Book Image

Hands-On Data Preprocessing in Python

By : Roy Jafari
5 (2)
Book Image

Hands-On Data Preprocessing in Python

5 (2)
By: Roy Jafari

Overview of this book

Hands-On Data Preprocessing is a primer on the best data cleaning and preprocessing techniques, written by an expert who’s developed college-level courses on data preprocessing and related subjects. With this book, you’ll be equipped with the optimum data preprocessing techniques from multiple perspectives, ensuring that you get the best possible insights from your data. You'll learn about different technical and analytical aspects of data preprocessing – data collection, data cleaning, data integration, data reduction, and data transformation – and get to grips with implementing them using the open source Python programming environment. The hands-on examples and easy-to-follow chapters will help you gain a comprehensive articulation of data preprocessing, its whys and hows, and identify opportunities where data analytics could lead to more effective decision making. As you progress through the chapters, you’ll also understand the role of data management systems and technologies for effective analytics and how to use APIs to pull data. By the end of this Python data preprocessing book, you'll be able to use Python to read, manipulate, and analyze data; perform data cleaning, integration, reduction, and transformation techniques, and handle outliers or missing values to effectively prepare data for analytic tools.
Table of Contents (24 chapters)
1
Part 1:Technical Needs
6
Part 2: Analytic Goals
11
Part 3: The Preprocessing
18
Part 4: Case Studies

Chapter 15: Case Study 1 – Mental Health in Tech

In this chapter and the two upcoming ones, we are going to put the skills that we have picked up in the course of this book into practice. For this case study, we are going to use data collected by Open Sourcing Mental Illness (OSMI) (https://osmihelp.org/), which is a non-profit corporation dedicated to raising awareness, educating, and providing resources to support mental wellness in the tech and open source communities. OSMI conducts yearly surveys that "aim to measure attitudes towards mental health in the tech workplace and examine the frequency of mental health disorders among tech workers." These surveys are accessible to the public for participation and can be found at https://osmihelp.org/research.

In this chapter, we're going to learn about mental health in tech case study by covering the following:

  • Introducing the case study
  • Integrating the data sources
  • Cleaning the data
  • Analyzing...