morganmelon/Final Project Scripts

## Final Project Scripts
#Morgan Waterman
#US History Through Census Data
#Final Project: Race, Segregation, and Incarceration in the United States, 1920-2010

#FIGURE 1: Spine Graph of Prison Population by Race 1920-2010

#load packages
library(dplyr)
library(readr)
library(ggplot2)
library(RColorBrewer)
library(scales)

#Program to print plots
printplot <- function(plot, filename) {
  png(paste(filename,'.png', sep=''), height= 500, width = 1000)
  print(plot)
  dev.off()
}

#Read in data extract
ipums <- read_csv('data/FINALFINALDATA.csv', col_types = cols(PERWT=col_double()))

#Filter for age and exclude Alaska and Hawaii and DC
a <- ipums %>% filter(AGE>=15 & AGE<=70)
aa<- a %>% filter(STATEFIP!=11 & (!(STATEFIP %in% c(2, 15)) | YEAR >=1960))

#recode RACESING
b <- aa %>% mutate(Race = factor(ifelse(RACESING==2, 1,
                                 ifelse(RACESING==1, 2, 3)),
      labels = c('Black', 'White', 'Other')))


#recode GQTYPE--create Institution
c <- b %>% mutate(Institution = factor(ifelse(GQTYPE==1, 1,
                                              ifelse(GQTYPE==2, 2, 3)),
                                       labels = c('Institution','Prison prior to 1990', 'Other Group Quarters')))

#filter out Other Institution prior to 1990 and Female to get total male prison population
e <- c %>% filter(Institution !='Other Group Quarters')
f <- e %>% filter(SEX==1)

#aggregate data by Year and Race--apply correction factor for 1990 and later
prisontotal <- f %>% group_by(YEAR, Race) %>% summarise(NumberTotal=sum(PERWT)) %>% mutate(NumberAdj=ifelse(YEAR>=1990, ifelse(Race=='Black', NumberTotal*0.72, ifelse(Race=='White', NumberTotal*.40, NumberTotal*.58)), NumberTotal))

#Sum
prisonrace <- prisontotal %>% group_by(YEAR) %>% summarise(NumberRace=sum(NumberAdj))

#Join so i can calculate percent
prisonjoin <- left_join(prisontotal, prisonrace)

#Calculate percent
prisonpct <- prisonjoin %>% mutate(Percent = NumberAdj/NumberRace)

#Graphing
graphprison <- ggplot(prisonpct, aes(x= YEAR, y=Percent, fill=Race)) +
  geom_bar(stat='identity', aes(width=rescale(NumberRace, c(5, 10)))) +
  labs(fill = 'Race of Prisoners', title = 'Percent of Prison Population by Race, 1920-2010', x = 'Year', y= 'Percent of Prisoners') +
  theme_bw(base_size=8) +
  scale_x_continuous(breaks=c(1920, 1930, 1940, 1950, 1960, 1970, 1980, 1990, 2000, 2010))+
  scale_y_continuous(labels=scales::percent)
printplot(graphprison, 'FINALspine')


#FIGURE 2: Animated Map of Percent of African Americans Males of Total State Male Population 1920-2010

#Load packages
library(readr)
library(dplyr)
library(ggplot2)
library(RColorBrewer)
library(ggmap)
library(maptools)
library(gtools)
library(devtools)
library(gganimate)

#Read in map dataframe
mapdata <-read_csv('data/map.csv')

#Create map base
map1 <-ggplot() + scale_fill_brewer(palette='Oranges') + theme_nothing(legend=TRUE) +
  geom_polygon(data=mapdata, aes(x=long, y=lat, group=group), fill='white', color='black')
png('mapped.png', width=1500, height=1000)
print(map1)
dev.off()

#Read in data extract
ipums <- read_csv('data/FINALFINALDATA.csv', col_types = cols(PERWT=col_double()))

#Filter for age and exclude DC & Alaska and Hawaii prior to 1960
a <- ipums %>% filter((AGE>=15 & AGE<=70) & (STATEFIP!=11) & ((!(STATEFIP %in% c(2,15)) | YEAR >=1960)))

