To get the most out of this book

What do we require for this book:

1. This book uses Python to complete all of its code examples. A machine (Linux/Mac/Windows is OK) with access to a Unix-style terminal and Python 2.7 installed is required.
2. Installing the Anaconda distribution is also recommended as it comes with most of the packages used in the examples.

Download the example code files

You can download the example code files for this book from your account at www.packtpub.com. If you purchased this book elsewhere, you can visit www.packtpub.com/support and register to have the files emailed directly to you.

You can download the code files by following these steps:

1. Log in or register at www.packtpub.com.
2. Select the SUPPORT tab.
3. Click on Code Downloads & Errata.
4. Enter the name of the book in the Search box and follow the onscreen instructions.

Once the file is downloaded, please make sure that you unzip or extract the folder using the latest version of:

• WinRAR/7-Zip for Windows
• Zipeg/iZip/UnRarX for Mac
• 7-Zip/PeaZip for Linux

The code bundle for the book is also hosted on GitHub at https://github.com/PacktPublishing/Feature-Engineering-Made-Easy. We also have other code bundles from our rich catalog of books and videos available at https://github.com/PacktPublishing/. Check them out!

Download the color images

We also provide a PDF file that has color images of the screenshots/diagrams used in this book. You can download it here: https://www.packtpub.com/sites/default/files/downloads/FeatureEngineeringMadeEasy_ColorImages.pdf.

Conventions used

There are a number of text conventions used throughout this book.

CodeInText: Indicates code words in text, database table names, folder names, filenames, file extensions, pathnames, dummy URLs, user input, and Twitter handles. Here is an example: "Suppose further that given this dataset, our task is to be able to take in three of the attributes (datetime, protocol, and urgent) and to be able to accurately predict the value of malicious. In layman's terms, we want a system that can map the values of datetime, protocol, and urgent to the values in malicious."

A block of code is set as follows:

Network_features = pd.DataFrame({'datetime': ['6/2/2018', '6/2/2018', '6/2/2018', '6/3/2018'], 'protocol': ['tcp', 'http', 'http', 'http'], 'urgent': [False, True, True, False]})
Network_response = pd.Series([True, True, False, True])
Network_features
>>
 datetime protocol  urgent
0  6/2/2018      tcp   False
1  6/2/2018     http    True
2  6/2/2018     http    True
3  6/3/2018     http   False
Network_response
>>
 0     True
1     True
2    False
3     True
dtype: bool

When we wish to draw your attention to a particular part of a code block, the relevant lines or items are set in bold:

times_pregnant                  0.221898
plasma_glucose_concentration    0.466581
diastolic_blood_pressure        0.065068
triceps_thickness               0.074752
serum_insulin                   0.130548
bmi                             0.292695
pedigree_function               0.173844
age                             0.238356
onset_diabetes                  1.000000
Name: onset_diabetes, dtype: float64

Bold: Indicates a new term, an important word, or words that you see onscreen. 

Warnings or important notes appear like this.

Tips and tricks appear like this.