R Projects For Dummies

1 - Title Page [Seite 3]
2 - Copyright Page [Seite 4]
3 - Table of Contents [Seite 7]
4 - Introduction [Seite 15]
4.1 - About This Book [Seite 16]
4.1.1 - Part 1: The Tools of the Trade [Seite 16]
4.1.2 - Part 2: Interacting with a User [Seite 16]
4.1.3 - Part 3: Machine Learning [Seite 16]
4.1.4 - Part 4: Large(ish) Data Sets [Seite 16]
4.1.5 - Part 5: Maps and Images [Seite 16]
4.1.6 - Part 6: The Part of Tens [Seite 17]
4.2 - What You Can Safely Skip [Seite 17]
4.3 - Foolish Assumptions [Seite 17]
4.4 - Icons Used in This Book [Seite 17]
4.5 - Beyond the Book [Seite 18]
4.6 - Where to Go from Here [Seite 18]
5 - Part 1 The Tools of the Trade [Seite 19]
5.1 - Chapter 1 R: What It Does and How It Does It [Seite 21]
5.1.1 - Getting R [Seite 21]
5.1.2 - Getting RStudio [Seite 22]
5.1.3 - A Session with R [Seite 25]
5.1.3.1 - The working directory [Seite 25]
5.1.3.2 - Getting started [Seite 26]
5.1.4 - R Functions [Seite 29]
5.1.5 - User-Defined Functions [Seite 30]
5.1.6 - Comments [Seite 32]
5.1.7 - R Structures [Seite 32]
5.1.7.1 - Vectors [Seite 32]
5.1.7.2 - Numerical vectors [Seite 33]
5.1.7.3 - Matrices [Seite 35]
5.1.7.4 - Lists [Seite 38]
5.1.7.5 - Data frames [Seite 39]
5.1.8 - Of for Loops and if Statements [Seite 42]
5.2 - Chapter 2 Working with Packages [Seite 45]
5.2.1 - Installing Packages [Seite 45]
5.2.2 - Examining Data [Seite 47]
5.2.2.1 - Heads and tails [Seite 47]
5.2.2.2 - Missing data [Seite 47]
5.2.2.3 - Subsets [Seite 48]
5.2.3 - R Formulas [Seite 49]
5.2.4 - More Packages [Seite 50]
5.2.5 - Exploring the tidyverse [Seite 51]
5.3 - Chapter 3 Getting Graphic [Seite 57]
5.3.1 - Touching Base [Seite 57]
5.3.1.1 - Histograms [Seite 58]
5.3.1.2 - Density plots [Seite 59]
5.3.1.3 - Bar plots [Seite 61]
5.3.1.4 - Grouping the bars [Seite 63]
5.3.1.5 - Quick Suggested Project [Seite 65]
5.3.1.6 - Pie graphs [Seite 67]
5.3.1.7 - Scatterplots [Seite 67]
5.3.1.8 - Scatterplot matrix [Seite 69]
5.3.1.9 - Box plots [Seite 70]
5.3.2 - Graduating to ggplot2 [Seite 71]
5.3.2.1 - How it works [Seite 72]
5.3.2.2 - Histograms [Seite 73]
5.3.2.3 - Bar plots [Seite 75]
5.3.2.4 - Grouped bar plots [Seite 76]
5.3.2.5 - Grouping yet again [Seite 78]
5.3.2.6 - Scatterplots [Seite 81]
5.3.2.7 - The plot thickens . . . [Seite 82]
5.3.2.8 - Scatterplot matrix [Seite 86]
5.3.2.9 - Box plots [Seite 87]
6 - Part 2 Interacting with a User [Seite 91]
6.1 - Chapter 4 Working with a Browser [Seite 93]
6.1.1 - Getting Your Shine On [Seite 93]
6.1.2 - Creating Your First shiny Project [Seite 94]
6.1.2.1 - The user interface [Seite 97]
6.1.2.2 - The server [Seite 98]
6.1.2.3 - Final steps [Seite 99]
6.1.2.4 - Getting reactive [Seite 100]
6.1.3 - Working with ggplot [Seite 103]
6.1.3.1 - Changing the server [Seite 104]
6.1.3.2 - A few more changes [Seite 106]
6.1.3.3 - Getting reactive with ggplot [Seite 108]
6.1.4 - Another shiny Project [Seite 110]
