Book Image

Hands-On Exploratory Data Analysis with Python

By : Suresh Kumar Mukhiya, Usman Ahmed
Book Image

Hands-On Exploratory Data Analysis with Python

By: Suresh Kumar Mukhiya, Usman Ahmed

Overview of this book

Exploratory Data Analysis (EDA) is an approach to data analysis that involves the application of diverse techniques to gain insights into a dataset. This book will help you gain practical knowledge of the main pillars of EDA - data cleaning, data preparation, data exploration, and data visualization. You’ll start by performing EDA using open source datasets and perform simple to advanced analyses to turn data into meaningful insights. You’ll then learn various descriptive statistical techniques to describe the basic characteristics of data and progress to performing EDA on time-series data. As you advance, you’ll learn how to implement EDA techniques for model development and evaluation and build predictive models to visualize results. Using Python for data analysis, you’ll work with real-world datasets, understand data, summarize its characteristics, and visualize it for business intelligence. By the end of this EDA book, you’ll have developed the skills required to carry out a preliminary investigation on any dataset, yield insights into data, present your results with visual aids, and build a model that correctly predicts future outcomes.
Table of Contents (17 chapters)
1
Section 1: The Fundamentals of EDA
6
Section 2: Descriptive Statistics
11
Section 3: Model Development and Evaluation

Choosing the best chart

There is no standard that defines which chart you should choose to visualize your data. However, there are some guidelines that can help you. Here are some of them:

  • As mentioned with each of the preceding charts that we have seen, it is important to understand what type of data you have. If you have continuous variables, then a histogram would be a good choice. Similarly, if you want to show ranking, an ordered bar chart would be a good choice.
  • Choose the chart that effectively conveys the right and relevant meaning of the data without actually distorting the facts.
  • Simplicity is best. It is considered better to draw a simple chart that is comprehensible than to draw sophisticated ones that require several reports and texts in order to understand them.
  • Choose a diagram that does not overload the audience with information. Our purpose should be to illustrate...