R Notebook Prepared by Ahmed Muhammad

The question asks for one plot that shows the top ten appropriations with the highest dollar increase in current-year budget between budget years 2019 and 2020, and the second plot is the same except it shows the top ten appropriations with the highest percentage year over year increase.

To make these plots, I used group_by to separate my data first into APPROPRIATION and then by BFY. Then, I used summarize to find the sum of each group. Then, I used spread to get my data in a position where I can use mutate to find the dollar amount change for plot 1, and the percent change for plot 2. Next, I removed Appropriations that had a non-zero value in one of the years, and a zero value in the other. This would greatly skew both are plots because any appropriation that goes from 0 to a dollar figure will be augmented in its increased value. Then, I stored the top 10 values into a data frame that is ready for plotting without any changes. I chose to hide all the code except for the plot commands as to give an organized look.

Question 1

p1 <- ggplot(data = d1plot) + 
  geom_bar(aes(x = reorder(APPROPRIATION, difference), y = difference), stat = "identity")+
  coord_flip() + 
  ggtitle("Top 10 Appropriations with Highest Dollar Change Increase") + 
  labs(y= "Dollar Amount Difference", x = "Appropriation") + 
  scale_y_continuous(labels = dollar)

p1

This first plot shows the top 10 highest dollar amount increases in Appropriations. I flipped the coordinates and used the scale() library to but my y axis in dollar figures.

Question 2

p2 <- ggplot(data = d2plot) + 
  geom_bar(aes(x = reorder(APPROPRIATION, percentChange), y = percentChange), stat = "identity")+
  coord_flip() + 
  ggtitle("Top 10 Appropriations with Highest Percentage Increase") + 
  labs(y= "Percent Change", x = "Appropriation") + 
  scale_y_continuous(labels = percent)

p2

This second plot shows the top 10 highest percent change increases in Appropriations.I flipped the coordinates and used the scale() library to but my y axis in percent figures.