Exploratory Data Analysis with Python Cookbook

Exploratory Data Analysis with Python Cookbook

eBook Details:

  • Paperback: 382 pages
  • Publisher: WOW! eBook (June 30, 2023)
  • Language: English
  • ISBN-10: 1803231106
  • ISBN-13: 978-1803231105

eBook Description:

Exploratory Data Analysis with Python Cookbook: Extract valuable insights from data by leveraging various analysis and visualization techniques with this comprehensive guide

In today’s data-centric world, the ability to extract meaningful insights from vast amounts of data has become a valuable skill across industries. Exploratory Data Analysis (EDA) lies at the heart of this process, enabling us to comprehend, visualize, and derive valuable insights from various forms of data.

This book is a comprehensive guide to Exploratory Data Analysis using the Python programming language. It provides practical steps needed to effectively explore, analyze, and visualize structured and unstructured data. It offers hands-on guidance and code for concepts such as generating summary statistics, analyzing single and multiple variables, visualizing data, analyzing text data, handling outliers, handling missing values and automating the EDA process. It is suited for data scientists, data analysts, researchers or curious learners looking to gain essential knowledge and practical steps for analyzing vast amounts of data to uncover insights.

Python is an open-source general purpose programming language which is used widely for data science and data analysis given its simplicity and versatility. It offers several libraries which can be used to clean, analyze, and visualize data. In this book, we will explore popular Python libraries such as Pandas, Matplotlib, and Seaborn and provide workable code for analyzing data in Python using these libraries.

  • Perform EDA with leading Python data visualization libraries
  • Execute univariate, bivariate, and multivariate analyses on tabular data
  • Uncover patterns and relationships within time series data
  • Identify hidden patterns within textual data
  • Discover different techniques to prepare data for analysis
  • Overcome the challenge of outliers and missing values during data analysis
  • Leverage automated EDA for fast and efficient analysis

By the end of this Exploratory Data Analysis with Python Cookbook book, you will have gained comprehensive knowledge about EDA and mastered the powerful set of EDA techniques and tools required for analyzing both structured and unstructured data to derive valuable insights.

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