We will be learning how to create professional looking graphs using the package “GGPlot 2”

#Scatterplot (w best fitting regression line)
library(ggplot2)

avg_freq_nr <- c(0,1,3,5,28,48,52,60)
avg_freq_r <- c(4,12,31,40,47,48,57,60)

plot_freq_soc <- data.frame(avg_freq_r,avg_freq_nr)

ggplot(data=plot_freq_soc, aes(x=avg_freq_nr,y=avg_freq_r))+
  geom_point(size=1)+
  geom_smooth(method = "lm", se=FALSE, color='BLACK')+
  coord_cartesian(xlim=c(0,70),ylim=c(0,70))+
  xlab("Average Frequency of Nonsocial Risk")+
  ylab("Average Frequency of Social Risk")+
  theme_classic(base_size=12)+
  ggtitle("Figure 6")

#how do you get regression line at zero & 70 to show... control the ticks?

#figure 4 evaluation of person X; man & woman communicated w ATC
library(ggplot2)
evalp<- rep(c(1,2,3,4,5,6,7),2)
#man <- c(91, 90, 89, 89, 88, 88, 87)
#woman<- c(82, 74, 68, 65, 55, 50, 45)
target <- c(91, 90, 89, 89, 88, 88, 87,82, 74, 68, 65, 55, 50, 45)
person<- rep(c("Man Communicated with ATC","Woman Communicated with ATC"),times=c(7,7))
evalopX <- data.frame(evalp,target,person)

ggplot(data = evalopX, aes(x=evalp,y=target,group=person))+
  geom_smooth(method=lm,size=2,show.legend = TRUE)+
  xlab("Evaluation of Person X")+
  ylab("P(Target = Pilot)")+
  ggtitle("Fig. 4 Results from Study 5")+
  theme_classic(base_size=11)

  #theme(axis.ticks.x = 1:7) -- "must be a element_line object?"
  #theme(axis.ticks.length = 1.00)
  



#why does only 1 line have the gray surrounding 
#make all tics show; add negative to 1 and positive to 7 

#figure 2 A.visual group B.auditory group
fac_one <- rep(rep(as.factor(c("No Transient", "Transient")),2),2)
fac_two <- rep(rep(as.factor(c("Outside","Inside")),2),2)
fac_three<- rep(as.factor(c("Visual Group", "Auditory Group")),each=4)
meanmed<- c(305,300,290,275,295,290,265,250)
er<- c(23,20,22,20,17,20,15,20)
fig2<- data.frame(fac_one,
                  fac_two,
                  fac_three,
                  meanmed,
                  er)

ggplot(data=fig2, aes(x=fac_one, y=meanmed, group=fac_three))+
  geom_bar(stat="identity",position="dodge")+
  facet_wrap(~fac_three)

#data not distributed right, should be 4 bars in each graph

# Class example redone w additional layers

Namez<- rep(c("Dara","Azalea","Barbi","Rowena","Fiona" ),each=2)
MF <- rnorm(10,45,25)
Condition <- rep(c("Social", "Nonsocial"),5)
Aversion <- rep(c("A","N_A"),times=c(4,6))
Fig5<- data.frame(Namez,MF,Condition,Aversion)

ggplot(data=Fig5, aes(x=Condition,y=MF,group=Namez, linetype=Aversion))+ #parantheses matter,pay attention
  geom_line()+
  geom_text(label=Namez)+
  theme_classic()+
  ylab("Mean Frequency of Risky Choice")

f1 <- rep(c("Emotional Stability", "Extraversion", "Openness/Intellect", "Agreeableness", "Conscientiousness"),4)
f2 <- c(-.1,-.2,.1,-.2,-.2,-.2,-.15,.2,-.5,-.2,-.2,-.02,.08,.00,-.08,.01,.25,.7,.4,.4)
f3 <- rep(c("Family","Friends","Colleagues","Strangers"),5)
meandif<-data.frame(f1,f2,f3)

ggplot(meandif, aes(x=f1,y=f2,group=f3))+
  geom_line()+
  ggtitle("Fig1 Mean difference in effect size")+
  ylab("Mean Difference")+
  scale_x_discrete(limits = c("Emotional Stability", "Extraversion", "Openness/Intellect","Agreeableness","Conscientiousness"))+
  theme_classic()

  #theme(axis.line.x.top = 0)



#dataframe needs equal values in each variable, so how do you get y axis to have all the categories once, not repeated

library(ggplot2)
year<- rep(c(2014,2015,2016,2017), each = 12)
changes <- rep(c(runif(12,5,15), runif(12,5,20), runif(12,13,28), runif(12,20,30)), each = 5)
program <- c("C", "Python", "Matlab", "R", "Java")

g<- data.frame(year, changes, program)
#  year = rep(c(2014,2015,2016,2017), each = 12),
 # var1 = 5 + c(0,runif(12,5,15),))
ggplot(g, aes(x=year, y=changes, group=program, colour = program))+
  geom_line()