Assignment Basic Loading and Transformation R Markdown

# DATA 607 Week 1 Assignment - Loading Data into a Data Frame
# Student Name: Kalyan (Kalyanaraman Parthasarathy)

# Read agaricus-lepiota.data
dataset <- read.csv("https://archive.ics.uci.edu/ml/machine-learning-databases/mushroom/agaricus-lepiota.data")

# Following are the general inspections of the data set
# Data Inspection
class(dataset)

# Number of columns in the data set
length(dataset)

# Number of rows in the data set
nrow(dataset)

dim(dataset)

# Structure
str(dataset)

# Naming the columns of the data frame - Used the file "agaricus-lepiota.names" to get 
# the names for the columns except for the first column which I named it as "Edibleness"
colnames(dataset) <- c(
  "Edibleness"
  , "cap-shape"
  , "cap-surface"
  , "cap-color"
  , "bruises?"
  , "odor"
  , "gill-attachment"
  , "gill-spacing"
  , "gill-size"
  , "gill-color"
  , "stalk-shape"
  , "stalk-root"
  , "stalk-surface-above-ring"
  , "stalk-surface-below-ring"
  , "stalk-color-above-ring"
  , "stalk-color-below-ring"
  , "veil-type"
  , "veil-color"
  , "ring-number"
  , "ring-type"
  , "spore-print-color"
  , "population"
  , "habitat"
)

# Print the new column names
colnames(dataset)


# Create a new data frame with only first 5 columns
dataset_2 <- dataset[, c(1, 2, 3, 4, 5)]

# Data Inspection
class(dataset_2)

# Structure
str(dataset_2)

# Assign column names to the new data set
colnames(dataset_2) <- c(
  "Edibleness"
  , "shape"
  , "surface"
  , "color"
  , "bruises"
)

# Print the column names
colnames(dataset_2)

# Change the data in "Edibleness" column according to the abbreviations below
# edible=e, non-edible=p
levels(dataset_2$Edibleness)[levels(dataset_2$Edibleness) == "e"] <- "edible"
levels(dataset_2$Edibleness)[levels(dataset_2$Edibleness) == "p"] <- "poisonous"

# Change the data in "shape" column according to the abbreviations below
# bell=b,conical=c,convex=x,flat=f, knobbed=k,sunken=s
levels(dataset_2$shape)[levels(dataset_2$shape) == "b"] <- "bell"
levels(dataset_2$shape)[levels(dataset_2$shape) == "c"] <- "conical"
levels(dataset_2$shape)[levels(dataset_2$shape) == "x"] <- "convex"
levels(dataset_2$shape)[levels(dataset_2$shape) == "f"] <- "flat"
levels(dataset_2$shape)[levels(dataset_2$shape) == "k"] <- "knobbed"
levels(dataset_2$shape)[levels(dataset_2$shape) == "s"] <- "sunken"

# Change the data in "surface" column according to the abbreviations below
# fibrous=f,grooves=g,scaly=y,smooth=s
levels(dataset_2$surface)[levels(dataset_2$surface) == "f"] <- "fibrous"
levels(dataset_2$surface)[levels(dataset_2$surface) == "g"] <- "grooves"
levels(dataset_2$surface)[levels(dataset_2$surface) == "y"] <- "scaly"
levels(dataset_2$surface)[levels(dataset_2$surface) == "s"] <- "smooth"

# Change the data in "color" column according to the abbreviations below
# brown=n,buff=b,cinnamon=c,gray=g,green=r,pink=p,purple=u,red=e,white=w,yellow=y
levels(dataset_2$color)[levels(dataset_2$color) == "n"] <- "brown"
levels(dataset_2$color)[levels(dataset_2$color) == "b"] <- "buff"
levels(dataset_2$color)[levels(dataset_2$color) == "c"] <- "cinnamon"
levels(dataset_2$color)[levels(dataset_2$color) == "g"] <- "gray"
levels(dataset_2$color)[levels(dataset_2$color) == "r"] <- "green"
levels(dataset_2$color)[levels(dataset_2$color) == "p"] <- "pink"
levels(dataset_2$color)[levels(dataset_2$color) == "u"] <- "purple"
levels(dataset_2$color)[levels(dataset_2$color) == "e"] <- "red"
levels(dataset_2$color)[levels(dataset_2$color) == "w"] <- "white"
levels(dataset_2$color)[levels(dataset_2$color) == "y"] <- "yellow"

# Change the data in "bruises" column according to the abbreviations below
# bruises=t,no=f
levels(dataset_2$bruises)[levels(dataset_2$bruises) == "t"] <- "bruises"
levels(dataset_2$bruises)[levels(dataset_2$bruises) == "f"] <- "no"

# Print data set 2 (5 columns data frame)
dataset_2