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{ "item_title" : "Introduction to Data Science with Python", "item_author" : [" Mark Smart "], "item_description" : "This book is a guide for you on how to use Pandas and Numpy in Python programming language for data analysis. The author begins by helping you familiarize yourself with the basics of data science, Numpy and Pandas. You are guided on how to work with Numpy arrays and how to manipulate them. The various operations that you can perform on your data via the Pandas library have been discussed. You will also know how to create various data structures in Pandas for data storage. Data from the environment is dirty. The process of cleaning such data has been discussed. This involves handling outliers, missing values etc. The author guides you on how to work with data in various types of storage formats. Examples include MS Excel, CSV files, JSON, etc. You are also guided on how to calculate various measures for your data. The process of visualizing data has been explored in detail.", "item_img_path" : "https://covers2.booksamillion.com/covers/bam/1/73/103/684/1731036841_b.jpg", "price_data" : { "retail_price" : "9.38", "online_price" : "9.38", "our_price" : "9.38", "club_price" : "9.38", "savings_pct" : "0", "savings_amt" : "0.00", "club_savings_pct" : "0", "club_savings_amt" : "0.00", "discount_pct" : "10", "store_price" : "" } }
Introduction to Data Science with Python|Mark Smart

Introduction to Data Science with Python : Basics of Numpy and Pandas

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Overview

This book is a guide for you on how to use Pandas and Numpy in Python programming language for data analysis. The author begins by helping you familiarize yourself with the basics of data science, Numpy and Pandas. You are guided on how to work with Numpy arrays and how to manipulate them. The various operations that you can perform on your data via the Pandas library have been discussed. You will also know how to create various data structures in Pandas for data storage. Data from the environment is dirty. The process of cleaning such data has been discussed. This involves handling outliers, missing values etc. The author guides you on how to work with data in various types of storage formats. Examples include MS Excel, CSV files, JSON, etc. You are also guided on how to calculate various measures for your data. The process of visualizing data has been explored in detail.

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Details

  • ISBN-13: 9781731036841
  • ISBN-10: 1731036841
  • Publisher: Independently Published
  • Publish Date: November 2018
  • Dimensions: 9 x 6 x 0.21 inches
  • Shipping Weight: 0.32 pounds
  • Page Count: 102

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