Module #6: Basic Graphic with RStudio
When spotting differences it is essential to classify or group units into categories and then from there one can find the outliers or standouts. What we are trying to do is to look at each variable for differences while also seeing the differences across all variables.
This week we used RStudio to create a visual. I decided to play around with the mtcars dataset that comes with the r programming language.
x <- setNames(mtcars$mpg[1:6], row.names(mtcars)[1:6])
pie(x)
Above is the code I used and below is the result.
I realized this visual didn’t do a good job of showing the value differences so I created a more descriptive one.
This visual is more descriptive and it allows us to easily see that the highest percentage of cars have 1, 3, and 4 carburators respectively.
