Clojure Data Analysis Cookbook - Second Edition
eBook - ePub

Clojure Data Analysis Cookbook - Second Edition

Eric Rochester

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eBook - ePub

Clojure Data Analysis Cookbook - Second Edition

Eric Rochester

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Information

Jahr
2015
ISBN
9781784390297

Clojure Data Analysis Cookbook Second Edition


Table of Contents

Clojure Data Analysis Cookbook Second Edition
Credits
About the Author
About the Reviewers
www.PacktPub.com
Support files, eBooks, discount offers, and more
Why subscribe?
Free access for Packt account holders
Preface
What this book covers
What you need for this book
Who this book is for
Conventions
Reader feedback
Customer support
Downloading the example code
Downloading the color images of this book
Errata
Piracy
Questions
1. Importing Data for Analysis
Introduction
Creating a new project
Getting ready
How to do it...
How it works...
Reading CSV data into Incanter datasets
Getting ready
How to do it…
How it works…
There's more…
Reading JSON data into Incanter datasets
Getting ready
How to do it…
How it works…
Reading data from Excel with Incanter
Getting ready
How to do it…
How it works…
Reading data from JDBC databases
Getting ready
How to do it…
How it works…
See also
Reading XML data into Incanter datasets
Getting ready
How to do it…
How it works…
There's more…
Navigating structures with zippers
Processing in a pipeline
Comparing XML and JSON
Scraping data from tables in web pages
Getting ready
How to do it…
How it works…
See also
Scraping textual data from web pages
Getting ready
How to do it…
How it works…
Reading RDF data
Getting ready
How to do it…
How it works…
See also
Querying RDF data with SPARQL
Getting ready
How to do it…
How it works…
There's more…
Aggregating data from different formats
Getting ready
How to do it…
Creating the triple store
Scraping exchange rates
Loading currency data and tying it all together
How it works…
See also
2. Cleaning and Validating Data
Introduction
Cleaning data with regular expressions
Getting ready
How to do it…
How it works…
There's more...
See also
Maintaining consistency with synonym maps
Getting ready
How to do it…
How it works…
See also
Identifying and removing duplicate data
Getting ready
How to do it…
How it works…
There's more…
Regularizing numbers
Getting ready
How to do it…
How it works…
Calculating relative values
Getting ready
How to do it…
How it works…
Parsing dates and times
Getting ready
How to do it…
There's more…
Lazily processing very large data sets
Getting ready
How to do it…
How it works…
Sampling from very large data sets
Getting ready
How to do it…
Sampling by percentage
Sampling exactly
How it works…
Fixing spelling errors
Getting ready
How to do it…
How it works…
There's more…
Parsing custom data formats
Getting ready
How to do it…
How it works…
Validating data with Valip
Getting ready
How to do it…
How it works…
3. Managing Complexity with Concurrent Programming
Introduction
Managing program complexity with STM
Getting ready
How to do it…
How it works…
See also
Managing program complexity with agents
Getting ready
How to do it…
How it works…
See also
Getting better performance with commute
Getting ready
How to do it…
How it works…
Combining agents and STM
Getting ready
How to do it…
How it works…
Maintaining consistency with ensure
Getting ready
How to do it…
How it works…
Introducing safe side effects into the STM
Getting ready
How to do it…
Maintaining data consistency with validators
Getting ready
How to do it…
How it works…
See also
Monitoring processing with watchers
Getting ready
How to do it…
How it works…
Debugging concurrent programs with watchers
Getting ready
How to do it…
There's more...
Recovering from errors in agents
How to do it…
Failing on errors
Continuing on errors
Using a custom error handler
There's more...
Managing large inputs with sized queues
How to do it…
How it works...
4. Improving Performance with Parallel Programming
Introduction
Parallelizing processing with pmap
How to do it…
How it works…
There's more…
See also
Parallelizing processing with Incanter
Getting ready
How to do it…
How it works…
Partitioning Monte Carlo simulations for better pmap performance
Getting ready
How to do it…
How it works…
Estimating with Monte Carlo simulations
Chunking data for pmap
Finding the optimal partition size with simulated annealing
Getting ready
How to do it…
How it works…
There's more…
Combining function calls with reducers
Getting ready
How to do it…
What happened here?
There's more...
See also
Parallelizing with reducers
Getting ready
How to do it…
How it works…
See also
Generating online summary statistics for data streams with reducers
Getting ready
How to do it…
Using type hints
Getting ready
How to do it…
How it works…
See also
Benchmarking with Criterium
Getting ready
How to do it…
How it works…
See also
5. Distributed Data Processing with Cascalog
Introduction
Initializing Cascalog and Hadoop for distributed processing
Getting ready
How to do it…
How it works…
See also
Querying data with Cascalog
Getting ready
How to do it…
How it works…
There's more
Distributing data with Apache HDFS
Getting ready
How to do it…
How it works…
Parsing CSV files with Cascalog
Getting ready
How to do it…
How it works…
There's more
Executing complex queries with Cascalog
Getting ready
How to do it…
Aggregating data with Cascalog
Getting ready
How to do it…
There's more
Defining new Cascalog operators
Getting ready
How to do it…
Creating map operators
Creating map concatenation operators
Creating filter operators
C...

Inhaltsverzeichnis