6.1.4.1 - The base R version [Seite 111]
6.1.4.2 - The ggplot version [Seite 118]
6.1.5 - Suggested Project [Seite 120]
6.2 - Chapter 5 Dashboards - How Dashing! [Seite 121]
6.2.1 - The shinydashboard Package [Seite 121]
6.2.2 - Exploring Dashboard Layouts [Seite 122]
6.2.2.1 - Getting started with the user interface [Seite 123]
6.2.2.2 - Building the user interface: Boxes, boxes, boxes . . . [Seite 124]
6.2.2.3 - Lining up in columns [Seite 131]
6.2.2.4 - A nice trick: Keeping tabs [Seite 135]
6.2.2.5 - Suggested project: Add statistics [Seite 139]
6.2.2.6 - Suggested project: Place valueBoxes in tabPanels [Seite 140]
6.2.3 - Working with the Sidebar [Seite 140]
6.2.3.1 - The user interface [Seite 142]
6.2.3.2 - The server [Seite 145]
6.2.3.3 - Suggested project: Relocate the slider [Seite 147]
6.2.4 - Interacting with Graphics [Seite 149]
6.2.4.1 - Clicks, double-clicks, and brushes - oh, my! [Seite 149]
6.2.4.2 - Why bother with all this? [Seite 152]
6.2.4.3 - Suggested project: Experiment with airquality [Seite 155]
7 - Part 3 Machine Learning [Seite 157]
7.1 - Chapter 6 Tools and Data for Machine Learning Projects [Seite 159]
7.1.1 - The UCI (University of California-Irvine) ML Repository [Seite 160]
7.1.1.1 - Downloading a UCI dataset [Seite 160]
7.1.1.2 - Cleaning up the data [Seite 162]
7.1.1.3 - Exploring the data [Seite 164]
7.1.1.4 - Exploring relationships in the data [Seite 166]
7.1.2 - Introducing the Rattle package [Seite 171]
7.1.3 - Using Rattle with iris [Seite 173]
7.1.3.1 - Getting and (further) exploring the data [Seite 173]
7.1.3.2 - Finding clusters in the data [Seite 176]
7.2 - Chapter 7 Decisions, Decisions, Decisions [Seite 181]
7.2.1 - Decision Tree Components [Seite 181]
7.2.1.1 - Roots and leaves [Seite 182]
7.2.1.2 - Tree construction [Seite 182]
7.2.2 - Decision Trees in R [Seite 183]
7.2.2.1 - Growing the tree in R [Seite 183]
7.2.2.2 - Drawing the tree in R [Seite 185]
7.2.3 - Decision Trees in Rattle [Seite 187]
7.2.3.1 - Creating the tree [Seite 188]
7.2.3.2 - Drawing the tree [Seite 189]
7.2.3.3 - Evaluating the tree [Seite 190]
7.2.4 - Project: A More Complex Decision Tree [Seite 191]
7.2.4.1 - The data: Car evaluation [Seite 191]
7.2.4.2 - Data exploration [Seite 193]
7.2.4.3 - Building and drawing the tree [Seite 194]
7.2.4.4 - Evaluating the tree [Seite 195]
7.2.4.5 - Quick suggested project: Understanding the complexity parameter [Seite 195]
7.2.5 - Suggested Project: Titanic [Seite 196]
7.3 - Chapter 8 Into the Forest, Randomly [Seite 199]
7.3.1 - Growing a Random Forest [Seite 199]
7.3.2 - Random Forests in R [Seite 201]
7.3.2.1 - Building the forest [Seite 201]
7.3.2.2 - Evaluating the forest [Seite 203]
7.3.2.3 - A closer look [Seite 204]
7.3.2.4 - Plotting error [Seite 205]
7.3.2.5 - Plotting importance [Seite 207]
7.3.3 - Project: Identifying Glass [Seite 208]
7.3.3.1 - The data [Seite 208]
7.3.3.2 - Getting the data into Rattle [Seite 209]
