Lecture 1

It covers the basics of R, plots, matrices, arrays, lists and some
about data frames

Lecture 1 /Lecture1_introduction.R

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+# The script works on the current directory
+#
+# Samuel Rodriguez Bernabeu
+# Assignment: lecture 1
+# deliver date: 22/09/14
+#
+#
+
+rm(list=ls()) # clear the actual workspace
+
+# we create the elasticband dataframe
+elasticband <- data.frame( stretch = c(46,54,48,50,44,42,52), distance = c(148,182,173,166,109,141,166))
+
+# exercise 1: create summary statistics for the elastic band data
+summary( elasticband )
+
+# exercise 2: create a plot of distance versus stretch
+plot( distance ~ stretch , elasticband, main="Distance vs. stretch", xlab="Stretch [N]", ylab="Distance [mm]")
+
+# exercise 3: use help() command to find more information about the hist() command
+help( hist )
+
+# exercise 4: create a histogram of the distance using hist()
+hist( elasticband$distance, main="Histogram of distance", xlab="Distance [mm]", ylab="Frequency")
+
+# exercise 5: create the dataframe of snow cover data and plot the results 
+snow <- data.frame( year=1970:1979, snow.cover=c(6.5,12.0,14.9,10.0,10.7,7.9,21.9,12.5,14.5,9.2))
+plot( log(snow.cover) ~ year, snow, main="Snow cover for Eurasia in the years 1970-1979", ylab="log of snow cover", xlab="Year")
+
+# exercise 6: remove the elasticband dataframe
+rm( elasticband)
+

Lecture 1 /Lecture1_lists.R

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+# The script works on the current directory
+#
+# Samuel Rodriguez Bernabeu
+# Assignment: lecture 1
+# deliver date: 22/09/14
+#
+#
+
+rm(list=ls()) # clear the actual workspace
+
+# Exercise 1: create the vector containing the provided data
+Year <- c(1980,1988,1996,1998,2000,2002)
+mean_weight <- c(71.5,72.1,73.3,74.3,75.2,74.7)
+Gender <- c("M", "M", "F", "F", "M", "M")
+mean_height <- c(179.3,179.9,180.5,180.1,180.3,180.4)
+
+# Exercise 2: Create a list called mylist containing the above vector.
+#             Give each component of the list a name
+
+mylist <- list( Year=Year, Weight=mean_weight, Gender=Gender, Height=mean_height)
+mylist
+
+# Exercise 3: use three different ways to access the 4th element of the list
+mylist[4]        # accessing via indexing directly to the 4th element.
+mylist["Height"] # "Height" is the name of the fourth element of the list
+mylist$Height    # "Height" is the name of the fourth element of the list

Lecture 1 /Lecture1_matrices_and_arrays.R

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+# The script works on the current directory
+#
+# Samuel Rodriguez Bernabeu
+# Assignment: lecture 1
+# deliver date: 22/09/14
+#
+#
+
+rm(list=ls()) # clear the actual workspace
+
+# Exercise 1: construct a matrix A with values 10,20,30,50 in column 1 (...)
+array <- c(10,20,30,50,1,4,2,3,15,11,19,5)
+A <- matrix( array, nrow=4, ncol=3)
+A
+
+B = matrix( data=c(2.5,3.5,1.75), nrow=1, ncol=3)
+B
+
+
+# Exercise 2: combine A and B into a new matrix C using cbind()
+C = cbind( A, B)
+C
+# cbind(A,B) throws an error, "the number of rows on the matrices must be the same"
+
+
+# Exercise 3: combine A and B into a new matrix C using rbind()
+H = rbind(A,B)
+H
+
+# Exercise 4: determine the dimensions of C and H using dim() function
+dim(H)
+
+
+# Exercise 5: calculate the following
+M = matrix( data=c(1,4,3,0,-2,8), nrow=2, ncol=3)
+N = matrix( data=c(1,9,2,17,-6,3), nrow=3, ncol=2)
+result <- M%*%N
+result
+
+# Exercise 6: create a 4x4x2 array arr using the values 1 to 32
+arr <- array( data=1:32, c(4,4,2))
+
+# Exercise 7: print out the value in row 1, column 3 of the first 'matrix'
+arr[1,3,1]
+
+
+# Exercise 8: print out the value in row 2, column 4 of the second 'matrix'
+arr[2,4,2]
+
+# Exercise 9: add these two values together
+arr[1,3,1] + arr[2,4,2]

Lecture 1 /Lecture1_vector_and_factors.R

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+# The script works on the current directory
+#
+# Samuel Rodriguez Bernabeu
+# Assignment: lecture 1
+# deliver date: 22/09/14
+#
+#
+
+rm(list=ls()) # clear the actual workspace
+
+# Exercise 1: create a vector x with the following entries, then change the 1's to 0's
+x <- c(3,4,1,1,2,1,4,2,1,1,5,3,1,1,1,2,4,5,5,3)
+x[ (x==1) ] = 0
+
+# Exercise 2: create a vector y containing the elements of x that are greater than 1
+y<-x[x>1]
+
+# Exercise 3: create a sequence of numbers from 1 to 20 in steps of 0.2 and store
+z<-seq( 1, 20, 0.2)
+
+# Exercise 4: concatenate x and y into a vector called newVec
+newVec <- c(x,y)
+
+# Exercise 5: display all objects in the workspace and then remove newVec
+ls()
+rm(newVec)
+
+# Exercise 6: six patients were asked to rate their pain from 0 to 3, with 0 representing "no pain", 1 representing 'mild' pain, 
+#             2 representing 'medium' pain and 3 'severe' pain.
+#             create a factor fpain to represent the data.
+
+# Explanation: I've done this using a dataframe instead of a single vector. For a single vector would be the same
+
+pain <- data.frame( Patient=1:6, fpain=c(0,3,1,2,1,2))
+pain$fpain = factor( pain$fpain, levels=0:3)
+levels(pain$fpain) <- c("no pain", "mild", "medium", "severe")
+summary(pain)