This is the first in a series on R Markdown, which is part of a series of mini-seminars at ICRAF on reproducible analysis.
In this session we introduce R Notebooks with a simple example.
Tree growth analysis
Loblolly pine
This is an R Markdown Notebook. When you execute code within the notebook, the results appear beneath the code.
Photo of a stand of Loblolly pine
Introduction
In this exercise we will be working with data that is already part of your R installation. The Loblolly pine data can be loaded using data(“Loblolly”).
library(ggplot2)
library(dplyr)
Now let’s load the data
data("Loblolly")
head(Loblolly)
## height age Seed
## 1 4.51 3 301
## 15 10.89 5 301
## 29 28.72 10 301
## 43 41.74 15 301
## 57 52.70 20 301
## 71 60.92 25 301
unique(levels(Loblolly$Seed))
## [1] "329" "327" "325" "307" "331" "311" "315" "321" "319" "301" "323"
## [12] "309" "303" "305"
Let’s visualize the data using ggplot2
ggplot(Loblolly) + geom_point(aes(x=age, y=height, colour=Seed)) + stat_smooth(aes(x=age, y=height, colour=Seed))
ggplot(Loblolly %>% filter(Seed == 305 | Seed == 327)) + geom_point(aes(x=age, y=height, colour=Seed)) + stat_smooth(aes(x=age, y=height, colour=Seed))
# Filtering by Seed source/type
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