#recode RACESING
b <- a %>% mutate(Race = factor(ifelse(RACESING==2, 1,
                                        ifelse(RACESING==1, 2, 3)),
                                 labels = c('Black', 'White', 'Other')))

#recode GQTYPE--create Institution
#not used in this map
c <- b %>% mutate(Institution = factor(ifelse(GQTYPE==1, 1,
                                              ifelse(GQTYPE==2, 2, 3)),
                                       labels = c('Institution','Prison prior to 1990', 'Other Group Quarters')))

#Filter out Female for total male population
totalall<- c %>% filter(SEX==1) %>% group_by(YEAR,STATEFIP) %>% summarise(TotalAll=sum(PERWT))

#data frame for total black population by state
totalblack <- c %>% filter(SEX==1 & Race=='Black') %>% group_by(YEAR, STATEFIP) %>% summarise(TotalBlack=sum(PERWT))

#join data frames
totalpop <- left_join(totalall, totalblack, by = c('YEAR','STATEFIP'))

#create percentage variable
blackpct <- totalpop %>% mutate(Percent = TotalBlack/TotalAll)

#used to determine "bins" in map
cuts <- quantcut(blackpct$Percent, q=seq(0,1,.2))

#joining data to map dataframe
#change STATEFIP to integer
newmap <- mapdata %>% mutate(STATEI=as.integer(STATEFIP))

#Creating "bins" for percentages
totalcats <- blackpct %>% mutate(Percentage = factor(ifelse(Percent<=.01, 1,
                                                             ifelse(Percent<=.03, 2,
                                                                    ifelse(Percent<=.07, 3,
                                                                           ifelse(Percent<=.15, 4,5))))))
levels(totalcats$Percentage) <- c('0-1%', '1-3%', '3-7%', '7-15%', '15%+')

#joining to map
prisonmap <- left_join(totalcats, newmap, by = c('STATEFIP' = 'STATEI')) %>% arrange(order)

prisonmap <- prisonmap %>% arrange(order)

#Animating map
anmap <- map1 +
  geom_polygon(data=prisonmap, aes(x=long, y=lat, group=group, fill=Percentage, frame=YEAR), color='black') +
  labs(title= 'Percent of African Americans Males of Total State Male Population, ')

gg_animate(anmap, ani.width=1500, ani.height=1000, 'AfAmofTotalPop.gif')

getPalette = colorRampPalette(brewer.pal(9, 'Oranges'))

map2 <- map1 + scale_fill_manual(values=getPalette(5)) +
  geom_polygon(data=filter(prisonmap, YEAR==1940), aes(x=long, y=lat, group=group, fill=Percentage), color= 'black')
png('mapviz3YAY.png', width= 1500, height=1000)
print(map2)
dev.off()

#for loop to make a map for each year
for (year in unique(prisonmap$YEAR)) {
  map2 <-map1 + theme_bw(base_size=24) +
    geom_polygon(data=filter(prisonmap, YEAR==year),
                 aes(x=long, y=lat, group=group, fill=Percentage), color='black') +
    labs(title=paste('Percent of African Americans Males of Total State Male Population,',year, sep=' '))
  png(paste('mapviz3YAY_', year,'.png', sep=''), width=1500, height=1000)
  print(map2)
  dev.off()
}


#FIGURE 3: Animated Map of Percent of Male African Americans in Total Prison Population By State, 1920-2010

#load packages
library(readr)
library(dplyr)
library(ggplot2)
library(RColorBrewer)
library(ggmap)
library(maptools)
library(gtools)
library(devtools)
library(gganimate)

#read in map dataframe
mapdata <-read_csv('data/map.csv')

#Create map base
map1 <-ggplot() + scale_fill_brewer(palette='Reds') + theme_nothing(legend=TRUE) +
  geom_polygon(data=mapdata, aes(x=long, y=lat, group=group), fill='white', color='black')
png('maprace.png', width=1500, height=1000)
print(map1)
dev.off()

