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Suresh Kumar Mukhiya
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Hands-On Exploratory Data Analysis with Python: Perform EDA techniques to understand, summarize, and investigate your data

by Suresh Kumar Mukhiya (Author), Usman Ahmed (Author)
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Discover techniques to summarize the characteristics of your data using PyPlot; NumPy; SciPy; and pandas

Key Features:

- Understand the fundamental concepts of exploratory data analysis using Python

- Find missing values in your data and identify the correlation between different variables

- Practice graphical exploratory analysis techniques using Matplotlib and the Seaborn Python package

Book Description:

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.

What You Will Learn:

- Import; clean; and explore data to perform preliminary analysis using powerful Python packages

- Identify and transform erroneous data using different data wrangling techniques

- Explore the use of multiple regression to describe non-linear relationships

- Discover hypothesis testing and explore techniques of time-series analysis

- Understand and interpret results obtained from graphical analysis

- Build; train; and optimize predictive models to estimate results

- Perform complex EDA techniques on open source datasets

Who this book is for:

This EDA book is for anyone interested in data analysis; especially students; statisticians; data analysts; and data scientists. The practical concepts presented in this book can be applied in various disciplines to enhance decision-making processes with data analysis and synthesis. Fundamental knowledge of Python programming and statistical concepts is all you need to get started with this book.

Table of Contents

- Exploratory Data Analysis Fundamentals

- Visual Aids for EDA

- EDA with Personal Email

- Data Transformation

- Descriptive Statistics

- Grouping Dataset

- Correlation

- Time Series Analysis

- Hypothesis Testing and Regression

- Model Development and Evaluation

- EDA on Wine Quality Data Analysis

- Appendix

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  1. ISBN-10
    1789537258
  2. ISBN-13
    978-1789537253
  3. Publisher
    Packt Publishing
  4. Publication date
    March 27, 2020
  5. Language
    English
  6. Dimensions
    7.5 x 0.8 x 9.25 inches
  7. Print length
    352 pages
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Editorial Reviews

About the Author

Suresh Kumar Mukhiya is a PhD candidate, currently affiliated to the Western Norway University of Applied Sciences (HVL). He is a big data enthusiast, specializing in Information Systems, Model-Driven Software Engineering, Big Data Analysis, Artificial Intelligence and Frontend development. He has completed a Masters in Information Systems from the Norwegian University of Science and Technology (NTNU, Norway) along with a thesis in processing mining. He also holds a bachelor's degree in computer science and information technology (BSc.CSIT) from Tribhuvan University, Nepal, where he was decorated with the Vice-Chancellor's Award for obtaining the highest score. He is a passionate photographer and a resilient traveler.

Usman Ahmed is a data scientist and Ph.D. candidate at Western Norway University of Applied Science (HVL). He has rich experience in building and scaling high-performance systems based on data mining, natural language processing, and machine learning. Usman's research interests are sequential data mining, heterogeneous computing, natural language processing, a recommendation system, and machine learning. He has completed a Master's of Science in computer science from Capital University of Science and Technology, Islamabad, Pakistan. Usman Ahmed was awarded Gold Medal in Bachelor of Computer Science from Heavy Industries Taxila Education City.

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Suresh Kumar Mukhiya

Suresh Kumar Mukhiya

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Suresh Kumar Mukhiya is a Ph.D. candidate currently affiliated with the Western Norway University of Applied Sciences (HVL). He has completed his Master's degree in information systems at the Norwegian University of Science and Technology (NTNU, Norway), along with a thesis in processing mining. He also holds a Bachelor's degree in computer science and information technology (BSc.CSIT) from Tribhuvan University, Nepal, where he was decorated with the Vice-Chancellor's Award for obtaining the highest score. He is a passionate photographer and a resilient traveler.

Suresh has many years of experience with coding in Python and other programming languages. He has given several seminars on the practical applications of data science and machine learning and deep learning over the years. Suresh loves to write and talk about data science, machine learning, and Python. He is very motivated to help people developing data-driven solutions without necessarily requiring a machine learning background. He believes Artificial Intelligence is the driving fuel for computer science in the coming days.

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Customer reviews

3.8 out of 5 stars
22 global ratings

Top reviews from the United States

  • Denzel Ignatius Arulmani Selvam
    4.0 out of 5 stars A good introductory book if you want to get started on EDA with Python
    Reviewed in the United States on October 15, 2020
    Format: Kindle
    Pros:
    1. Covers all the important concepts you need to know to get started with EDA.
    2. Lots of sample codes which the reader can use to get their hands dirty.
    3. Works excellently as a reference book to look up the basic concepts of EDA.

    Cons:
    This book only contains an brief overview of the concepts. So, if you want to get a very deep understanding of the subject matter, this is not the book for you.
    Helpful
     Report

Top reviews from other countries

  • samarth saxena
    1.0 out of 5 stars Waste of money 💰 , content of no use
    Reviewed in India on August 28, 2020
    Format: PaperbackVerified Purchase
    Worst print , black - white copy , no colour print as shown in Google book preview and not any special content
    Customer image
    samarth saxena
    1.0 out of 5 stars
    Waste of money 💰 , content of no use

    Reviewed in India on August 28, 2020
    Worst print , black - white copy , no colour print as shown in Google book preview and not any special content
    Images in this review
    Customer image
    Report
  • David
    1.0 out of 5 stars Don't waste your time
    Reviewed in the United Kingdom on June 27, 2025
    Format: PaperbackVerified Purchase
    Not worth your time, the tone of the author is needlessly condescending, a significant portion of the book is basically just scraped basic tutorials of numpy, pandas and seaborn. There are also a number of serious errors in the code, examples do not work and require modification to work as the author intended and some of the referenced datasets do not exist

    Don't waste your time with this book, just set up the libraries and have a play around on the quick-start tutorials for those instead.
    Report