Exploratory Data Analysis with Python Cookbook
Oluleye, Ayodele
Verkauft von Books Puddle, New York, NY, USA
AbeBooks-Verkäufer seit 22. November 2018
Neu - Softcover
Zustand: Neu
Anzahl: 4 verfügbar
In den Warenkorb legenVerkauft von Books Puddle, New York, NY, USA
AbeBooks-Verkäufer seit 22. November 2018
Zustand: Neu
Anzahl: 4 verfügbar
In den Warenkorb legenExtract valuable insights from data by leveraging various analysis and visualization techniques with this comprehensive guide
Purchase of the print or Kindle book includes a free PDF eBook
Exploratory data analysis (EDA) is a crucial step in data analysis and machine learning projects as it helps in uncovering relationships and patterns and provides insights into structured and unstructured datasets. With various techniques and libraries available for performing EDA, choosing the right approach can sometimes be challenging. This hands-on guide provides you with practical steps and ready-to-use code for conducting exploratory analysis on tabular, time series, and textual data.
The book begins by focusing on preliminary recipes such as summary statistics, data preparation, and data visualization libraries. As you advance, you’ll discover how to implement univariate, bivariate, and multivariate analyses on tabular data. Throughout the chapters, you’ll become well versed in popular Python visualization and data manipulation libraries such as seaborn and pandas.
By the end of this book, you will have mastered the various EDA techniques and implemented them efficiently on structured and unstructured data.
If you are a data analyst interested in the practical application of exploratory data analysis in Python, then this book is for you. This book will also benefit data scientists, researchers, and statisticians who are looking for hands-on instructions on how to apply EDA techniques using Python libraries. Basic knowledge of Python programming and a basic understanding of fundamental statistical concepts is a prerequisite.
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