# Demographic Data

# Create 2008 matrix

data2008<-matrix(c(1.5,1.5,2.5,2.7,25.4,26.4,0.9,0.9), ncol=2, byrow=T)

# Add column names using colnames()

colnames(data2008)<-c("M","F")

# Add row names using rownames()

rownames(data2008)<-c("Wales","Scotland","England","NI")

# Display data2008

data2008

# Create 2013 matrix

data2013<-matrix(c(1.5,1.6,2.6,2.7,26.5,27.3,0.9,0.9), ncol=2, byrow=T)

# Add column names using colnames()

colnames(data2013)<-c("M","F")

# Add row names using rownames()

rownames(data2013)<-c("Wales","Scotland","England","NI")

# Display data2013

data2013

# Create 2018 matrix

data2018<-matrix(c(1.5,1.5,2.6,2.8,27.7,28.3,0.9,1.0), ncol=2, byrow=T)

# Add column names using colnames()

colnames(data2018)<-c("M","F")

# Add row names using rownames()

rownames(data2018)<-c("Wales","Scotland","England","NI")

# Display data2018

data2018

# Combine the two matrices into an array obs_array

data_array<-array(data=c(data2008,data2013,data2018),dim=c(4,2,3))

# Display array

data_array

# Data extraction

# Extract population of Wales
# Wales is row 1, so use 1, , 

data_array[1, ,]

# Extract population of Scotland in 2013
# Scotland is row 2, 2013 is layer 2, so use 2, ,2

data_array[2, ,2]

# Extract female population of England in 2008
# England is row 3, female is column 2, 2008 is layer 1, so use 3,2,1

data_array[3,2,1]
