### LQ Human Robot Integration ###

# Clean space
remove(list=ls())
dev.off()
cat("\014")

# Load Packages 
library(tidyverse)
library(ggplot2)
library(dplyr)
library(ggpubr)
library(gridExtra)
library(grid)
library(lattice)
library(gtable)

#### IMPORT DATA ####
df<-readxl::read_excel("~/Desktop/R Practice /Leadership & Robotics Coding_Compiled.xlsx")

#### SUBSET DATA - ONLY PHYSICAL ROBOT PUBLICATIONS ####
mydata <-df[ which(df$`Physical Robot`==1), ]

##############################
#### RENAME COLUMN VALUES ####
##############################

# TaskOrRel
mydata$TaskOrRel[mydata$TaskOrRel==1] <- "Task"
mydata$TaskOrRel[mydata$TaskOrRel==2] <- "Relationship"
mydata$TaskOrRel[mydata$TaskOrRel==3] <- "Both"
mydata$TaskOrRel[mydata$TaskOrRel==4] <- "Other"

# Area
mydata$Area[mydata$Area==1] <- "Psychology"
mydata$Area[mydata$Area==2] <- "Engineering"
mydata$Area[mydata$Area==3] <- "Management"
mydata$Area[mydata$Area==4] <- "Econ"

# ConOrEmp
mydata$ConOrEmp[mydata$ConOrEmp==1] <- "Conceptual"
mydata$ConOrEmp[mydata$ConOrEmp==2] <- "Emperical"

# Type
mydata$Type[mydata$Type==1] <- "Book"
mydata$Type[mydata$Type==2] <- "Conference"
mydata$Type[mydata$Type==3] <- "Journal"
mydata$Type[mydata$Type==4] <- "Other"

# Robot Position
mydata$`Robot Position`[mydata$`Robot Position`==1] <- "Follower"
mydata$`Robot Position`[mydata$`Robot Position`==2] <- "Dyadic Partner"
mydata$`Robot Position`[mydata$`Robot Position`==3] <- "Leader"
mydata$`Robot Position`[mydata$`Robot Position`==4] <- "Follower"  #Team member in coding 
mydata$`Robot Position`[mydata$`Robot Position`==5] <- "Other"  
mydata$`Robot Position`[mydata$`Robot Position`=="Multi"] <- "Other" 

# Robot Position
mydata$Level[mydata$Level=="I"] <- "Individual"
mydata$Level[mydata$Level=="D"] <- "Dyadic"
mydata$Level[mydata$Level=="G"] <- "Group"
mydata$Level[mydata$Level=="O"] <- "Organization"  
mydata$Level[mydata$Level=="Multi"] <- "Multilevel"  

#### Subset by Specific Area ####
mngt <- mydata[ which(mydata$Area == "Management"), ]
psy <- mydata[ which(mydata$Area == "Psychology"), ]
eng <- mydata[ which(mydata$Area == "Engineering"), ]
econ <- mydata[ which(mydata$Area == "Econ"), ]


#### CREATE TABLE 4 IN MANUSCRIPT ####

# Management
pos_mngt<-as.data.frame(table(mngt$`Robot Position`))
dplyr::glimpse(pos_mngt)
pos_mngt<-pos_mngt %>%
  arrange(match(Var1,c("Follower", "Dyadic Partner", "Leader","Other")), desc(Var1), desc(Freq))
pos_mngt

# Economics
pos_econ<-as.data.frame(table(econ$`Robot Position`))
dplyr::glimpse(pos_econ)
pos_econ<-pos_econ %>%
  arrange(match(Var1,c("Follower", "Dyadic Partner", "Leader","Other")), desc(Var1), desc(Freq))
pos_econ

# Psychology 
pos_psy<-as.data.frame(table(psy$`Robot Position`))
dplyr::glimpse(pos_psy)
pos_psy<-pos_psy %>%
  arrange(match(Var1,c("Follower", "Dyadic Partner", "Leader","Other")), desc(Var1), desc(Freq))
pos_psy

# Engineering 
pos_eng<-as.data.frame(table(eng$`Robot Position`))
dplyr::glimpse(pos_eng)
pos_eng<-pos_eng %>%
  arrange(match(Var1,c("Follower", "Dyadic Partner", "Leader","Other")), desc(Var1), desc(Freq))
pos_eng


