Lexical Scoping

.Rhistory

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+List.files()
+list.files()
+source("cachematrix.R")
+ls()
+git add .
+outcome <-read.csv("outcome-of-care-measures.csv" colClasses="character")
+outcome <-read.csv("outcome-of-care-measures.csv",colClasses="character")
+View(outcome)
+head(outcome)
+clear
+View(outcome)
+q()

best.R

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+best <- function(state, outcome) {
+    ## Read outcome data
+    data <- read.csv("outcome-of-care-measures.csv", colClasses = "character")
+
+    ## Check that state is valid
+    if (!state %in% data$State) {
+        stop("invalid state")
+    }
+
+    ## Check that outcome is valid
+    valid_outcomes <- c("heart attack", "heart failure", "pneumonia")
+    if (!outcome %in% valid_outcomes) {
+        stop("invalid outcome")
+    }
+
+    ## Map outcomes to their respective column indices
+    outcome_col <- c(
+        "heart attack" = 11,
+        "heart failure" = 17,
+        "pneumonia" = 23
+    )
+
+    ## Filter data for the specified state
+    state_data <- data[data$State == state, ]
+
+    ## Extract and convert rates to numeric
+    rates <- as.numeric(state_data[, outcome_col[outcome]])
+
+    ## Filter out NA values
+    valid <- !is.na(rates)
+    state_data <- state_data[valid, ]
+    rates <- rates[valid]
+
+    ## Find the hospital with the lowest rate
+    lowest <- min(rates)
+
+    best_hospitals <- state_data$Hospital.Name[rates == lowest]
+
+    ## Sort alphabetically in case of a tie and return the first one
+    best_hospitals <- sort(best_hospitals)
+    return(best_hospitals[1])
+}

cachematrix.R

@@ -1,15 +1,40 @@
-## Put comments here that give an overall description of what your
-## functions do
+## These two functions work together to cache the inverse of a matrix,
+## so that if the inverse has already been calculated for the current
+## matrix, it can be retrieved from the cache instead of recomputed.
 
-## Write a short comment describing this function
+## makeCacheMatrix creates a special "matrix" object that can cache
+## its inverse. It returns a list of functions to set and get the
+## value of the matrix, and to set and get the value of the inverse.
 
 makeCacheMatrix <- function(x = matrix()) {
 
+    inv <- NULL
+    set <- function(y) {
+        x <<- y
+        inv <<- NULL
+    }
+    get <- function() x
+    setinverse <- function(inverse) inv <<- inverse
+    getinverse <- function() inv
+    list(set = set, 
+         get = get,
+         setinverse = setinverse,
+         getinverse = getinverse)
 }
 
-
-## Write a short comment describing this function
+## cacheSolve computes the inverse of the special "matrix" returned
+## by makeCacheMatrix. If the inverse has already been calculated
+## (and the matrix has not changed), it retrieves the inverse from
+## the cache instead of recomputing it.
 
 cacheSolve <- function(x, ...) {
-        ## Return a matrix that is the inverse of 'x'
+    inv <- x$getinverse()
+    if(!is.null(inv)) {
+        message("getting cached data")
+        return(inv)
+    }
+    data <- x$get()
+    inv <- solve(data, ...)
+    x$setinverse(inv)
+    inv
 }

rankall.R

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+rankall <- function(outcome, num = "best") {
+    ## Read outcome data
+    data <- read.csv("outcome-of-care-measures.csv", colClasses = "character")
+
+    valid_outcomes <- c("heart attack", "heart failure", "pneumonia")
+    if (!outcome %in% valid_outcomes) {
+        stop("invalid outcome")
+    }
+
+    outcome_col <- c(
+        "heart attack" = 11,
+        "heart failure" = 17,
+        "pneumonia" = 23
+    )
+
+    col_index <- outcome_col[outcome]
+    states <- sort(unique(data$State))
+
+    hospital_vector <- c()
+    state_vector <- c()
+
+    for (s in states) {
+        state_data <- data[data$State == s, ]
+        rates <- as.numeric(state_data[, col_index])
+
+        valid <- !is.na(rates)
+        state_data <- state_data[valid, ]
+        rates <- rates[valid]
+
+        ordered_indices <- order(rates, state_data$Hospital.Name)
+        state_data <- state_data[ordered_indices, ]
+
+        total_hospitals <- nrow(state_data)
+
+        selected_hospital <- NA
+        if (total_hospitals > 0) {
+            if (num == "best") {
+                selected_hospital <- state_data$Hospital.Name[1]
+            } else if (num == "worst") {
+                selected_hospital <- state_data$Hospital.Name[total_hospitals]
+            } else if (is.numeric(num)) {
+                if (num <= total_hospitals) {
+                    selected_hospital <- state_data$Hospital.Name[num]
+                }
+            }
+        }
+
+        hospital_vector <- c(hospital_vector, selected_hospital)
+        state_vector <- c(state_vector, s)
+    }
+
+    return(data.frame(hospital = hospital_vector, state = state_vector, row.names = state_vector))
+}

rankhospital.R

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+rankhospital <- function(state, outcome, num = "best") {
+    ## Read outcome data
+    data <- read.csv("outcome-of-care-measures.csv", colClasses = "character")
+
+    ## Check that state and outcome are valid
+    if (!state %in% data$State) {
+        stop("invalid state")
+    }
+
+    valid_outcomes <- c("heart attack", "heart failure", "pneumonia")
+    if (!outcome %in% valid_outcomes) {
+        stop("invalid outcome")
+    }
+
+    outcome_col <- c(
+        "heart attack" = 11,
+        "heart failure" = 17,
+        "pneumonia" = 23
+    )
+
+    ## Filter by state and extract valid rate rows
+    state_data <- data[data$State == state, ]
+    rates <- as.numeric(state_data[, outcome_col[outcome]])
+
+    valid <- !is.na(rates)
+    state_data <- state_data[valid, ]
+    rates <- rates[valid]
+
+    ## Order hospitals by rate and then by name alphabetically
+    ordered_indices <- order(rates, state_data$Hospital.Name)
+    state_data <- state_data[ordered_indices, ]
+
+    ## Handle num argument ("best", "worst", or numeric rank)
+    total_hospitals <- nrow(state_data)
+
+    if (num == "best") {
+        target_row <- 1
+    } else if (num == "worst") {
+        target_row <- total_hospitals
+    } else if (is.numeric(num)) {
+        if (num > total_hospitals) {
+            return(NA)
+        }
+        target_row <- num
+    } else {
+        stop("invalid num")
+    }
+
+    return(state_data$Hospital.Name[target_row])
+}