7.3.3.3 - Exploring the data [Seite 210]
7.3.3.4 - Growing the random forest [Seite 212]
7.3.3.5 - Visualizing the results [Seite 212]
7.3.4 - Suggested Project: Identifying Mushrooms [Seite 214]
7.4 - Chapter 9 Support Your Local Vector [Seite 215]
7.4.1 - Some Data to Work With [Seite 215]
7.4.1.1 - Using a subset [Seite 216]
7.4.1.2 - Defining a boundary [Seite 216]
7.4.1.3 - Understanding support vectors [Seite 217]
7.4.2 - Separability: It's Usually Nonlinear [Seite 219]
7.4.3 - Support Vector Machines in R [Seite 221]
7.4.3.1 - Working with e1071 [Seite 221]
7.4.3.2 - Working with kernlab [Seite 226]
7.4.4 - Project: House Parties [Seite 228]
7.4.4.1 - Reading in the data [Seite 230]
7.4.4.2 - Exploring the data [Seite 231]
7.4.4.3 - Creating the SVM [Seite 232]
7.4.4.4 - Evaluating the SVM [Seite 234]
7.4.5 - Suggested Project: Titanic Again [Seite 234]
7.5 - Chapter 10 K-Means Clustering [Seite 235]
7.5.1 - How It Works [Seite 235]
7.5.2 - K-Means Clustering in R [Seite 237]
7.5.2.1 - Setting up and analyzing the data [Seite 237]
7.5.2.2 - Understanding the output [Seite 238]
7.5.2.3 - Visualizing the clusters [Seite 239]
7.5.2.4 - Finding the optimum number of clusters [Seite 240]
7.5.2.5 - Quick suggested project: Adding the sepals [Seite 243]
7.5.3 - Project: Glass Clusters [Seite 245]
7.5.3.1 - The data [Seite 245]
7.5.3.2 - Starting Rattle and exploring the data [Seite 246]
7.5.3.3 - Preparing to cluster [Seite 247]
7.5.3.4 - Doing the clustering [Seite 248]
7.5.3.5 - Going beyond Rattle [Seite 248]
7.5.4 - Suggested Project: A Few Quick Ones [Seite 249]
7.5.4.1 - Visualizing data points and clusters [Seite 249]
7.5.4.2 - The optimum number of clusters [Seite 250]
7.5.4.3 - Adding variables [Seite 250]
7.6 - Chapter 11 Neural Networks [Seite 251]
7.6.1 - Networks in the Nervous System [Seite 251]
7.6.2 - Artificial Neural Networks [Seite 252]
7.6.2.1 - Overview [Seite 252]
7.6.2.2 - Input layer and hidden layer [Seite 253]
7.6.2.3 - Output layer [Seite 254]
7.6.2.4 - How it all works [Seite 254]
7.6.3 - Neural Networks in R [Seite 255]
7.6.3.1 - Building a neural network for the iris data frame [Seite 255]
7.6.3.2 - Plotting the network [Seite 257]
7.6.3.3 - Evaluating the network [Seite 258]
7.6.3.4 - Quick suggested project: Those sepals [Seite 259]
7.6.4 - Project: Banknotes [Seite 259]
7.6.4.1 - The data [Seite 259]
7.6.4.2 - Taking a quick look ahead [Seite 260]
7.6.4.3 - Setting up Rattle [Seite 261]
7.6.4.4 - Evaluating the network [Seite 263]
7.6.4.5 - Going beyond Rattle: Visualizing the network [Seite 263]
7.6.5 - Suggested Projects: Rattling Around [Seite 265]
8 - Part 4 Large(ish) Data Sets [Seite 267]
8.1 - Chapter 12 Exploring Marketing [Seite 269]
8.1.1 - Project: Analyzing Retail Data [Seite 269]
8.1.1.1 - The data [Seite 270]
8.1.1.2 - RFM in R [Seite 271]
8.1.2 - Enter Machine Learning [Seite 279]
8.1.2.1 - K-means clustering [Seite 279]