###########################################
#### SUBSET DATA TO CREATE FIGURES 2-4 ####
###########################################

### Area Subsets
psych <-mydata[ which(mydata$Area=="Psychology"), ]
eng <-mydata[ which(mydata$Area=="Engineering"), ]
mngt <-mydata[ which(mydata$Area=="Management"), ]
econ <-mydata[ which(mydata$Area=="Econ"), ]

### ConOrEmp Subsets
con <-mydata[ which(mydata$ConOrEmp=="Conceptual"), ]
emp <-mydata[ which(mydata$ConOrEmp=="Emperical"), ]

### Task or Relation Subsets
task <-mydata[ which(mydata$TaskOrRel=="Task"), ]
relation <-mydata[ which(mydata$TaskOrRel=="Relation"), ]
both <-mydata[ which(mydata$TaskOrRel=="Both"), ]
other <-mydata[ which(mydata$TaskOrRel=="Other"), ]

### Level Subsets
I <-mydata[ which(mydata$Level=="Individual"), ]
D <-mydata[ which(mydata$Level=="Dyadic"), ]
G <-mydata[ which(mydata$Level=="Group"), ]
O <-mydata[ which(mydata$Level=="Organization"), ]
Multi <-mydata[ which(mydata$Level=="Multilevel"), ]


#######################################
#### CREATE FIGURES FOR MANUSCRIPT ####
#######################################

#### FIGURE 2 IN MANUSCRIPT ####

# Subset Data 
Task <-mydata[ which(mydata$`TaskOrRel`=="Task"), ]
Relation<-mydata[ which(mydata$`TaskOrRel`=="Relationship"), ]
Both <-mydata[ which(mydata$`TaskOrRel`=="Both"), ]

# Create Invidual Histograms for Each Subset 
plot1 <- qplot(Task$Year, breaks=seq(1980,2021,by=2),geom="histogram",fill=I("lightblue"),col=I("blue"),ylim=c(0,20),xlim=c(1980,2020)) + ggtitle("Task-based") + xlab("Year") + ylab("Number")+ theme(text=element_text(size=7, family="serif"))
plot2 <- qplot(Relation$Year, breaks=seq(1980,2021,by=2),geom="histogram",fill=I("pink"),col=I("red"),ylim=c(0,20),xlim=c(1980,2020)) + ggtitle("Relationship-based") + xlab("Year") + ylab("Number")+ theme(text=element_text(size=7, family="serif"))
plot3 <- qplot(Both$Year, breaks=seq(1980,2021,by=2),geom="histogram",fill=I("lemon chiffon"),col=I("orange"),ylim=c(0,20),xlim=c(1980,2020)) + ggtitle("Both Task-based and Relationship-based") + xlab("Year") + ylab("Number")+ theme(text=element_text(size=7, family="serif"))

# Combine Histograms into One Plot 
Figure2 <- ggarrange(plot1, plot2, plot3, ncol=1, nrow=3)

# Save the Figure 2 Plot by file type (png, pdf, jpeg, tiff, etc.)
ggsave(Figure2, filename = "~/Desktop/Figure2.png", units="in", width=3, height=5)

#### FIGURE 3 IN MANUSCRIPT ####

# Create Position Subsets
Follower <-mydata[ which(mydata$`Robot Position`=="Follower"), ]
DyadPartner <-mydata[ which(mydata$`Robot Position`=="Dyadic Partner"), ]
Leader <-mydata[ which(mydata$`Robot Position`=="Leader"), ]
Other <-mydata[ which(mydata$`Robot Position`=="Other"), ]

# Create Histograms by Position 
plot1 <- qplot(Follower$Year, breaks=seq(1980,2021,by=2),geom="histogram",fill=I("lightblue"),col=I("blue"),ylim=c(0,15),xlim=c(1980,2020)) + ggtitle("Robots as Followers") + xlab("Year") + ylab("Number")+ theme(text=element_text(size=7, family="serif"))
plot2 <- qplot(DyadPartner$Year, breaks=seq(1980,2021,by=2),geom="histogram",fill=I("pink"),col=I("red"),ylim=c(0,15),xlim=c(1980,2020)) + ggtitle("Robots as Dyadic Partners") + xlab("Year") + ylab("Number")+ theme(text=element_text(size=7, family="serif"))
plot3 <- qplot(Leader$Year, breaks=seq(1980,2021,by=2),geom="histogram",fill=I("lemon chiffon"),col=I("orange"),ylim=c(0,15),xlim=c(1980,2020)) + ggtitle("Robots as Leaders") + xlab("Year") + ylab("Number")+ theme(text=element_text(size=7, family="serif"))
plot4 <- qplot(Other$Year, breaks=seq(1980,2021,by=2),geom="histogram",fill=I("grey"),col=I("black"),ylim=c(0,15),xlim=c(1980,2020)) + ggtitle("Robots as Other") + xlab("Year") + ylab("Number")+ theme(text=element_text(size=7, family="serif"))