#read in data extract
ipums <- read_csv('data/FINALFINALDATA.csv', col_types = cols(PERWT=col_double()))

#filter for age and exclude DC & Alaska and Hawaii prior to 1960
a <- ipums %>% filter((AGE>=15 & AGE<=70) & (STATEFIP!=11) & ((!(STATEFIP %in% c(2,15)) | YEAR >=1960)))

#recode RACESING
b <- a %>% mutate(Race = factor(ifelse(RACESING==2, 1,
                                        ifelse(RACESING==1, 2, 3)),
                                 labels = c('Black', 'White', 'Other')))
#recode GQTYPE--create Institution
c <- b %>% mutate(Institution = factor(ifelse(GQTYPE==1, 1,
                                              ifelse(GQTYPE==2, 2, 3)),
                                       labels = c('Institution','Prison prior to 1990', 'Other Group Quarters')))

#filter out Other Institution prior to 1990 and Female to get total male prison population
e <- c %>% filter(Institution !='Other Group Quarters')
f <- e %>% filter(SEX==1)

#aggregate data by year, STATEFIP, and Race and apply correction factor for 1990 and after
prisontotal <- f %>% group_by(YEAR, STATEFIP, Race) %>% summarise(NumberTotal=sum(PERWT)) %>% mutate(NumberAdj=ifelse(YEAR>=1990, ifelse(Race=='Black', NumberTotal*0.72, ifelse(Race=='White', NumberTotal*.40, NumberTotal*.58)), NumberTotal))

#get total for year
prisonyr <- prisontotal %>% group_by(YEAR,STATEFIP) %>% summarise(NumberYear=sum(NumberAdj))

#join so I can calculate percent later
prisonpop <- left_join(prisontotal, prisonyr, by = c('YEAR','STATEFIP'))

#calculate percent
prisonpct <- prisonpop %>% mutate(Percent = NumberAdj/NumberYear)

#filter for just black
prisonblackpct <- prisonpct %>% filter(Race == 'Black')

#used to determine "bins"
cuts <- quantcut(prisonblackpct$Percent, q=seq(0,1,.2))

#joining data to map dataframe
#change STATEFIP to integer
newmap <- mapdata %>% mutate(STATEI=as.integer(STATEFIP))

#create "bins"
prisoncats <- prisonblackpct %>% mutate(Percentage = factor(ifelse(Percent<=.10, 1,
                                                              ifelse(Percent<=.30, 2,
                                                                     ifelse(Percent<=.50, 3,
                                                                            ifelse(Percent<=.70, 4,5))))))
levels(prisoncats$Percentage) <- c('0-10%', '>10-30%', '>30-50%', '>50-70%', '70%+')

#joing with map
prisonmap <- left_join(prisoncats, newmap, by = c('STATEFIP' = 'STATEI')) %>% arrange(order)

#Animating map
anmap <- map1 +
  geom_polygon(data=prisonmap, aes(x=long, y=lat, group=group, fill=Percentage, frame=YEAR), color='black') +
  labs(title= 'Percent of Male African Americans of Total Male Prison Population By State, ')

gg_animate(anmap, ani.width=1500, ani.height=1000, 'AfAmofTotalPrison.gif')

getPalette = colorRampPalette(brewer.pal(9, 'Reds'))

map2 <- map1 + scale_fill_manual(values=getPalette(5)) +
  geom_polygon(data=filter(prisonmap, YEAR==1940), aes(x=long, y=lat, group=group, fill=Percentage), color= 'black')
png('mapviz2YAY.png', width= 1500, height=1000)
print(map2)
dev.off()

#for loop for a map of each year
for (year in unique(prisonmap$YEAR)) {
  map2 <-map1 + theme_bw(base_size=24) +
    geom_polygon(data=filter(prisonmap, YEAR==year),
                 aes(x=long, y=lat, group=group, fill=Percentage), color='black') +
    labs(title=paste('Percent of Male African Americans of Total Male Prison Population By State,',year, sep=' '))
  png(paste('mapviz2YAY_', year,'.png', sep=''), width=1500, height=1000)
  print(map2)
  dev.off()
}


