Python For Data Analysis: Master the Basics of Data Analysis in Python Using Numpy, Pandas and IPython (Step-by-Step Tutorial for Beginners)

Samuel Burns

ISBN 10: 1091253900 / ISBN 13: 9781091253902

Edité par Independently published, 2019

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Synopsis :

You want to learn Python for data analysis using NumPy, Pandas, and IPython, and you don't know how to start? You don't need a big boring and expensive textbook. This book is the best one for everyone.Get your copy Now!!Why this book? Here are the reasons:The author has explored everything about python for data analysis using pandas, NumPy, Ipython and Matplotlib libraries from the basics.

• A simple language has been used.
• Many examples have been given, both theoretically and programmatically.
• Screenshots showing program outputs have been added.

The book is written chronologically, in a step-by-step manner.

Book Objectives:

The Aims and Objectives of the Book:

• To help you understand why you should choose Python for data analysis tasks.
• To help you know the various data analysis libraries supported by Python and how to use them.
• To help you know how to analyze your business data and draw meaningful insights for effective decision making.
• To equip you with data analysis skills using Python programming language.
• To help you know where data analysis is applied today and how to use it in your everyday life.

Who is this Book is for? :

Here are the target readers for this book:

• Anybody who is a complete beginner to data analysis with Python or data analysis in general.
• Anybody who wants to advance their data analysis skills with Python programming language.
• Anybody who wants to know how to use data analysis for the benefit of their business or brand.
• Professionals in data science, computer programming, computer scientist.
• Professors, lecturers or tutors who are looking to find better ways to explain python for data analysis to their students in the simplest and easiest way.
• Students and academicians, especially those focusing on python programming, computer science,neural networks, machine learning, and deep learning.

What do you need for this Book? :

You are required to have installed the following on your computer:

• Python 3.X
• Numpy
• Pandas
• Matplotlib

The Author guides you on how to install and configure the rest of the Python libraries that are required for data analysis.

What is inside the book? :

• Why Python for Data Analysis?
• Exploring the Libraries
• Installation and Setup
• Using IPython
• Numpy Arrays and Vectorized Computation
• Pandas Library
• Data Wrangling
• Data Visualization
• Data Aggregation
• Working with Time Series Data
• Applications of Data Analysis Today

The content of this book is all about data analysis with Python programming language using NumPy, Pandas, and IPython. It has been grouped into chapters, with each chapter exploring a different aspect of data analysis. The author has provided Python codes for doing different data analysis tasks. All these codes have been tested to ensure they are working correctly. Corresponding explanations have also been provided alongside each piece of code to help the reader understand the meaning of the various lines of the code. In addition to this, screenshots showing the output that each code should return have been given. The author has used a simple language to make it easy even for beginners to understand. The author begins by exploring the basic to the complex tasks in data analysis.

Présentation de l'éditeur: You want to learn Python for data analysis using NumPy, Pandas, and IPython, and you don't know how to start? You don't need a big boring and expensive textbook. This book is the best one for everyone.Get your copy Now!!Why this book? Here are the reasons:The author has explored everything about python for data analysis using pandas, NumPy, Ipython and Matplotlib libraries from the basics.

• A simple language has been used.
• Many examples have been given, both theoretically and programmatically.
• Screenshots showing program outputs have been added.

The book is written chronologically, in a step-by-step manner.

Book Objectives:

The Aims and Objectives of the Book:

• To help you understand why you should choose Python for data analysis tasks.
• To help you know the various data analysis libraries supported by Python and how to use them.
• To help you know how to analyze your business data and draw meaningful insights for effective decision making.
• To equip you with data analysis skills using Python programming language.
• To help you know where data analysis is applied today and how to use it in your everyday life.

Who is this Book is for? :

Here are the target readers for this book:

• Anybody who is a complete beginner to data analysis with Python or data analysis in general.
• Anybody who wants to advance their data analysis skills with Python programming language.
• Anybody who wants to know how to use data analysis for the benefit of their business or brand.
• Professionals in data science, computer programming, computer scientist.
• Professors, lecturers or tutors who are looking to find better ways to explain python for data analysis to their students in the simplest and easiest way.
• Students and academicians, especially those focusing on python programming, computer science,neural networks, machine learning, and deep learning.

What do you need for this Book? :

You are required to have installed the following on your computer:

• Python 3.X
• Numpy
• Pandas
• Matplotlib

The Author guides you on how to install and configure the rest of the Python libraries that are required for data analysis.

What is inside the book? :

• Why Python for Data Analysis?
• Exploring the Libraries
• Installation and Setup
• Using IPython
• Numpy Arrays and Vectorized Computation
• Pandas Library
• Data Wrangling
• Data Visualization
• Data Aggregation
• Working with Time Series Data
• Applications of Data Analysis Today

The content of this book is all about data analysis with Python programming language using NumPy, Pandas, and IPython. It has been grouped into chapters, with each chapter exploring a different aspect of data analysis. The author has provided Python codes for doing different data analysis tasks. All these codes have been tested to ensure they are working correctly. Corresponding explanations have also been provided alongside each piece of code to help the reader understand the meaning of the various lines of the code. In addition to this, screenshots showing the output that each code should return have been given. The author has used a simple language to make it easy even for beginners to understand. The author begins by exploring the basic to the complex tasks in data analysis.

Détails bibliographiques

Titre : Python For Data Analysis: Master the Basics ...
Éditeur : Independently published
Date d'édition : 2019
Reliure : paperback
Etat : Good