Practical data science cookbook : 89 hands-on recipes to help you complete real-world data science projects in R and Python /: 89 hands-on recipes to help you complete real-world data science projects in R and Python. (2014)

• Record Type: Book
• Further Information: Note: Tony Ojeda, Sean Patrick Murphy, Benjamin Bengfort, Abhijit Dasgupta.
• Authors: Ojeda, Tony; Murphy, Sean Patrick; Bengfort, Benjamin; Dasgupta, Abhijit
• Contents: Cover; Copyright; Credits; About the Authors; About the Reviewers; www.PacktPub.com; Table of Contents; Preface; Chapter 1: Preparing Your Data Science Environment; Introduction; Understanding the data science pipeline; Installing R on Windows, Mac OS X, and Linux; Installing libraries in R and RStudio; Installing Python on Linux and Mac OS X; Installing Python on Windows; Installing the Python data stack on Mac OS X and Linux; Installing extra Python packages; Installing and using virtualenv; Chapter 2: Driving Visual Analysis with Automobile Data (R); Introduction. Acquiring automobile fuel efficiency dataPreparing R for your first project; Importing automobile fuel efficiency data into R; Exploring and describing the fuel efficiency data; Analyzing automobile fuel efficiency over time; Investigating the makes and models of automobiles; Chapter 3: Simulating American Football Data (R); Introduction; Acquiring and cleaning football data; Analyzing and understanding football data; Constructing indexes to measure offensive and defensive strength; Simulating a single game with outcomes decided by calculations. Simulating multiple games with outcomes decided by calculationsChapter 4: Modeling Stock Market Data (R); Introduction; Acquiring stock market data; Summarizing the data; Cleaning and exploring the data; Generating relative valuations; Screening stocks and analyzing historical prices; Chapter 5: Visually Exploring Employment Data (R); Introduction; Preparing for analysis; Importing employment data into R; Exploring the employment data; Obtaining and merging additional data; Adding geographical information; Extracting state- and county-level wage and employment information. Visualizing geographical distributions of payExploring where the jobs are, by industry; Animating maps for a geospatial time series; Benchmarking performance for some common tasks; Chapter 6: Creating Application-oriented Analyses Using Tax Data (Python); Introduction; Preparing for the analysis of top incomes; Importing and exploring the world top incomes dataset; Analyzing and visualizing U.S. top income data; Furthering the analysis of U.S. top income groups; Reporting with Jinja2; Chapter 7: Driving Visual Analyses with Automobile Data (Python); Introduction; Getting started with IPython. Exploring IPython NotebookPreparing to analyze automobile fuel efficiencies; Exploring and describing the fuel efficiency data; Analyzing automobile fuel efficiency over time; Investigating the makes and models of automobiles; Chapter 8: Working with Social Graphs (Python); Introduction; Preparing to work with social networks in Python; Importing networks; Exploring subgraphs within a heroic network; Finding the strong ties; Finding key players; Exploring the characteristics of entire networks; Clustering and community detection in social networks; Visualizing graphs.
• Publisher Details: Birmingham : Packt Publishing
• Publication Date: 2014
• Extent: 1 online resource
• Subjects: 005.117; COMPUTERS -- Mathematical & Statistical Software; Object-oriented programming (Computer science); Data mining; Mathematical statistics -- Data processing; Python (Computer program language); R (Computer program language); COMPUTERS -- Programming -- General; Data mining; Mathematical statistics -- Data processing; Object-oriented programming (Computer science); Python (Computer program language); R (Computer program language); COMPUTERS -- Programming Languages -- Python; COMPUTERS -- Programming -- Open Source; COMPUTERS -- Programming Languages -- General; Electronic books
• Languages: English
• ISBNs: 9781783980253; 1783980257; 9781322166063; 1322166064
• Related ISBNs: 1783980249; 9781783980246
• Notes: Note: Print version record.
• Access Rights: Legal Deposit; Only available on premises controlled by the deposit library and to one user at any one time; The Legal Deposit Libraries (Non-Print Works) Regulations (UK).
• Access Usage: Restricted: Printing from this resource is governed by The Legal Deposit Libraries (Non-Print Works) Regulations (UK) and UK copyright law currently in force.