require(ggplot2)
## Loading required package: ggplot2
## Warning: package 'ggplot2' was built under R version 3.1.3
library(ggplot2)
library(plot3D)
## Warning: package 'plot3D' was built under R version 3.1.3
library(scatterplot3d)
## Warning: package 'scatterplot3d' was built under R version 3.1.3

I took the summary table that Honey, Vuthy, James, and Sonya had created and added few graphics as well

Please note that i only took the summary with the below following columns: Category.Nominations, Count, Category.Winners, Count

Also, I loaded and shared the table as csv using dropconvas website as per below

data1<- read.table(file= "http://dropcanvas.com/dcm0h/1", header = TRUE, sep=",")
str(data1)
## 'data.frame':    16 obs. of  4 variables:
##  $ Category.Nominations: Factor w/ 16 levels "ACTOR – LEADING ROLE",..: 16 8 9 1 2 6 11 5 13 4 ...
##  $ Count               : int  80 78 69 59 55 54 50 48 45 36 ...
##  $ Category.Winners    : Factor w/ 16 levels "ACTOR – LEADING ROLE",..: 8 16 9 5 1 6 11 13 7 2 ...
##  $ Count.1             : int  61 56 33 27 26 25 24 23 19 15 ...
head(data1)
##      Category.Nominations Count     Category.Winners Count.1
## 1                 WRITING    80            DIRECTING      61
## 2               DIRECTING    78              WRITING      56
## 3            FILM EDITING    69         FILM EDITING      33
## 4    ACTOR – LEADING ROLE    59        ART DIRECTION      27
## 5 ACTOR – SUPPORTING ROLE    55 ACTOR – LEADING ROLE      26
## 6          CINEMATOGRAPHY    54       CINEMATOGRAPHY      25

Distribution Nominations By Category

Distribution of Winning By Category

Distribution of Wins over Winning by Nominations Category

attach(data1) 
scatterplot3d(Category.Nominations, Category.Winners, Count.1, pch=16, highlight.3d=TRUE,
               type="h", main="Distribution of Wins over Winning by Nominations Category",
               xlab = "Category.Nominations", ylab = "Winning Category", zlab = " Winners")