Mastering Clojure Data Analysis

If you’d like to apply your Clojure skills to performing data analysis, this is the book for you. The example based approach aids fast learning and covers basic to advanced topics. Get deeper into your data.

Mastering Clojure Data Analysis

Eric Rochester

If you’d like to apply your Clojure skills to performing data analysis, this is the book for you. The example based approach aids fast learning and covers basic to advanced topics. Get deeper into your data.
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Book Details

ISBN 139781783284139
Paperback340 pages

Book Description

Clojure is a Lisp dialect built on top of the Java Virtual Machine. As data increasingly invades more and more parts of our lives, we continually need more tools to deal with it effectively. Data can be organized effectively using Clojure data tools.

Mastering Clojure Data Analysis teaches you how to analyze and visualize complex datasets. With this book, you'll learn how to perform data analysis using established scientific methods with the modern, powerful Clojure programming language with the help of exciting examples drawn from real-world data. This will help you get to grips with advanced topics such as network analysis, the characteristics of social networks, applying topic modeling to get a handle on unstructured textual data, and GIS analysis to apply geospatial techniques to your data analysis problems.

With this guide, you'll learn how to leverage the power and flexibility of Clojure to dig into your data and access the insights it hides.

Table of Contents

Chapter 1: Network Analysis – The Six Degrees of Kevin Bacon
Analyzing social networks
Getting the data
Understanding graphs
Implementing the graphs
Measuring social network graphs
Visualizing the graph
Summary
Chapter 2: GIS Analysis – Mapping Climate Change
Understanding GIS
Mapping the climate change
Working with map projections
Working with ArcGIS
Summary
Chapter 3: Topic Modeling – Changing Concerns in the State of the Union Addresses
Understanding data in the State of Union addresses
Understanding topic modeling
Preparing for visualizations
Setting up the project
Getting the data
Summary
Chapter 4: Classifying UFO Sightings
Getting the data
Extracting the data
Dealing with messy data
Visualizing UFO data
Description
Topic modeling descriptions
Hoaxes
Summary
Chapter 5: Benford's Law – Detecting Natural Progressions of Numbers
Learning about Benford's Law
Failing Benford's Law
Case studies
Summary
Chapter 6: Sentiment Analysis – Categorizing Hotel Reviews
Understanding sentiment analysis
Getting hotel review data
Exploring the data
Preparing the data
Cross-validating the results
Calculating error rates
Using the Weka machine learning library
Running the experiment
Examining the results
Improving the results
Summary
Chapter 7: Null Hypothesis Tests – Analyzing Crime Data
Introducing confirmatory data analysis
Understanding null hypothesis testing
Understanding burglary rates
Exploring the data
Conducting the experiment
Interpreting the results
Summary
Chapter 8: A/B Testing – Statistical Experiments for the Web
Defining A/B testing
Conducting an A/B test
Summary
Chapter 9: Analyzing Social Data Participation
Setting up the project
Summary
Chapter 10: Modeling Stock Data
Learning about financial data analysis
Setting up the basics
Getting prepared with data
Analyzing the text
Inspecting the stock prices
Merging text and stock features
Analyzing both text and stock features together with neural nets
Predicting the future
Taking it with a grain of salt
Summary

What You Will Learn

  • Use geospatial data to learn about geographical patterns in data
  • Use sentiment analysis to determine people's opinions from online reviews
  • Frame and implement statistical experiments
  • Use A/B testing to determine the best UI to keep users engaged
  • Work with time series data
  • Learn how to use parallelization and concurrency to work with large datasets
  • Use topic modeling to find the subjects discussed in a group of documents
  • Use network analysis to learn about online social networks

Authors

Table of Contents

Chapter 1: Network Analysis – The Six Degrees of Kevin Bacon
Analyzing social networks
Getting the data
Understanding graphs
Implementing the graphs
Measuring social network graphs
Visualizing the graph
Summary
Chapter 2: GIS Analysis – Mapping Climate Change
Understanding GIS
Mapping the climate change
Working with map projections
Working with ArcGIS
Summary
Chapter 3: Topic Modeling – Changing Concerns in the State of the Union Addresses
Understanding data in the State of Union addresses
Understanding topic modeling
Preparing for visualizations
Setting up the project
Getting the data
Summary
Chapter 4: Classifying UFO Sightings
Getting the data
Extracting the data
Dealing with messy data
Visualizing UFO data
Description
Topic modeling descriptions
Hoaxes
Summary
Chapter 5: Benford's Law – Detecting Natural Progressions of Numbers
Learning about Benford's Law
Failing Benford's Law
Case studies
Summary
Chapter 6: Sentiment Analysis – Categorizing Hotel Reviews
Understanding sentiment analysis
Getting hotel review data
Exploring the data
Preparing the data
Cross-validating the results
Calculating error rates
Using the Weka machine learning library
Running the experiment
Examining the results
Improving the results
Summary
Chapter 7: Null Hypothesis Tests – Analyzing Crime Data
Introducing confirmatory data analysis
Understanding null hypothesis testing
Understanding burglary rates
Exploring the data
Conducting the experiment
Interpreting the results
Summary
Chapter 8: A/B Testing – Statistical Experiments for the Web
Defining A/B testing
Conducting an A/B test
Summary
Chapter 9: Analyzing Social Data Participation
Setting up the project
Summary
Chapter 10: Modeling Stock Data
Learning about financial data analysis
Setting up the basics
Getting prepared with data
Analyzing the text
Inspecting the stock prices
Merging text and stock features
Analyzing both text and stock features together with neural nets
Predicting the future
Taking it with a grain of salt
Summary

Book Details

ISBN 139781783284139
Paperback340 pages
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