#FIGURE 4: Animated Map of Percent of Males in Prison By State, 1920-2010

#load packages
library(readr)
library(dplyr)
library(ggplot2)
library(RColorBrewer)
library(ggmap)
library(maptools)
library(gtools)
library(devtools)
library(gganimate)

#read in map dataframe
mapdata <-read_csv('data/map.csv')

#Create map base
map1 <-ggplot() + scale_fill_brewer(palette='Purples') + theme_nothing(legend=TRUE) +
  geom_polygon(data=mapdata, aes(x=long, y=lat, group=group), fill='white', color='black')
png('mapped.png', width=1500, height=1000)
print(map1)
dev.off()

#read in data extract
ipums <- read_csv('data/FINALFINALDATA.csv', col_types = cols(PERWT=col_double()))

#filter age and exclude Alaska and Hawaii prior to 1960 and DC
a <- ipums %>% filter((AGE>=15 & AGE<=70) & (STATEFIP!=11) & ((!(STATEFIP %in% c(2,15)) | YEAR >=1960)))


#recode GQTYPE--create Institution
c <- a %>% mutate(Institution = factor(ifelse(GQTYPE==1, 1,
                                              ifelse(GQTYPE==2, 2, 3)),
                                       labels = c('Institution','Prison prior to 1990', 'Other Group Quarters')))

#data frame for total men in state
totalmale <- c %>% filter(SEX==1) %>% group_by(YEAR, STATEFIP) %>% summarise(Number=sum(PERWT))

#data frame for men institutionalized in state--apply correction factor for 1990 and after
totalprison <- c %>% filter(SEX==1 & Institution!='Other Group Quarters') %>% group_by(YEAR, STATEFIP) %>% summarise(Prison=sum(PERWT)) %>% mutate(NumberAdj=ifelse(YEAR>=1990, Prison *0.5, Prison))

#join
totalmaledif <- left_join(totalmale, totalprison)

#create percentage variable
malepct <- totalmaledif %>% mutate(Percent = NumberAdj/Number)

#used to make "bins"
cuts <- quantcut(malepct$Percent, q=seq(0, 1, .2))

#joining data to map dataframe
newmap <- mapdata %>% mutate(STATEI=as.integer(STATEFIP))

#create "bins" by percent
prisoncats <- malepct %>% mutate(Percentage = factor(ifelse(Percent<=.003, 1,
                                                             ifelse(Percent<=.005, 2,
                                                                    ifelse(Percent<=.007, 3,
                                                                           ifelse(Percent<=.009, 4,5))))))
levels(prisoncats$Percentage) <- c('0-0.3%', '0.3-0.5%', '0.5-0.7%', '0.7-0.9%', '0.9%+')

#join to map
prisonmap <- left_join(prisoncats, newmap, by = c('STATEFIP' = 'STATEI')) %>% arrange(order)

#Animating map
anmap <- map1 +
  geom_polygon(data=prisonmap, aes(x=long, y=lat, group=group, fill=Percentage, frame=YEAR), color='black') +
  labs(title= 'Percent of Men in Prison by State, ')

gg_animate(anmap, ani.width=1500, ani.height=1000, 'MeninPrison.gif')

getPalette = colorRampPalette(brewer.pal(9, 'Purples'))

map2 <- map1 + scale_fill_manual(values=getPalette(5)) +
  geom_polygon(data=filter(prisonmap, YEAR==1940), aes(x=long, y=lat, group=group, fill=Percentage), color= 'black')
png('vizNEW.png', width= 1500, height=1000)
print(map2)
dev.off()

