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Hands-On Exploratory Data Analysis with Python

Hands-On Exploratory Data Analysis with Python

By : Kumar Mukhiya, Ahmed
2.5 (2)
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Hands-On Exploratory Data Analysis with Python

Hands-On Exploratory Data Analysis with Python

2.5 (2)
By: Kumar Mukhiya, 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)
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1
Section 1: The Fundamentals of EDA
6
Section 2: Descriptive Statistics
11
Section 3: Model Development and Evaluation

Using regular expressions

A regular expression, or regex, is a sequence of characters and special metacharacters used to match a set of character strings. Regular expressions allow you to be more expressive with string-matching operations than just providing a simple substring. You can think of it as a pattern that you want to match with strings of different lengths, made up of different characters.

In the str.contains() method, we supplied the regular expression, wigg|drew. In this case, the vertical bar | is a metacharacter that acts as the OR operator, so this regular expression matches any string that contains the substring wigg or drew.

Metacharacters let you change how you make matches. When you provide a regular expression that contains no metacharacters, it simply matches the exact substring. For instance, Wiggins would only match strings containing the exact substring...

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Hands-On Exploratory Data Analysis with Python
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