DATA 607 Assignment 1
Assignment Instructions
Mushrooms Dataset. A famous—if slightly moldy—dataset about mushrooms can be found in the UCI repository here: https://archive.ics.uci.edu/ml/datasets/Mushroom.
Your task is to study the dataset and the associated description of the data (i.e. “data dictionary”). You may need to look around a bit, but it’s there! You should take the data, and create a data frame with a subset of the columns in the dataset. You should include the column that indicates edible or poisonous and three or four other columns. You should also add meaningful column names and replace the abbreviations used in the data—for example, in the appropriate column, “e” might become “edible.” Your deliverable is the R code to perform these transformation tasks.
Please place your solution into a single R Markdown (.Rmd) file and publish your solution out to rpubs.com. You should post the .Rmd file in your GitHub repository, and provide the appropriate URLs to your GitHub repository and your rpubs.com file in your assignment link. You should also have the original data file accessible through your code—for example, stored in a GitHub repository and referenced in your code.
Load the Data into R
library(RCurl) ## Loading required package: bitopsx <- getURL("https://raw.githubusercontent.com/betsyrosalen/DATA_607_Data_Acquisition_and_Management/master/Assignment1/Mushrooms/agaricus-lepiota.csv")
mushrooms <-data.frame(read.csv(text=x, header=FALSE))
dim(mushrooms)## [1] 8124 23head(mushrooms, 3)## V1 V2 V3 V4 V5 V6 V7 V8 V9 V10 V11 V12 V13 V14 V15 V16 V17 V18 V19 V20
## 1 p x s n t p f c n k e e s s w w p w o p
## 2 e x s y t a f c b k e c s s w w p w o p
## 3 e b s w t l f c b n e c s s w w p w o p
## V21 V22 V23
## 1 k s u
## 2 n n g
## 3 n n mCreate Header Row
mushrooms_dictionary <- read.table("https://raw.githubusercontent.com/betsyrosalen/DATA_607_Data_Acquisition_and_Management/master/Assignment1/Mushrooms/Data_Dictionary.txt",row.names = 1, sep=":", header=FALSE, quote="")
row.names(mushrooms_dictionary)## [1] "classes" "cap-shape"
## [3] "cap-surface" "cap-color"
## [5] "bruises?" "odor"
## [7] "gill-attachment" "gill-spacing"
## [9] "gill-size" "gill-color"
## [11] "stalk-shape" "stalk-root"
## [13] "stalk-surface-above-ring" "stalk-surface-below-ring"
## [15] "stalk-color-above-ring" "stalk-color-below-ring"
## [17] "veil-type" "veil-color"
## [19] "ring-number" "ring-type"
## [21] "spore-print-color" "population"
## [23] "habitat"names(mushrooms) <- row.names(mushrooms_dictionary)
head(mushrooms, 3)## classes cap-shape cap-surface cap-color bruises? odor gill-attachment
## 1 p x s n t p f
## 2 e x s y t a f
## 3 e b s w t l f
## gill-spacing gill-size gill-color stalk-shape stalk-root
## 1 c n k e e
## 2 c b k e c
## 3 c b n e c
## stalk-surface-above-ring stalk-surface-below-ring stalk-color-above-ring
## 1 s s w
## 2 s s w
## 3 s s w
## stalk-color-below-ring veil-type veil-color ring-number ring-type
## 1 w p w o p
## 2 w p w o p
## 3 w p w o p
## spore-print-color population habitat
## 1 k s u
## 2 n n g
## 3 n n mSubset the Data for Class, Gill Characteristics, and Spore Color
levels(mushrooms$classes)## [1] "e" "p"gills_spores <- mushrooms[c(1,7:10,21)]
dim(gills_spores)## [1] 8124 6Rename Data Levels in Subsetted Dataframe
I commented out the code that returns the values in the dictionary because I spent hours on this section and can’t figure out how to print/return just the value that is in the location without also printing the list of all 21 factor levels each time or how to use that directly to rename the factor levels in the gills_spores dataframe.
v1 <- mushrooms_dictionary$V2[1]
v7 <- mushrooms_dictionary$V2[7]
v8 <- mushrooms_dictionary$V2[8]
v9 <- mushrooms_dictionary$V2[9]
v10 <- mushrooms_dictionary$V2[10]
v21 <- mushrooms_dictionary$V2[21]
#v1
#v7
#v8
#v9
#v10
#v21
levels(gills_spores$classes) <- list("edible"="e","poisonous"="p")
levels(gills_spores$`gill-attachment`) <- list("attached"="a","descending"="d","free"="f","notched"="n")
levels(gills_spores$`gill-spacing`) <- list("close"="c","crowded"="w","distant"="d")
levels(gills_spores$`gill-size`) <- list("broad"="b","narrow"="n")
levels(gills_spores$`gill-color`) <- list("black"="k","brown"="n","buff"="b","chocolate"="h","gray"="g","green"="r","orange"="o","pink"="p","purple"="u","red"="e","white"="w","yellow"="y")
levels(gills_spores$`spore-print-color`) <- list("black"="k","brown"="n","buff"="b","chocolate"="h","green"="r","orange"="o","purple"="u","white"="w","yellow"="y")
head(gills_spores)## classes gill-attachment gill-spacing gill-size gill-color
## 1 poisonous free close narrow black
## 2 edible free close broad black
## 3 edible free close broad brown
## 4 poisonous free close narrow brown
## 5 edible free crowded broad black
## 6 edible free close broad brown
## spore-print-color
## 1 black
## 2 brown
## 3 brown
## 4 black
## 5 brown
## 6 blackFurther Subset the Data by Class
edible <- subset(gills_spores, classes == 'edible')
poisonous <- subset(gills_spores, classes == 'poisonous')
dim(edible)## [1] 4208 6dim(poisonous)## [1] 3916 6summary(edible)## classes gill-attachment gill-spacing gill-size
## edible :4208 attached : 192 close :3008 broad :3920
## poisonous: 0 descending: 0 crowded:1200 narrow: 288
## free :4016 distant: 0
## notched : 0
##
##
##
## gill-color spore-print-color
## white :956 brown :1744
## brown :936 black :1648
## pink :852 white : 576
## purple :444 buff : 48
## black :344 chocolate: 48
## gray :248 orange : 48
## (Other):428 (Other) : 96summary(poisonous)## classes gill-attachment gill-spacing gill-size
## edible : 0 attached : 18 close :3804 broad :1692
## poisonous:3916 descending: 0 crowded: 112 narrow:2224
## free :3898 distant: 0
## notched : 0
##
##
##
## gill-color spore-print-color
## buff :1728 white :1812
## pink : 640 chocolate:1584
## chocolate: 528 black : 224
## gray : 504 brown : 224
## white : 246 green : 72
## brown : 112 buff : 0
## (Other) : 158 (Other) : 0Plot Some Data!
Spore Print Color of Edible Mushrooms
plot(edible$`spore-print-color`, las=3)
Spore Print Color of Poisonous Mushrooms
plot(poisonous$`spore-print-color`, las=3)
Gill Color of Edible Mushrooms
plot(edible$`gill-color`, las=3)
Gill Color of Poisonous Mushrooms
plot(poisonous$`gill-color`, las=3)
There’s probably a better plot for this, but it was the best I could do for now…
I am trying to show the correlation between the combination of gill color and spore print color and whether a mushroom is edible or not.
library(ggplot2)
ggplot(data = gills_spores) +
geom_jitter(mapping = aes(x = `gill-color`, y = `spore-print-color`, color = classes))