#for loop to make map for each year
for (year in unique(prisonmap$YEAR)) {
  map2 <-map1 + theme_bw(base_size=24) +
    geom_polygon(data=filter(prisonmap, YEAR==year),
                 aes(x=long, y=lat, group=group, fill=Percentage), color='black') +
    labs(title=paste('Percent of Men in Prison by State,',year, sep=' '))
  png(paste('mapvizNEW_', year,'.png', sep=''), width=1500, height=1000)
  print(map2)
  dev.off()
}

#FIGURE 5: Animated Map of Percent of African American men in Prison of Total African American By State 1940-2010

#load packages
library(readr)
library(dplyr)
library(ggplot2)
library(RColorBrewer)
library(ggmap)
library(maptools)
library(gtools)
library(devtools)
library(gganimate)

#read in map dataframe
mapdata <-read_csv('data/map.csv')

#Create map base
map1 <-ggplot() + scale_fill_brewer(palette='Blues') + theme_nothing(legend=TRUE) +
  geom_polygon(data=mapdata, aes(x=long, y=lat, group=group), fill='white', color='black')
png('mapped.png', width=1500, height=1000)
print(map1)
dev.off()

#read in data extract
ipums <- read_csv('data/FINALFINALDATA.csv', col_types = cols(PERWT=col_double()))

#filter age and exclude Alaska and Hawaii prior to 1960 and DC
a <- ipums %>% filter((AGE>=15 & AGE<=70) & (STATEFIP!=11) & ((!(STATEFIP %in% c(2,15)) | YEAR >=1960)))

#recode RACESING
b <- a %>% mutate(Race = factor(ifelse(RACESING==2, 1,
                                        ifelse(RACESING==1, 2, 3)),
                                 labels = c('Black', 'White', 'Other')))

#recode GQTYPE--create Institution
c <- b %>% mutate(Institution = factor(ifelse(GQTYPE==1, 1,
                                              ifelse(GQTYPE==2, 2, 3)),
                                       labels = c('Institution','Prison prior to 1990', 'Other Group Quarters')))

#filter out Female to get only males
e <- c %>% filter(SEX==1)

#data frame for total black population by state
totalblack <- e %>% filter(Race=='Black') %>% group_by(YEAR, STATEFIP) %>% summarise(TotalBlack=sum(PERWT))

#data frame for black prisoners
prisonblack <- e %>% filter(Race=='Black' & Institution!='Other Group Quarters') %>% group_by(YEAR, STATEFIP) %>% summarise(NumberPrison=sum(PERWT))

#apply correction factor for 1990 and after
prisonblackcorrect <- prisonblack %>% group_by(YEAR, STATEFIP) %>% mutate(NumberAdj=ifelse(YEAR>=1990, NumberPrison*0.72, NumberPrison))

#join data frames
blackdifprison <- left_join(prisonblackcorrect, totalblack, by = c('YEAR','STATEFIP'))

#create percentage variable
blackpct <- blackdifprison %>% mutate(Percent = NumberAdj/TotalBlack)

#used to make "bins" for percent
cuts <- quantcut(blackpct$Percent, q=seq(0, 1, .2))

#joining data to map dataframe
#change STATEFIP to integer
newmap <- mapdata %>% mutate(STATEI=as.integer(STATEFIP))

#create categories by population
prisoncats <- blackpct %>% mutate(Percentage = factor(ifelse(Percent<=.02, 1,
                                                              ifelse(Percent<=.03, 2,
                                                                     ifelse(Percent<=.04, 3,
                                                                            ifelse(Percent<=.05, 4,5))))))
levels(prisoncats$Percentage) <- c('0-2%', '2-3%', '3-4%', '4-5%', '5%+')

#join to map
prisonmap <- left_join(prisoncats, newmap, by = c('STATEFIP' = 'STATEI')) %>% arrange(order)

