and classes and how these concepts can be introduced into the way you code in Python. Thus far in this book everything has been shown as blocks of code. These blocks of code may be just snippets to demonstrate a specific concept or longer sections to demonstrate how to perform a task. When you come to practically write your code you can write it in the manner that you have seen within this book and that is perfectly acceptable. However, if you want to group code together or reuse it then functions and classes are a great thing to use.

Functions and Classes

Previously we have looked at concepts and packages from the standard Python library, and now in this chapter we will look at a third‐party package and one that is very relevant within the Python eco‐system. Pandas is a package that is used for data analysis and data manipulation. It's used in a variety of packages and therefore understanding of it and its concepts is a crucial tool for a Python programmer to learn. In this chapter, we will introduce the package pandas from the basics up to some more advanced techniques. However, before we get started with pandas, we will briefly cover numpy arrays which alongside dictionaries and lists are concepts that should be understood to allow us to cover pandas.

Pandas

Plotting is a key component when looking to work with data, and Python has a number of plotting libraries. In this chapter, we cover plotting in great detail starting with creating basic plots directly from Pandas DataFrames to getting more control using matplotlib all the way through to using Seaborn. The chapter is fully example driven with code snippets alongside the graphics they produce. The aim of including both is to give you the ability to see what the code produces but also act as a reference for when you want to produce graphs. The examples are based on datasets that come from with Python with many being taken from the documentation with the idea of giving them greater explanation to help you understand what is happening. The packages that we will look to use in this chapter are imported below.

Plotting

In this chapter, we will cover how to deal with APIs (application programming interfaces) using Python. To do this we are going to cover both how to create and access an API and build examples to do both. Before we get to writing any code we need to cover what an API is and why its useful. An API is a mechanism that allows communication between software applications and in this case will cover communication between an application and a web user. The uses of APIs have become increasingly popular allowing users to access data or communicate with services. They give a unified approach to doing so and therefore have become an important aspect to become familiar with, understanding how to communicate with.

APIs in Python

The last chapter of the book covers the concept of web scraping. This is the programmatic process of obtaining information from a web page. To do this we need to get up to speed on a number of things:

Web Scraping in Python

This book has given you an introduction into Python covering all the basics right up to some complex examples. However, there is much more that could have been covered and much more for you the reader to learn. Python has many more packages and changes are always being made, so its important to keep up to date with the trends within the language. From a development point of view, we have kept things simple working in the shell or writing basic scripts, however Python can be so much more than an exploratory language. Python can be used in a production environment and given its adoption by many big tech firms it works very well with a lot of cloud computing solutions and is an excellent choice for everything from web applications to machine learning. This book is a gateway to give you the tools to follow your own Python journey and with a community as big as Pythons there is always something to learn as well as new things to be aware of. Good luck!

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