# Plot All Histograms in One Plot 
Figure3 <- ggarrange(plot1, plot2, plot3, ncol=1, nrow=3)

# Save the Figure 3 Plot by file type (png, pdf, jpeg, tiff, etc.)
ggsave(Figure3, filename = "~/Desktop/Figure3.png", units="in", width=3, height=5)


#### FIGURE 4 IN MANUSCRIPT ####

### Histograms by Level 
plot1 <- qplot(I$Year, breaks=seq(1963,2020,by=2),geom="histogram",fill=I("lightblue"),col=I("blue")) + coord_cartesian(ylim=c(0,20),xlim=c(1980,2020)) + ggtitle("Individual level") + xlab("Year") + ylab("Number")+ theme(text=element_text(size=10, family="serif"))
plot2 <- qplot(D$Year, breaks=seq(1963,2020,by=2),geom="histogram",fill=I("pink"),col=I("red")) + coord_cartesian(ylim=c(0,20),xlim=c(1980,2020)) + ggtitle("Dyad level") + xlab("Year") + ylab("Number")+ theme(text=element_text(size=10, family="serif"))
plot3 <- qplot(G$Year, breaks=seq(1963,2020,by=2),geom="histogram",fill=I("lemon chiffon"),col=I("orange")) + coord_cartesian(ylim=c(0,20),xlim=c(1980,2020)) + ggtitle("Group level") + xlab("Year") + ylab("Number")+ theme(text=element_text(size=10, family="serif"))
plot4 <- qplot(O$Year, breaks=seq(1963,2020,by=2),geom="histogram",fill=I("lightgreen"),col=I("green")) + coord_cartesian(ylim=c(0,20),xlim=c(1980,2020)) + ggtitle("Organization level") + xlab("Year") + ylab("Number")+ theme(text=element_text(size=10, family="serif"))

# Plot All Histograms in One in 2 x 2 Display for I,D,G,O Plot
Figure4 <- ggarrange(plot1, plot2, plot3, plot4, ncol=2, nrow=2)

# Save the Figure 4 Plot by file type (png, pdf, jpeg, tiff, etc.)
ggsave(Figure4, filename = "~/Desktop/Figure4.png", units="in", width=7, height=5)



#### OTHER TABLES NOT USED IN MANUSCRIPT ####

# Area
A<-as.data.frame(table(mydata$Area))
dplyr::glimpse(A)
A<-A %>%
  arrange(match(Var1,c("Psychology", "Engineering", "Management","Econ")), desc(Var1), desc(Freq))

A

# Area
JBC<-as.data.frame(table(mydata$Type))
dplyr::glimpse(JBC)
JBC<-JBC %>%
  arrange(match(Var1,c("Journal", "Book", "Conference","Other")), desc(Var1), desc(Freq))

JBC

# Robot Position 
R<-as.data.frame(table(mydata$`Robot Position`))
dplyr::glimpse(R)
R<-R %>%
  arrange(match(Var1,c("Follower", "Dyadic Partner", "Leader","Other")), desc(Var1), desc(Freq))

R


# TaskOrRel
T<-as.data.frame(table(mydata$TaskOrRel))
dplyr::glimpse(T)
T<-T %>%
  arrange(match(Var1,c("Task", "Relation", "Both","Other")), desc(Var1), desc(Freq))

T

# Level
L<-as.data.frame(table(mydata$Level))
dplyr::glimpse(L)
L<-L %>%
  arrange(match(Var1,c("I", "D", "G","O","Multi","Industry")), desc(Var1), desc(Freq))

L

# ConOrEmp
C<-as.data.frame(table(mydata$ConOrEmp))
dplyr::glimpse(C)
C<-C %>%
  arrange(match(Var1,c("Conceptual", "Emperical")), desc(Var1), desc(Freq))

C