Hands-On Exploratory Data Analysis with Python

Hands-On Exploratory Data Analysis with Python

eBook Details:

  • Paperback: 352 pages
  • Publisher: WOW! eBook (March 27, 2020)
  • Language: English
  • ISBN-10: 1789537258
  • ISBN-13: 978-1789537253

eBook Description:

Hands-On Exploratory Data Analysis with Python: Discover techniques to summarize the characteristics of your data using PyPlot, NumPy, SciPy, and Pandas

Exploratory Data Analysis (EDA) is an approach to data analysis that involves the application of diverse techniques to gain insights into a dataset. This Hands-On Exploratory Data Analysis with Python 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.

  • 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

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.

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