| Description |
1 online resource (391 p.) |
| Series |
Chapman and Hall/CRC the R Ser |
|
Chapman and Hall/CRC the R Ser
|
| Contents |
Cover -- Half Title -- Series Page -- Title Page -- Copyright Page -- Dedication -- Contents -- Preface -- 1. Introduction -- 1.1. What is R? -- 1.2. Why R? -- 1.3. Why this book? -- 1.4. What are development and conservation? -- 1.5. Science and decision making -- 1.6. Why data science is important -- 1.6.1. Monitoring and evaluation -- 1.6.2. Projects versus programmes -- 1.6.3. Project delivery versus research projects -- 1.7. The goal of this book -- 1.8. How this book is organised -- 1.9. How code is organised in this book -- I: Basics -- 2. Inference and Evidence -- 2.1. Inference |
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2.2. Study design -- 2.3. Evidence -- 2.4. What makes good data? -- 2.5. Recommended resources -- 2.6. Summary -- 3. Data integration in project management -- 3.1. Adaptive management cycles -- 3.2. The Deming cycle -- 3.2.1. Plan -- 3.2.1.1. Development of a project strategy and proposal -- 3.2.1.2. Proposal submission process -- 3.2.1.3. What is a logframe? -- 3.2.1.4. Logframe terminology -- 3.2.1.5. Pre-implementation planning -- 3.2.2. Train -- 3.2.3. Do -- 3.2.4. Check -- 3.2.5. Act -- 3.3. Challenges -- 3.4. Recommended resources -- 3.5. Summary -- 4. Getting started in R |
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4.1. Installing R -- 4.2. Installing RStudio -- 4.3. The R interface -- 4.3.1. The console -- 4.3.2. Version information -- 4.3.3. Writing code in the console -- 4.3.4. Script editors -- 4.3.5. Using the default script editor -- 4.3.6. Using RStudio -- 4.4. R as a calculator -- 4.5. How R works -- 4.5.1. Objects -- 4.5.2. Functions -- 4.5.2.1. Getting help on functions -- 4.5.3. Packages -- 4.5.3.1. Getting help on packages -- 4.6. Writing meaningful code -- 4.7. Reproducibility -- 4.8. Recommended resources -- 4.9. Summary -- 5. Introduction to data frames -- 5.1. Making data frames |
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5.2. Importing a data frame -- 5.3. Saving a data frame -- 5.4. Investigating a data frame -- 5.5. Other functions to examine an R object -- 5.6. Subsetting using the ̀[' and ̀]' operators -- 5.7. Descriptive statistics -- 5.8. Viewing data frames -- 5.9. Making a reproducible example -- 5.9.1. Reproducible example steps -- 5.10. Recommended resources -- 5.11. Summary -- 6. The Waihi project -- 6.1. The scenario -- 6.1.1. Why evidence is important -- 6.2. The data -- 6.2.1. Description of condev data sets -- 6.3. Recommended resources -- 6.4. Summary -- II: First steps |
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7. ggplot2: graphing with the tidyverse -- 7.1. Why graph? -- 7.2. The tidyverse package -- 7.3. The data -- 7.4. Graphing in R -- 7.4.1. Making a ggplot -- 7.4.2. Scatter plots -- 7.4.3. Bar plots -- 7.4.4. Histograms -- 7.4.5. Box plots -- 7.4.6. Polygons -- 7.4.7. Other common geoms -- 7.5. How to save a ggplot -- 7.6. Recommended resources -- 7.7. Summary -- 8. Customising a ggplot -- 8.1. Why customise a ggplot? -- 8.2. The packages -- 8.3. The data -- 8.4. Families of layers -- 8.5. Aesthetics properties -- 8.5.1. Settings aesthetics -- 8.5.2. A quick note about colour |
| Notes |
Description based upon print version of record |
|
8.5.3. Using aesthetics to distinguish groups |
| Subject |
R (Computer program language)
|
|
Mathematical statistics -- Data processing.
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Conservation projects (Natural resources) -- Data processing
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| Form |
Electronic book
|
| ISBN |
9780429552786 |
|
0429552785 |
|
