Instant Data Intensive Apps with pandas How-to

Manipulate, visualize, and analyze your data with pandas

Instant Data Intensive Apps with pandas How-to

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Trent Hauck

Manipulate, visualize, and analyze your data with pandas
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Book Details

ISBN 139781782165583
Paperback50 pages

Book Description

Pandas helps to alleviate a genuinely complex situation in data analytics libraries. Many incumbent languages aren't approachable or are fairly unproductive in general computing tasks in comparison to Python. However with Pandas it's easy to begin working with tabular datasets in a language that's easier to learn and use.

Instant Data Intensive Apps with pandas How-to starts with Pandas’ functionalities such as joining datasets, cleaning data, and other data munging tasks. It quickly moves onto building a data reporting tool, which consists of analysis in Pandas to determine what’s relevant and present that relevant data in an easy-to-consume manner.

Instant Data Intensive Apps with pandas How-to starts with data manipulation and other practical tasks for a fundamental understanding, and through successive recipes you will gain a more profitable understanding of Pandas.

Throughout this book the recipes are presented in a structured way. It starts with data transformation techniques, but builds up to more complex examples such as performing statistical analysis and integrating Pandas objects with web applications. The other recipes cover visualization and machine learning, among other things.

Instant Data Intensive Apps with pandas How-to will get the reader up and running quickly with Pandas and put the user in a position to move up the learning curve faster.

Table of Contents

Chapter 1: Instant Data-intensive Apps with pandas How-to
Working with files (Simple)
Slicing pandas objects (Simple)
Subsetting data (Simple)
Working with dates (Medium)
Modifying data with functions (Simple)
Combining datasets (Medium)
Using indexes to manipulate objects (Medium)
Getting data from the Web (Simple)
Combining pandas with scikit-learn (Advanced)
Integrating pandas with statistics packages (Advanced)
Using Flask for the backend (Advanced)
Visualizing pandas objects (Advanced)
Reporting with pandas objects (Medium)

What You Will Learn

  • Learn data manipulation in Pandas including subsetting data, data transformation, and data reshaping
  • Combine data sets to get an idea of what the output with tabular data looks like
  • Perform aggregate data operations such as counts and sums for exploratory analysis
  • Use basic machine learning to identify stock performance similarities
  • Create visualizations of data including displaying tables and line graphs
  • Integrate other libraries with Pandas and carry out a simple analysis
  • Create a web application to display Pandas data in a web page

Authors

Table of Contents

Chapter 1: Instant Data-intensive Apps with pandas How-to
Working with files (Simple)
Slicing pandas objects (Simple)
Subsetting data (Simple)
Working with dates (Medium)
Modifying data with functions (Simple)
Combining datasets (Medium)
Using indexes to manipulate objects (Medium)
Getting data from the Web (Simple)
Combining pandas with scikit-learn (Advanced)
Integrating pandas with statistics packages (Advanced)
Using Flask for the backend (Advanced)
Visualizing pandas objects (Advanced)
Reporting with pandas objects (Medium)

Book Details

ISBN 139781782165583
Paperback50 pages
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