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############### Introduction to R ###############
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# Some basic things in R
# Firstly you will need to set your working directory. This is a place where R will go to look for to import
# any data you want and where R will store any files you make like figures and tables.
setwd("C:/Users/YOURNAME/Documents/R_workshop/workshop_material/exercises/introduction_to_r")
# or
setwd("C:\\Users\\YOURNAME\\Documents\\R_workshop\\workshop_material\\exercises\\introduction_to_r")
# to check that you are in the right directort type in the console
getwd()
# Storing information
# To store the number 10 for later use:
x<-10
# or
y=15
x
y
# These are called objects and you can then use these in calculations
x+y
# and you can store that too
z<-x+y
# You can make a list of these objects this is called a vector
a<-c(x,y,z)
a
# and calculate things from that list
a*2
# or
a/z
## NB named objects are case sensitive
A
## The names you use cannot contain spaces and cannot be entirely numeric
a space<-10
10<-11
# but
a_with.space<-10
X10<-11
#
# You can view all your objects using
ls()
# and you can remove an object
rm(a)
# You can read in an external data set from a txt file or from excel, but you cant read in a .xls file only a .csv
# so first convert your file to a .csv then read it into R
# this will import the data as a data frame
catch_effort<-read.csv(file="sample_data.csv", header =TRUE)
catch_effort
# note the first column name has changes to catch.year to remove the space
head(catch_effort)
tail(catch_effort)
catch_effort$catch.year
class(catch_effort)
# r reads data frames by row then column so to see a specific number eg the catch of albacore in 2000
# [] use for data frame referencing
# () used for functions
catch_effort[1,3] # [row, column]
#or
catch_effort[1,"alb"]
# To change the column names
colnames(catch_effort)<-c("yy","hook", "ALB", "BET","YFT")
# To make a new column of data with the catch totals you can use thr row sum function (rowSums)
# you need to assign this to a column in the data frame
catch_effort$total<-rowSums(catch_effort)
# is this correct?
1162 + 2959 + 1993 # in 2000
# 6114 but the total is 20650 more than that
# so we need to leave out the first twp columnc
catch_effort$total<-rowSums(catch_effort[c(3:5)])
head(catch_effort)
#You can also sum the columns you want
colSums(catch_effort[c(-1:-2)])
# calculate the total cpue
catch_effort$cpue<-catch_effort$total/catch_effort$hook
# How would you calculate the average cpue?
# save the new data to something you can use again
write.csv(catch_effort,file = "catch_cpue.csv" ) # look at the csv file in excel there are row numbers in the file which can be annoying
# these can be excluded:
write.csv(catch_effort,file = "catch_cpue.csv", row.names = FALSE )
# You can also save the data you have created to an R data file
save(catch_effort, x, y, file = "catch.RData")
# or
save.image(file = "catch_all_data.RData") # will save all active objects
# these are handy things to have as it means that you can access all you objects withour re-running all the code
# you can load them back into the R environmant using load eg:
load("catch.RData")
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##### Plot some stuff
###########################################################
plot(catch_effort$yy, catch_effort$ALB)
?plot
#How can we make it nicer?
plot(catch_effort$yy, catch_effort$ALB, las=1)
plot(catch_effort$yy, catch_effort$ALB, las=1, xlab="Years", ylab="Catch (t)")
plot(catch_effort$yy, catch_effort$ALB, las=1, xlab="Years", ylab="Catch (t)", ylim=c(0,3500))
lines(catch_effort$yy, catch_effort$YFT)
lines(catch_effort$yy, catch_effort$BET, col="red")
savePlot(filename = "first_plot", type="png")
# Bar plots
barplot(t(catch_effort[,c("ALB", "BET", "YFT")]), names.arg= catch_effort$yy, beside = FALSE)
## fix the y-axis so that the bars don't go above it and the labels look good
barplot(t(catch_effort[,c("ALB", "BET", "YFT")]), names.arg= catch_effort$yy, beside = FALSE,
ylim=c(0,7000), las=1, col=c("forestgreen","firebrick","yellow" ))
savePlot(filename = "first_bar_plot", type="png")
# what happens of you change besides= TRUE
# Box plots
load("cpue_data.RData") # load the data file
#load("catch.RData")
boxplot(cpue ~ mm, data= cpue_dat, subset= sp_code =="FAL", las=1, col="red", ylab="CPUE kg/100 hooks",
main="Silky shark", cex.axis=0.8, xlab = "Years", ylim=c(0,200))
savePlot(filename = "box_plot1", type="png")
boxplot(cpue ~ yy, data= cpue_dat, subset= sp_code =="ALB", las=1, col="forestgreen", ylab="CPUE kg/100 hooks",
main="Albacore", cex.axis=0.8, xlab = "Years", ylim=c(0,100))
savePlot(filename = "box_plot2", type="png")
####################################################################
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# Exercises
# 1 Make all of the series from your first plot lines
plot(catch_effort$yy, catch_effort$ALB, las=1, xlab="Years", ylab="Catch (t)", ylim=c(0,3500))
lines(catch_effort$yy, catch_effort$YFT)
lines(catch_effort$yy, catch_effort$BET, col="red")
savePlot(filename = "first_plot_ex1", type="png")
# 2 Make the same plot above but make the lines thicker and color the lines as follows:
# albacore - forestgreen
# bigeye - firebrick
# yellowfin - gold2
# add a legend in the top right corner
?legend
savePlot(filename = "first_plot_ex2", type="png")
# 3 remove the box around the legend
savePlot(filename = "first_plot_ex3", type="png")
# 4 change the lines in the plot and the legend to be lines showing the data points as filled dots
# in the plot and legend
savePlot(filename = "first_plot_ex4", type="png")
# 5 add cpue as a new line on a secondary axis as a line with the data points as filled triangles
# hint you will need to make more space around the plot and create a new plot to overaly your original
# use par(new=TRUE)
savePlot(filename = "first_plot_ex5", type="png")
# 6 Use the bar plot code above and add in a legend, and a heading "Catch of the three main tuna",
# and x and y - axis labels
savePlot(filename = "first_plot_ex6", type="png")
# 7 use the plot call above to make individual plots for bigeye, yellowfin, albacore and your barplot
# then plot each plot in its own panel with a heading on a single page
savePlot(filename = "first_plot_ex7", type="png")
# 8 Using the cpue_dat file make a box plot showing the annual cpue of yellowfin tuna by year
savePlot(filename = "first_plot_ex8", type="png")Copyright © 2017 Pacific Community. All rights reserved.