## R commands modified from Matrices_and_Data_Frames my_vector <- c(4, 2, 5) # create the vector (4, 2, 5) called my_vector my_vector # Display my_vector my_vector <- 1:20 # create a vector called my_vector containing the numbers 1 through 20 # WARNING: we wrote over our old my_vector my_vector # Display my_vector dim(my_vector) # Observe dim does not work for vector length(my_vector) # But length does dim(my_vector) <- c(4, 5) # Assign dimension to my_vector # my_vector is now a matrix with 4 rows and 5 columns class(my_vector) # we can see that my_vector is now a matrix dim(my_vector) # dim returns its dimensions my_vector # display my_vector attributes(my_vector) # See attributes (i.e., dimension) of this matrix my_matrix <- my_vector # copy my_vector into my_matrix my_matrix2 <- matrix(c(1, 2, 3), nrow=4, ncol=5) # create a 4x5 matrix # Note matrix is filled with repeating 1, 2, 3 # Note warning since 3 does not divide 20 my_matrix2 # display my_matrix2 <- matrix(c(1, 2, 3, 4, 5), nrow=4, ncol=5) #create a 4x5 matrix # Note matrix is filled with repeating 1, 2, 3, 4, 5 # Note there is NO warning since 5 divides 20 my_matrix2 # display my_matrix2 <- matrix(1:20, nrow=4, ncol=5) #create a 4x5 matrix my_matrix2 # display identical(my_matrix, my_matrix2) # check if the two matrices are the same patients <- c("Bill", "Gina", "Kelly", "Sean") cbind(patients, my_matrix) # combine as columns: patients vector and # my_matrix into a single matrix and display # Note that since we did not assign it a name, # we are not saving it to work with it later my_data <- data.frame(patients, my_matrix) # We instead combine patients and # my_matrix into a data frame # which we call my_data my_data class(my_data) cnames <- c("patient", "age", "weight", "bp", "rating", "test") colnames(my_data) <- cnames # assign names to each of the columns my_data my_data\$age # the age column of my_data my_data[,2] # the 2nd column of my_data my_data[1,] # the 1rst row of my_data my_data[1,2] # the element in 1rst row, 2nd columns of my_data range(my_data\$age) # calculate the range: lowest value, highest value range(my_data[,2]) mean(my_data\$age) # calculate the mean sum(my_data\$age)/4 # calculate the sum and divide sum by 4 median(my_data\$age) # calculate the median sd(my_data\$age) # calculate the standard deviation var(my_data\$age) # calculate the variance sqrt(var(my_data\$age)) # square root of variance = standard deviation mode(my_data\$age) # Get the type or storage mode of an object. ?mode sort(my_data\$age) # Sort the data in increasing order ?sort sort(my_data\$age, decr = TRUE) # Sort the data in decreasing order summary(my_data\$age) summary(my_data) hist(my_data\$age, xlab="age", main="Title") hist(my_data\$age, main="", breaks = 4, col = "lightblue", border = "black") hist(my_data\$age, main="", breaks = 5, col = "lightblue", border = "pink") hist(my_data\$age, xlab="age", main="", breaks = c(0, 1, 2, 3, 4), col = "lightblue") ?hist plot(my_data) plot(cbind(my_data\$age, my_data\$bp)) # First used cbind to create matrix with # 2 columns: my_data\$age, my_data\$bp # Then used plot to plot these points cbind(my_data\$age, my_data\$bp) 2*my_data # for fun I multiplied my_data by 2. Observe the output. rm(my_data) # remove my_data my_data # note my_data no longer exists. rm(list=ls(all=TRUE)) # removes ALL your Data!!!!!!!!!!! # NOTE: ALL values are ERASED!!!!