Learning pandas - Second Edition
Nonfiction, Computers, Database Management, Data Processing, Programming, Programming Languages
| Author: | Michael Heydt | ISBN: | 9781787120310 |
| Publisher: | Packt Publishing | Publication: | June 30, 2017 |
| Imprint: | Packt Publishing | Language: | English |
| Author: | Michael Heydt |
| ISBN: | 9781787120310 |
| Publisher: | Packt Publishing |
| Publication: | June 30, 2017 |
| Imprint: | Packt Publishing |
| Language: | English |
Get to grips with pandas—a versatile and high-performance Python library for data manipulation, analysis, and discovery
About This Book
- Get comfortable using pandas and Python as an effective data exploration and analysis tool
- Explore pandas through a framework of data analysis, with an explanation of how pandas is well suited for the various stages in a data analysis process
- A comprehensive guide to pandas with many of clear and practical examples to help you get up and using pandas
Who This Book Is For
This book is ideal for data scientists, data analysts, Python programmers who want to plunge into data analysis using pandas, and anyone with a curiosity about analyzing data. Some knowledge of statistics and programming will be helpful to get the most out of this book but not strictly required. Prior exposure to pandas is also not required.
What You Will Learn
- Understand how data analysts and scientists think about of the processes of gathering and understanding data
- Learn how pandas can be used to support the end-to-end process of data analysis
- Use pandas Series and DataFrame objects to represent single and multivariate data
- Slicing and dicing data with pandas, as well as combining, grouping, and aggregating data from multiple sources
- How to access data from external sources such as files, databases, and web services
- Represent and manipulate time-series data and the many of the intricacies involved with this type of data
- How to visualize statistical information
- How to use pandas to solve several common data representation and analysis problems within finance
In Detail
You will learn how to use pandas to perform data analysis in Python. You will start with an overview of data analysis and iteratively progress from modeling data, to accessing data from remote sources, performing numeric and statistical analysis, through indexing and performing aggregate analysis, and finally to visualizing statistical data and applying pandas to finance.
With the knowledge you gain from this book, you will quickly learn pandas and how it can empower you in the exciting world of data manipulation, analysis and science.
Style and approach
- Step-by-step instruction on using pandas within an end-to-end framework of performing data analysis
- Practical demonstration of using Python and pandas using interactive and incremental examples
Get to grips with pandas—a versatile and high-performance Python library for data manipulation, analysis, and discovery
About This Book
- Get comfortable using pandas and Python as an effective data exploration and analysis tool
- Explore pandas through a framework of data analysis, with an explanation of how pandas is well suited for the various stages in a data analysis process
- A comprehensive guide to pandas with many of clear and practical examples to help you get up and using pandas
Who This Book Is For
This book is ideal for data scientists, data analysts, Python programmers who want to plunge into data analysis using pandas, and anyone with a curiosity about analyzing data. Some knowledge of statistics and programming will be helpful to get the most out of this book but not strictly required. Prior exposure to pandas is also not required.
What You Will Learn
- Understand how data analysts and scientists think about of the processes of gathering and understanding data
- Learn how pandas can be used to support the end-to-end process of data analysis
- Use pandas Series and DataFrame objects to represent single and multivariate data
- Slicing and dicing data with pandas, as well as combining, grouping, and aggregating data from multiple sources
- How to access data from external sources such as files, databases, and web services
- Represent and manipulate time-series data and the many of the intricacies involved with this type of data
- How to visualize statistical information
- How to use pandas to solve several common data representation and analysis problems within finance
In Detail
You will learn how to use pandas to perform data analysis in Python. You will start with an overview of data analysis and iteratively progress from modeling data, to accessing data from remote sources, performing numeric and statistical analysis, through indexing and performing aggregate analysis, and finally to visualizing statistical data and applying pandas to finance.
With the knowledge you gain from this book, you will quickly learn pandas and how it can empower you in the exciting world of data manipulation, analysis and science.
Style and approach
- Step-by-step instruction on using pandas within an end-to-end framework of performing data analysis
- Practical demonstration of using Python and pandas using interactive and incremental examples
