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Hands-On Data Analysis with NumPy and pandas
Hands-On Data Analysis with NumPy and pandas

Hands-On Data Analysis with NumPy and pandas: Implement Python packages from data manipulation to processing

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Hands-On Data Analysis with NumPy and pandas

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Key benefits

  • Explore the tools you need to become a data analyst
  • Discover practical examples to help you grasp data processing concepts
  • Walk through hierarchical indexing and grouping for data analysis

Description

Python, a multi-paradigm programming language, has become the language of choice for data scientists for visualization, data analysis, and machine learning. Hands-On Data Analysis with NumPy and Pandas starts by guiding you in setting up the right environment for data analysis with Python, along with helping you install the correct Python distribution. In addition to this, you will work with the Jupyter notebook and set up a database. Once you have covered Jupyter, you will dig deep into Python’s NumPy package, a powerful extension with advanced mathematical functions. You will then move on to creating NumPy arrays and employing different array methods and functions. You will explore Python’s pandas extension which will help you get to grips with data mining and learn to subset your data. Last but not the least you will grasp how to manage your datasets by sorting and ranking them. By the end of this book, you will have learned to index and group your data for sophisticated data analysis and manipulation.

Who is this book for?

Hands-On Data Analysis with NumPy and Pandas is for you if you are a Python developer and want to take your first steps into the world of data analysis. No previous experience of data analysis is required to enjoy this book.

What you will learn

  • Understand how to install and manage Anaconda
  • Read, sort, and map data using NumPy and pandas
  • Find out how to create and slice data arrays using NumPy
  • Discover how to subset your DataFrames using pandas
  • Handle missing data in a pandas DataFrame
  • Explore hierarchical indexing and plotting with pandas

Product Details

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Publication date, Length, Edition, Language, ISBN-13
Publication date : Jun 29, 2018
Length: 168 pages
Edition : 1st
Language : English
ISBN-13 : 9781789534245
Category :
Languages :
Concepts :
Tools :

What do you get with eBook?

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Product Details

Publication date : Jun 29, 2018
Length: 168 pages
Edition : 1st
Language : English
ISBN-13 : 9781789534245
Category :
Languages :
Concepts :
Tools :

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Table of Contents

7 Chapters
Setting Up a Python Data Analysis Environment Chevron down icon Chevron up icon
Diving into NumPY Chevron down icon Chevron up icon
Operations on NumPy Arrays Chevron down icon Chevron up icon
pandas are Fun! What is pandas? Chevron down icon Chevron up icon
Arithmetic, Function Application, and Mapping with pandas Chevron down icon Chevron up icon
Managing, Indexing, and Plotting Chevron down icon Chevron up icon
Other Books You May Enjoy Chevron down icon Chevron up icon

Customer reviews

Top Reviews
Rating distribution
Full star icon Full star icon Half star icon Empty star icon Empty star icon 2.9
(7 Ratings)
5 star 28.6%
4 star 14.3%
3 star 0%
2 star 28.6%
1 star 28.6%
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Top Reviews

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Akshay Jan 02, 2024
Full star icon Full star icon Full star icon Full star icon Full star icon 5
Excellent book that gets down to the basics!
Subscriber review Packt
S. Sankara Subramanian Sep 10, 2018
Full star icon Full star icon Full star icon Full star icon Full star icon 5
no specific comments
Amazon Verified review Amazon
Amazon Customer Aug 27, 2018
Full star icon Full star icon Full star icon Full star icon Empty star icon 4
Would recommend this book to those with a background in data analysis and are untrained in using Python.Pros - This book delivers exactly what is written in the title, no more, no less. The writing style is introductory and there are plenty of examples. The book addresses how to clean data using Python which is mandatory when performing data analysis. Examples discussed in this book could be used to supplement references which are less practical.Cons - The editing uses incorrect fonts on words that refer to technical terms. For example, some Python functions in this book are type-font, but the editor frequently omits this formatting. Many screenshots include cursors. Some sections, such as the linear algebra section, explain how to implement code but do not explain the context or give references.
Amazon Verified review Amazon
BBCReview Sep 30, 2021
Full star icon Full star icon Empty star icon Empty star icon Empty star icon 2
The books has good content on Numpy and Pandas, but you can't read the code snippets without a magnifying glass, or worse yet, zooming each one. Not the fault of the author, but it's darn hard to follow when it take 10 seconds to read each each snippet.
Amazon Verified review Amazon
Philip H Sep 15, 2018
Full star icon Full star icon Empty star icon Empty star icon Empty star icon 2
The explanations are reasonable although the book could have been written much more concisely. The examples are written in tiny fonts
Amazon Verified review Amazon
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