Scatter plot showing multiple variables that visualize the departure delays for three major airport and the extent of delay at detination

mpg dataset

mpg dataset

mpg dataset

adding too many aesthetic mappings to a plot makes it cluttered and difficult to make sense of. Another way, which is particularly useful for categorical variables, is to split your plot into facets, subplots that each display one subset of the data. To facet your plot by a single variable, use facet_wrap(). The first argument of facet_wrap() is a formula3, which you create with ~ followed by a variable name. The variable that you pass to facet_wrap() should be categorical.

adding too many aesthetic mappings to a plot makes it cluttered and difficult to make sense of. Another way, which is particularly useful for categorical variables, is to split your plot into facets, subplots that each display one subset of the data

The second plot, a relative frequency plot created by setting position = "fill" in the geom, is more useful for comparing species distributions across islands since it’s not affected by the unequal numbers of penguins. In creating these bar charts, we map the variable that will be separated into bars to the x aesthetic, and the variable that will change the colors inside the bars to the fill aesthetic.

Database = diamonds library = ggplot2

using diamonds database and ggplot2 library

diamonds dataset and ggplot2 library

to ascertain the shape of the individual distributions

diamonds dataset in ggplot

diamonds dataset

histogram density plot for carats variable in diamond dataset

diamonds dataset - histogram bins

How are the following two plots different? Which aesthetic, color or fill, is more useful for changing the color of bars?

Run this code in your head and predict what the output will look like. Then, run the code in R and check your predictions.

Recreate the following visualization. What aesthetic should bill_depth_mm be mapped to? And should it be mapped at the global level or at the geom level?

Q.4 What happens if you make a scatterplot of species vs. bill_depth_mm? What might be a better choice of geom?

Palmer penguins dataset Q3. Make a scatterplot of bill_depth_mm vs. bill_length_mm. That is, make a scatterplot with bill_depth_mm on the y-axis and bill_length_mm on the x-axis. Describe the relationship between these two variables.

Based on the palmerpenguin library dataset