R for Everyone Advanced Analytics and Graphics
Publication details: Noida Pearson Education 2023 Edition: 2Description: 528ISBN: 978-9386873521Subject(s): Computer ScienceDDC classification: 006.31 LAN/R Summary: Contents Chapter 1: Getting R Chapter 2: The R Environment Chapter 3: R Packages Chapter 4: Basics of RChapter 5: Advanced Data StructuresChapter 6: Reading Data into RChapter 7: Statistical Graphics Chapter 8: Writing R functionsChapter 9: Control Statements Chapter 10: Loops, the Un-R Way to IterateChapter 11: Group ManipulationChapter 12: Faster Group Manipulation with dplyrChapter 13: Iterating with purrChapter 14: Data ReshapingChapter 15: Reshaping Data in the TidyverseChapter 16: Manipulating Strings Chapter 17: Probability Distributions Chapter 18: Basic StatisticsChapter 19: Linear ModelsChapter 20: Generalized Linear Models Chapter 21: Model DiagnosticsChapter 22: Regularization and ShrinkageChapter 23: Nonlinear ModelsChapter 24: Time Series and AutocorrelationChapter 25: ClusteringChapter 26: Model Fitting with CaretChapter 27: Reproducibility and Reports with knitrChapter 28: Rich Documents with RMarkdownChapter 29: Interactive Dashboards with ShinyChapter 30: Building R PackagesAppendix A: Real-Life Resources| Item type | Home library | Call number | Materials specified | Status | Date due | Barcode |
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Parvatibai Chowgule College of Arts and Science, Margao Computer Science | 006.31 LAN/R (Browse shelf(Opens below)) | Available | PCC-49454 |
Contents Chapter 1: Getting R Chapter 2: The R Environment Chapter 3: R Packages Chapter 4: Basics of RChapter 5: Advanced Data StructuresChapter 6: Reading Data into RChapter 7: Statistical Graphics Chapter 8: Writing R functionsChapter 9: Control Statements Chapter 10: Loops, the Un-R Way to IterateChapter 11: Group ManipulationChapter 12: Faster Group Manipulation with dplyrChapter 13: Iterating with purrChapter 14: Data ReshapingChapter 15: Reshaping Data in the TidyverseChapter 16: Manipulating Strings Chapter 17: Probability Distributions Chapter 18: Basic StatisticsChapter 19: Linear ModelsChapter 20: Generalized Linear Models Chapter 21: Model DiagnosticsChapter 22: Regularization and ShrinkageChapter 23: Nonlinear ModelsChapter 24: Time Series and AutocorrelationChapter 25: ClusteringChapter 26: Model Fitting with CaretChapter 27: Reproducibility and Reports with knitrChapter 28: Rich Documents with RMarkdownChapter 29: Interactive Dashboards with ShinyChapter 30: Building R PackagesAppendix A: Real-Life Resources
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