#Animating map
anmap <- map1 +
  geom_polygon(data=prisonmap, aes(x=long, y=lat, group=group, fill=Percentage, frame=YEAR), color='black') +
  labs(title= 'Percent of African American Males in Prison of Total Afican American Populaiton By State, ')

gg_animate(anmap, ani.width=1500, ani.height=1000, 'AnimationStationed.gif')

getPalette = colorRampPalette(brewer.pal(9, 'Blues'))

map2 <- map1 + scale_fill_manual(values=getPalette(5)) +
  geom_polygon(data=filter(prisonmap, YEAR==1940), aes(x=long, y=lat, group=group, fill=Percentage), color= 'black')
png('FINALviz4.png', width= 1500, height=1000)
print(map2)
dev.off()

#for loop to make map for each year
for (year in unique(prisonmap$YEAR)) {
  map2 <-map1 + theme_bw(base_size=36) +
    geom_polygon(data=filter(prisonmap, YEAR==year),
                 aes(x=long, y=lat, group=group, fill=Percentage), color='black') +
    labs(size=36, title=paste('Percent of African American Males in Prison of Total Afican American Populaiton By State,',year, sep=' '))
  png(paste('FINALviz4YAY_', year,'.png', sep=''), width=1500, height=1000)
  print(map2)
  dev.off()
}

#FIGURE 6: Map of Segregation Indices By State 1940-2010

#load packages
library(readr)
library(dplyr)
library(ggplot2)
library(RColorBrewer)
library(ggmap)
library(maptools)
library(gtools)
library(devtools)
library(gganimate)

#read in map dataframe
mapdata <-read_csv('data/map.csv')

#Create map base
map1 <-ggplot() + scale_fill_brewer(palette='Greens') + theme_nothing(legend=TRUE) +
  geom_polygon(data=mapdata, aes(x=long, y=lat, group=group), fill='white', color='black')
png('mapped.png', width=1500, height=1000)
print(map1)
dev.off()

#read in data extract
ipums <- read_csv('data/SegregationIndicesByState.csv')

ipums <- ipums %>% arrange(State)

#used to make bins
cuts <- quantcut(ipums$Index, q=seq(0,1,.2))

#create "bins" for segregation indices
segcats <- ipums %>% mutate(Indices = factor(ifelse(Index<=55, 1,
                                                             ifelse(Index<=59, 2,
                                                                    ifelse(Index<=62, 3,
                                                                           ifelse(Index<=68, 4,5))))))
levels(segcats$Indices) <- c('0-55', '56-59', '60-62', '63-68', '69+')

#join to map
segmap <- left_join(segcats, mapdata, by = c('State' = 'id')) %>% arrange(order)

map2 <- map1 +
  geom_polygon(data=segmap, aes(x=long, y=lat, group=group, fill=Indices), color= 'black') +
  labs(title = 'Segregation Indices by State 2005-9')
png('mapseg.png', width= 1500, height=1000)
print(map2)
dev.off()

#THE END
	#Morgan Waterman
	#US History Through Census Data
	#Final Project: Race, Segregation, and Incarceration in the United States, 1920-2010

	#FIGURE 1: Spine Graph of Prison Population by Race 1920-2010

	#load packages
	library(dplyr)
	library(readr)
	library(ggplot2)
	library(RColorBrewer)
	library(scales)

	#Program to print plots
	printplot <- function(plot, filename) {
	png(paste(filename,'.png', sep=''), height= 500, width = 1000)
	print(plot)
	dev.off()
	}

	#Read in data extract
	ipums <- read_csv('data/FINALFINALDATA.csv', col_types = cols(PERWT=col_double()))

	#Filter for age and exclude Alaska and Hawaii and DC
	a <- ipums %>% filter(AGE>=15 & AGE<=70)
	aa<- a %>% filter(STATEFIP!=11 & (!(STATEFIP %in% c(2, 15)) \| YEAR >=1960))

	#recode RACESING
	b <- aa %>% mutate(Race = factor(ifelse(RACESING==2, 1,
	ifelse(RACESING==1, 2, 3)),
	labels = c('Black', 'White', 'Other')))


	#recode GQTYPE--create Institution
	c <- b %>% mutate(Institution = factor(ifelse(GQTYPE==1, 1,
	ifelse(GQTYPE==2, 2, 3)),
	labels = c('Institution','Prison prior to 1990', 'Other Group Quarters')))

