1 Goal

The goal of this tutorial is to create our first interactive plot using the plotly library.

2 Loading libraries

library(plotly)

3 Data import

# In this tutorial we are going to use the iris dataset
data("iris")
str(iris)

## 'data.frame':    150 obs. of  5 variables:
##  $ Sepal.Length: num  5.1 4.9 4.7 4.6 5 5.4 4.6 5 4.4 4.9 ...
##  $ Sepal.Width : num  3.5 3 3.2 3.1 3.6 3.9 3.4 3.4 2.9 3.1 ...
##  $ Petal.Length: num  1.4 1.4 1.3 1.5 1.4 1.7 1.4 1.5 1.4 1.5 ...
##  $ Petal.Width : num  0.2 0.2 0.2 0.2 0.2 0.4 0.3 0.2 0.2 0.1 ...
##  $ Species     : Factor w/ 3 levels "setosa","versicolor",..: 1 1 1 1 1 1 1 1 1 1 ...

4 Creating a ggplot object

# We are going to make a ggplot plot and the store it in an object
my_plot <- ggplot() + geom_point(data = iris, aes(x = Petal.Width, y = Petal.Length, color = Species)) +
  xlab("Petal Width (cm)")  + ylab("Petal Length (cm)") + theme(plot.title = element_text(hjust = 0.5))


my_plot

5 Creating a plotly object

# Using plotly we can create an interactive plot
# The way to use the ggplotly function is
# ggplotly(ggplot_object)

ggplotly(my_plot)

6 Conclusion

Using the plotly library we can create interactive objects that will help us learn more about our data.