Clojure Data Analysis Cookbook -- Table of Contents -- Clojure Data Analysis Cookbook -- 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 -- 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… -- See also -- 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… -- 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 -- Reading RDF data with SPARQL -- Getting ready -- How to do it… -- How it works… -- See also -- 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… -- 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… -- Normalizing numbers -- Getting ready -- How to do it… -- How it works… -- Rescaling values -- Getting ready -- How to do it… -- How it works… -- Normalizing 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 -- 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… -- There's more... -- 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 -- Tracking 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 input 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… -- Parallelizing with reducers -- Getting ready -- How to do it… -- How it works… -- There's more... -- See also -- Generating online summary statistics with reducers -- Getting ready -- How to do it… -- Harnessing your GPU with OpenCL and Calx -- Getting ready -- How to do it… -- How it works… -- Writing the GPU code in C -- Wrapping it in Calx -- There's more… -- 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… -- There's more… -- 5. Distributed Data Processing with Cascalog -- Introduction -- Distributed processing with Cascalog and Hadoop -- 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… -- 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 operations -- Creating filter operators -- Creating buffer operators -- Creating aggregate operators -- Creating parallel aggregate operators -- Composing Cascalog queries -- Getting ready -- How to do it… -- How it works… -- Handling errors in Cascalog workflows -- Getting ready -- How to do it… -- Transforming data with Cascalog -- Getting ready -- How to do it… -- How it works… -- Executing Cascalog queries in the Cloud with Pallet -- Getting ready -- How to do it... -- How it works... -- 6. Working with Incanter Datasets -- Introduction -- Loading Incanter's sample datasets -- Getting ready -- How to do it… -- How it works… -- There's more... -- Loading Clojure data structures into datasets -- Getting ready -- How to do it… -- How it works… -- See also -- Viewing datasets interactively with view -- Getting ready -- How to do it… -- How it works… -- See also -- Converting datasets to matrices -- Getting ready -- How to do it… -- How it works… -- There's more… -- See also -- Using infix formulas in Incanter -- Getting ready -- How to do it… -- How it works… -- Selecting columns with -- Getting ready -- How to do it… -- How it works… -- There's more… -- See also -- Selecting rows with -- Getting ready -- How to do it… -- How it works… -- Filtering datasets with where -- Getting ready -- How to do it… -- How it works… -- There's more… -- Grouping data with group-by -- Getting ready -- How to do it… -- How it works… -- Saving datasets to CSV and JSON -- Getting ready -- How to do it… -- Saving data as CSV -- Saving data as JSON.

How it works… -- See also -- Projecting from multiple datasets with join -- Getting ready -- How to do it… -- How it works… -- 7. Preparing for and Performing Statistical Data Analysis with Incanter -- Introduction -- Generating summary statistics with rollup -- Getting ready -- How to do it… -- How it works… -- Differencing variables to show changes -- Getting ready -- How to do it… -- How it works… -- Scaling variables to simplify variable relationships -- Getting ready -- How to do it… -- How it works… -- Working with time series data with Incanter Zoo -- Getting ready -- How to do it… -- There's more... -- Smoothing variables to decrease noise -- Getting ready -- How to do it… -- How it works… -- Validating sample statistics with bootstrapping -- Getting ready -- How to do it… -- How it works… -- There's more… -- Modeling linear relationships -- Getting ready -- How to do it… -- How it works… -- There's more… -- Modeling non-linear relationships -- Getting ready -- How to do it… -- How it works... -- Modeling multimodal Bayesian distributions -- Getting ready -- How to do it… -- How it works… -- There's more... -- Finding data errors with Benford's law -- Getting ready -- How to do it… -- How it works… -- There's more… -- 8. Working with Mathematica and R -- Introduction -- Setting up Mathematica to talk to Clojuratica for Mac OS X and Linux -- Getting ready -- How to do it… -- How it works… -- There's more… -- Setting up Mathematica to talk to Clojuratica for Windows -- Getting ready -- How to do it... -- How it works... -- Calling Mathematica functions from Clojuratica -- Getting ready -- How to do it… -- How it works… -- Sending matrices to Mathematica from Clojuratica -- Getting ready -- How to do it… -- How it works… -- Evaluating Mathematica scripts from Clojuratica -- Getting ready -- How to do it… -- How it works….

Creating functions from Mathematica.