Prez Test

Student Body Separated by State

StudentState=gusd%>%group_by(State)%>%summarize(Count=length(State))%>%filter(!is.na(State))

GeoStates <- gvisGeoChart(StudentState, "State", "Count",
                          options=list(region="US", 
                                       displayMode="regions", 
                                       resolution="provinces",
                                       width=600, height=400,colorAxis="{colors:['lightblue', 'blue', 'red','green','orange']}"))
plot(GeoStates)

Military Student Enrollment

Mil=gumil%>%group_by(State)%>%summarize(Count=length(State))%>%filter(!is.na(State))

head(Mil[order(-Mil$Count),],20)%>%dimple(x ="State", y = "Count", type = "bar",width=1000, height=750) %>%
  xAxis(type = "addCategoryAxis") %>% 
  add_title( html = "<h4>Military Student Personel Enrollment By State</h4>")

Mean GPA of Military vs Non Military

milvnon1=gusd%>%group_by(State, Status)%>%summarise(Ave.GPA=mean(GPA))%>%
  filter(!is.na(Ave.GPA))


  dimple(data = milvnon1,
    x = c("State","Status"), y = "Ave.GPA",
    groups = "Status", type = "bar", width = 950, height = 600
  ) %>%

  add_legend( x = 50, y = 10, width = 100, height = 50,
              horizontalAlign = "left"
  ) %>%
  default_colors()

Mean GPA of Students - State

SGPA1=gusd%>%group_by(State)%>%summarise(Ave.GPA=mean(GPA))%>%filter(!is.na(Ave.GPA))
                                                            
SGPA1=data.frame(SGPA1)

GeoStates1 <- gvisGeoChart(SGPA1, "State",colorvar =  "Ave.GPA",
                          options=list(title = "Mill Score vs State", region="US", displayMode="regions", resolution="provinces",colorAxis="{colors:['gold','blue']}", width=600, height=400))


GeoTable1 <- gvisTable(SGPA1, 
               options=list(width=220, height=300))
GT1 <- gvisMerge(GeoStates1,GeoTable1, horizontal=TRUE) 
  
plot(GT1)  

Military vs Non Military - Mean Miller Scores

milvnon2=gusd%>%group_by(State, Status)%>%summarise(AVE.MIL=mean(MILLER.ANALOGIES.RAW.SCORE))%>%
  filter(!is.na(AVE.MIL))

  dimple(data = milvnon2,
    x = c("State","Status"), y = "AVE.MIL",
    groups = "Status", type = "bar", width = 950, height = 600
  ) %>%

  add_legend( x = 50, y = 10, width = 100, height = 50,
              horizontalAlign = "left"
  ) %>%
  default_colors()

Mean Miller Score of Students - State

SMIL=gusd%>%group_by(State)%>%summarise(AVE.MIL=mean(MILLER.ANALOGIES.RAW.SCORE))%>%
  filter(!is.na(AVE.MIL))
                                                            
SMIL=data.frame(SMIL)

GeoStates2 <- gvisGeoChart(SMIL, "State",colorvar =  "AVE.MIL",
                          options=list(title = "Miller Score vs State", region="US", displayMode="regions", resolution="provinces",colorAxis="{colors:['gold','blue']}", width=600, height=400))


GeoTable2 <- gvisTable(SMIL, 
               options=list(width=220, height=300))
GT2 <- gvisMerge(GeoStates2,GeoTable2, horizontal=TRUE) 
  
plot(GT2)  

Degree vs GPA

DEGvGPA=gusd%>%group_by(Degree)%>%summarise(AVE.GPA=mean(GPA))%>%
  filter(!is.na(AVE.GPA))

  dimple(data = DEGvGPA,
    x = c("Degree"), y = "AVE.GPA",
     type = "bar", width = 950, height = 600
  ) %>%

  add_legend( x = 50, y = 10, width = 100, height = 50,
              horizontalAlign = "left"
  ) %>%
  default_colors()%>% 
  add_title( html = "<h4>Student Degree vs GPA</h4>")

Program vs GPA

PRGMvGPA=prgm%>%group_by(PROGRAM)%>%summarise(AVE.GPA=mean(GPA))%>%
  filter(!is.na(AVE.GPA))

  dimple(data = PRGMvGPA,
    x = c("PROGRAM"), y = "AVE.GPA", groups = "PROGRAM",
     type = "bar", width = 850, height = 900
  ) %>%
  default_colors()%>%  
  add_title( html = "<h4>Student Program vs GPA</h4>")

Students Enrolled by Program

PRGMvENR=prgm%>%group_by(PROGRAM)%>%summarise(Count=length(GPA))


  dimple(data = PRGMvENR,
    x = c("PROGRAM"), y = "Count", groups = "PROGRAM",
     type = "bar", width = 850, height = 900
  ) %>%
  default_colors()%>%  
  add_title( html = "<h4>Student Program by Enrollment</h4>")