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Exploratory Data Analysis with Python Cookbook

You're reading from Exploratory Data Analysis with Python Cookbook Over 50 recipes to analyze, visualize, and extract insights from structured and unstructured data

Product type Paperback

Published in Jun 2023

Publisher Packt

ISBN-13 9781803231105

Length 382 pages

Edition 1st Edition

Languages

Python

Tools

Matplotlib

Concepts

Data Analysis

Author (1):

Ayodele Oluleye

View More author details

Table of Contents (13) Chapters

Preface

1. Chapter 1: Generating Summary Statistics

2. Chapter 2: Preparing Data for EDA FREE CHAPTER

3. Chapter 3: Visualizing Data in Python

4. Chapter 4: Performing Univariate Analysis in Python

5. Chapter 5: Performing Bivariate Analysis in Python

6. Chapter 6: Performing Multivariate Analysis in Python

7. Chapter 7: Analyzing Time Series Data in Python

8. Chapter 8: Analysing Text Data in Python

9. Chapter 9: Dealing with Outliers and Missing Values

10. Chapter 10: Performing Automated Exploratory Data Analysis in Python

11. Index

Why subscribe?

12. Other Books You May Enjoy

Visualizing Data in Python

Visualizing data is a critical component of Exploratory Data Analysis (EDA). It helps us understand relationships, patterns, and hidden trends within our data much better. With the right charts or visuals, trends within large and complex datasets can be easily interpreted, and hidden patterns or outliers can be easily identified. In Python, data can be visualized using a wide array of libraries, and in this chapter, we will explore the most common data visualization libraries in Python.

In this chapter, we will cover the following key topics:

Preparing for visualization
Visualizing data in Matplotlib
Visualizing data in Seaborn
Visualizing data in GGPLOT
Visualizing data in Bokeh

The rest of the chapter is locked

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Authors (1)

Ayodele Oluleye

Ayodele Oluleye

Ayodele is a data professional with nearly a decade of experience. Throughout his career, he has gained valuable experience in various domains such as strategy, data science and more recently data management. Previously, he served as a consultant at a big 4 consulting firm, where he successfully provided data-driven solutions and insights to clients. Currently, he holds a leadership position at a financial services group where he leads a dynamic data team, driving analytics initiatives to empower the organization. Beyond his professional endeavors, he is passionate about sharing his knowledge and experience. You can find him actively engaging with the data community through insightful articles on LinkedIn and speaking at industry events.

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