The Orange data frame has 35 rows and 3 columns of records of the growth of orange trees.
data("Orange")
View(Orange)
str(Orange)
## Classes 'nfnGroupedData', 'nfGroupedData', 'groupedData' and 'data.frame': 35 obs. of 3 variables:
## $ Tree : Ord.factor w/ 5 levels "3"<"1"<"5"<"2"<..: 2 2 2 2 2 2 2 4 4 4 ...
## $ age : num 118 484 664 1004 1231 ...
## $ circumference: num 30 58 87 115 120 142 145 33 69 111 ...
## - attr(*, "formula")=Class 'formula' language circumference ~ age | Tree
## .. ..- attr(*, ".Environment")=<environment: R_EmptyEnv>
## - attr(*, "labels")=List of 2
## ..$ x: chr "Time since December 31, 1968"
## ..$ y: chr "Trunk circumference"
## - attr(*, "units")=List of 2
## ..$ x: chr "(days)"
## ..$ y: chr "(mm)"
tr <- Orange$Tree
ag <- Orange$age
cr <- Orange$circumference
library(ggplot2)
ggplot(data = Orange, aes(x=ag, y=cr)) + geom_point()
ggplot(data = Orange, aes(x=ag, y=cr, color=tr)) + geom_point()
### Step 5: For better clearity we will take manual and automatic
seperately
ggplot(data = Orange[Orange$tr <2,], aes(x=ag, y=cr, color=tr)) + geom_point()
### Step 6: To see the averages for the circumference, let us run the
following line.
ggplot(data = Orange[Orange$tr <2,], aes(x=ag, y=cr, color=tr)) + geom_point() + geom_smooth()
## `geom_smooth()` using method = 'loess' and formula = 'y ~ x'
## Conclusion: From the above analysis we can observe that as the age of
the tree growths the circumference of the tree also increase and the
frequency of the tree also increase over the period. as we see the graph
all the lines are in a up trend which indicates that the relation
between age and circumferance is positive.