	#filter out Other Institution prior to 1990 and Female to get total male prison population
	e <- c %>% filter(Institution !='Other Group Quarters')
	f <- e %>% filter(SEX==1)

	#aggregate data by Year and Race--apply correction factor for 1990 and later
	prisontotal <- f %>% group_by(YEAR, Race) %>% summarise(NumberTotal=sum(PERWT)) %>% mutate(NumberAdj=ifelse(YEAR>=1990, ifelse(Race=='Black', NumberTotal0.72, ifelse(Race=='White', NumberTotal.40, NumberTotal*.58)), NumberTotal))

	#Sum
	prisonrace <- prisontotal %>% group_by(YEAR) %>% summarise(NumberRace=sum(NumberAdj))

	#Join so i can calculate percent
	prisonjoin <- left_join(prisontotal, prisonrace)

	#Calculate percent
	prisonpct <- prisonjoin %>% mutate(Percent = NumberAdj/NumberRace)

	#Graphing
	graphprison <- ggplot(prisonpct, aes(x= YEAR, y=Percent, fill=Race)) +
	geom_bar(stat='identity', aes(width=rescale(NumberRace, c(5, 10)))) +
	labs(fill = 'Race of Prisoners', title = 'Percent of Prison Population by Race, 1920-2010', x = 'Year', y= 'Percent of Prisoners') +
	theme_bw(base_size=8) +
	scale_x_continuous(breaks=c(1920, 1930, 1940, 1950, 1960, 1970, 1980, 1990, 2000, 2010))+
	scale_y_continuous(labels=scales::percent)
	printplot(graphprison, 'FINALspine')


	#FIGURE 2: Animated Map of Percent of African Americans Males of Total State Male Population 1920-2010

	#Load packages
	library(readr)
	library(dplyr)
	library(ggplot2)
	library(RColorBrewer)
	library(ggmap)
	library(maptools)
	library(gtools)
	library(devtools)
	library(gganimate)

	#Read in map dataframe
	mapdata <-read_csv('data/map.csv')

	#Create map base
	map1 <-ggplot() + scale_fill_brewer(palette='Oranges') + theme_nothing(legend=TRUE) +
	geom_polygon(data=mapdata, aes(x=long, y=lat, group=group), fill='white', color='black')
	png('mapped.png', width=1500, height=1000)
	print(map1)
	dev.off()

	#Read in data extract
	ipums <- read_csv('data/FINALFINALDATA.csv', col_types = cols(PERWT=col_double()))

	#Filter for age and exclude DC & Alaska and Hawaii prior to 1960
	a <- ipums %>% filter((AGE>=15 & AGE<=70) & (STATEFIP!=11) & ((!(STATEFIP %in% c(2,15)) \| YEAR >=1960)))

	#recode RACESING
	b <- a %>% mutate(Race = factor(ifelse(RACESING==2, 1,
	ifelse(RACESING==1, 2, 3)),
	labels = c('Black', 'White', 'Other')))

	#recode GQTYPE--create Institution
	#not used in this map
	c <- b %>% mutate(Institution = factor(ifelse(GQTYPE==1, 1,
	ifelse(GQTYPE==2, 2, 3)),
	labels = c('Institution','Prison prior to 1990', 'Other Group Quarters')))

	#Filter out Female for total male population
	totalall<- c %>% filter(SEX==1) %>% group_by(YEAR,STATEFIP) %>% summarise(TotalAll=sum(PERWT))

	#data frame for total black population by state
	totalblack <- c %>% filter(SEX==1 & Race=='Black') %>% group_by(YEAR, STATEFIP) %>% summarise(TotalBlack=sum(PERWT))

	#join data frames
	totalpop <- left_join(totalall, totalblack, by = c('YEAR','STATEFIP'))

	#create percentage variable
	blackpct <- totalpop %>% mutate(Percent = TotalBlack/TotalAll)

