Visualizing Fuel Efficiency Deviation

I created a diverging bar chart showing how each car's MPG compares to the dataset average of 20.09. Blue bars indicate above-average performers, coral bars show below-average ones. The zero line marks the mean, making deviations immediately visible.

This chart reveals clear differences between groups: fuel-efficient compact cars cluster on the right (Toyota Corolla at +13.8 MPG) while heavy luxury vehicles dominate the left (Cadillac Fleetwood at 9.7 MPG). The deviation from the benchmark is the chart's core feature: the sorted arrangement and contrasting colors let you spot outliers instantly, which connects to Yau's point about making interesting data points stand out. The color coding does the heavy lifting here, letting viewers categorize performance without reading every number. 

The biggest challenge was the overlapping car names along the x-axis; they're hard to read in places. More importantly, the chart shows which cars deviate but not why. Adding variables like cylinder count or weight might explain these patterns, though that would sacrifice the simplicity that makes quick comparisons possible.




Comments

Post a Comment

Popular posts from this blog

R Programming Journal - Omar Hamad

Image
  RStudio Installation Experience Yesterday, I switched from Windows to Mac, which was new for me. Installing R and RStudio on macOS  It was simple, but I had to change some security settings in my Mac to allow the software to run.  I downloaded the correct files from the official sites, installed them, and opened RStudio successfully.  What is an R Vector? An R vector is a basic data structure that stores a sequence of elements all of the same type, such as  numbers, words, or logical values. It’s a core part of R because it allows you to organize and work with  data efficiently. Vectors are the foundation for many operations in R, making data manipulation and  analysis faster and easier. Vectors are essential in R because they enable you to perform operations on entire collections of data at  once, rather than handling each element individually. This makes your code more concise and efficient.  Understanding vectors is crucial because most ...
Read more

Assignment 6

Code: # Task 1: Matrix Addition & Subtraction A = matrix(c(2, 0, 1, 3), ncol = 2) B = matrix(c(5, 2, 4, -1), ncol = 2) cat("Matrix A:\n") print(A) cat("\nMatrix B:\n") print(B) A_plus_B = A + B cat("\nA + B:\n") print(A_plus_B) A_minus_B = A - B cat("\nA - B:\n") print(A_minus_B) # Task 2: Create a Diagonal Matrix D = diag(c(4, 1, 2, 3)) cat("\nDiagonal Matrix D:\n") print(D) # Task 3: Construct a Custom 5x5 Matrix first_col = c(3, 2, 2, 2, 2) remaining_block = rbind(   c(1, 1, 1, 1),   diag(3, 4) ) custom_matrix = cbind(first_col, remaining_block) cat("\nCustom 5x5 Matrix:\n") print(custom_matrix) Output: > # Task 1: Matrix Addition & Subtraction > A = matrix(c(2, 0, 1, 3), ncol = 2) > B = matrix(c(5, 2, 4, -1), ncol = 2) > cat("Matrix A:\n") Matrix A: > print(A)      [,1] [,2] [1,]    2    1 [2,]    0    3 > cat("\nMatrix B:\n") Matrix B: > print(B)      [,1] [,2] [1,]   ...
Read more

Generic Functions in R

What I Did   This assignment helped me learn how R's generic functions work and the difference between S3 and S4 objects. I used the mtcars dataset to see how functions change behavior based on what kind of object they're working with.   Loading the Dataset   First, I loaded mtcars data(" mtcars ") head( mtcars ) str( mtcars )   This dataset has 11 columns with things like miles per gallon, horsepower, Etc . How Generic Functions Work   I tested some basic R functions to see how they adapt to different objects:   summary( mtcars ) plot( mtcars )   lm_model = lm (mpg ~ wt + hp, data = mtcars ) summary( lm_model )   What I noticed: when you run summary( ) on a data frame, you get min/max/mean values. But when you run it on a linear model, you get totally different outputs, like coefficients and p-values. Same function name, different behavior!   Creating S3 Objects   S3 is the simpler object system. Here's how I made one:   s3...
Read more