8.1.2.2 - Working with Rattle [Seite 281]
8.1.2.3 - Digging into the clusters [Seite 282]
8.1.2.4 - The clusters and the classes [Seite 284]
8.1.2.5 - Quick suggested project [Seite 285]
8.1.3 - Suggested Project: Another Data Set [Seite 286]
8.2 - Chapter 13 From the City That Never Sleeps [Seite 289]
8.2.1 - Examining the Data Set [Seite 289]
8.2.2 - Warming Up [Seite 290]
8.2.2.1 - Glimpsing and viewing [Seite 290]
8.2.2.2 - Piping, filtering, and grouping [Seite 291]
8.2.2.3 - Visualizing [Seite 293]
8.2.2.4 - Joining [Seite 294]
8.2.2.5 - Quick Suggested Project: Airline names [Seite 297]
8.2.3 - Project: Departure Delays [Seite 297]
8.2.3.1 - Adding a variable: weekday [Seite 297]
8.2.3.2 - Quick Suggested Project: Analyze weekday differences [Seite 298]
8.2.3.3 - Delay, weekday, and airport [Seite 299]
8.2.3.4 - Delay and flight duration [Seite 301]
8.2.4 - Suggested Project: Delay and Weather [Seite 303]
9 - Part 5 Maps and Images [Seite 305]
9.1 - Chapter 14 All Over the Map [Seite 307]
9.1.1 - Project: The Airports of Wisconsin [Seite 307]
9.1.1.1 - Dispensing with the preliminaries [Seite 307]
9.1.1.2 - Getting the state geographic data [Seite 308]
9.1.1.3 - Getting the airport geographic data [Seite 309]
9.1.1.4 - Plotting the airports on the state map [Seite 312]
9.1.1.5 - Quick Suggested Project: Another source of airport geographic info [Seite 313]
9.1.2 - Suggested Project 1: Map Your State [Seite 313]
9.1.3 - Suggested Project 2: Map the Country [Seite 313]
9.1.3.1 - Plotting the state capitals [Seite 315]
9.1.3.2 - Plotting the airports [Seite 316]
9.2 - Chapter 15 Fun with Pictures [Seite 319]
9.2.1 - Polishing a Picture: It's magick! [Seite 319]
9.2.1.1 - Reading the image [Seite 320]
9.2.1.2 - Rotating, flipping, and flopping [Seite 321]
9.2.1.3 - Annotating [Seite 322]
9.2.1.4 - Combining transformations [Seite 323]
9.2.1.5 - Quick suggested project: Three F's [Seite 323]
9.2.1.6 - Combining images [Seite 324]
9.2.1.7 - Animating [Seite 325]
9.2.1.8 - Making your own morphs [Seite 326]
9.2.2 - Project: Two Legends in Search of a Legend [Seite 327]
9.2.2.1 - Getting Stan and Ollie [Seite 327]
9.2.2.2 - Combining the boys with the background [Seite 328]
9.2.2.3 - Explaining image_apply() [Seite 328]
9.2.2.4 - Getting back to the animation [Seite 330]
9.2.3 - Suggested Project: Combine an Animation with a Plot [Seite 330]
10 - Part 6 The Part of Tens [Seite 333]
10.1 - Chapter 16 More Than Ten Packages for Your R Projects [Seite 335]
10.1.1 - Machine Learning [Seite 335]
10.1.2 - Databases [Seite 336]
10.1.3 - Maps [Seite 336]
10.1.4 - Image Processing [Seite 338]
10.1.5 - Text Analysis [Seite 338]
10.2 - Chapter 17 More than Ten Useful Resources [Seite 341]
10.2.1 - Interacting with Users [Seite 341]
10.2.2 - Machine Learning [Seite 342]
10.2.3 - Databases [Seite 342]
10.2.4 - Maps and Images [Seite 343]
11 - Index [Seite 345]
12 - EULA [Seite 363]