	#used to determine "bins" in map
	cuts <- quantcut(blackpct$Percent, q=seq(0,1,.2))

	#joining data to map dataframe
	#change STATEFIP to integer
	newmap <- mapdata %>% mutate(STATEI=as.integer(STATEFIP))

	#Creating "bins" for percentages
	totalcats <- blackpct %>% mutate(Percentage = factor(ifelse(Percent<=.01, 1,
	ifelse(Percent<=.03, 2,
	ifelse(Percent<=.07, 3,
	ifelse(Percent<=.15, 4,5))))))
	levels(totalcats$Percentage) <- c('0-1%', '1-3%', '3-7%', '7-15%', '15%+')

	#joining to map
	prisonmap <- left_join(totalcats, newmap, by = c('STATEFIP' = 'STATEI')) %>% arrange(order)

	prisonmap <- prisonmap %>% arrange(order)

	#Animating map
	anmap <- map1 +
	geom_polygon(data=prisonmap, aes(x=long, y=lat, group=group, fill=Percentage, frame=YEAR), color='black') +
	labs(title= 'Percent of African Americans Males of Total State Male Population, ')

	gg_animate(anmap, ani.width=1500, ani.height=1000, 'AfAmofTotalPop.gif')

	getPalette = colorRampPalette(brewer.pal(9, 'Oranges'))

	map2 <- map1 + scale_fill_manual(values=getPalette(5)) +
	geom_polygon(data=filter(prisonmap, YEAR==1940), aes(x=long, y=lat, group=group, fill=Percentage), color= 'black')
	png('mapviz3YAY.png', width= 1500, height=1000)
	print(map2)
	dev.off()

	#for loop to make a map for each year
	for (year in unique(prisonmap$YEAR)) {
	map2 <-map1 + theme_bw(base_size=24) +
	geom_polygon(data=filter(prisonmap, YEAR==year),
	aes(x=long, y=lat, group=group, fill=Percentage), color='black') +
	labs(title=paste('Percent of African Americans Males of Total State Male Population,',year, sep=' '))
	png(paste('mapviz3YAY_', year,'.png', sep=''), width=1500, height=1000)
	print(map2)
	dev.off()
	}


	#FIGURE 3: Animated Map of Percent of Male African Americans in Total Prison Population By State, 1920-2010

	#load packages
	library(readr)
	library(dplyr)
	library(ggplot2)
	library(RColorBrewer)
	library(ggmap)
	library(maptools)
	library(gtools)
	library(devtools)
	library(gganimate)

	#read in map dataframe
	mapdata <-read_csv('data/map.csv')

	#Create map base
	map1 <-ggplot() + scale_fill_brewer(palette='Reds') + theme_nothing(legend=TRUE) +
	geom_polygon(data=mapdata, aes(x=long, y=lat, group=group), fill='white', color='black')
	png('maprace.png', width=1500, height=1000)
	print(map1)
	dev.off()

	#read in data extract
	ipums <- read_csv('data/FINALFINALDATA.csv', col_types = cols(PERWT=col_double()))

	#filter for age and exclude DC & Alaska and Hawaii prior to 1960
	a <- ipums %>% filter((AGE>=15 & AGE<=70) & (STATEFIP!=11) & ((!(STATEFIP %in% c(2,15)) \| YEAR >=1960)))

	#recode RACESING
	b <- a %>% mutate(Race = factor(ifelse(RACESING==2, 1,
	ifelse(RACESING==1, 2, 3)),
	labels = c('Black', 'White', 'Other')))
	#recode GQTYPE--create Institution
	c <- b %>% mutate(Institution = factor(ifelse(GQTYPE==1, 1,
	ifelse(GQTYPE==2, 2, 3)),
	labels = c('Institution','Prison prior to 1990', 'Other Group Quarters')))

	#filter out Other Institution prior to 1990 and Female to get total male prison population
	e <- c %>% filter(Institution !='Other Group Quarters')
	f <- e %>% filter(SEX==1)

	#aggregate data by year, STATEFIP, and Race and apply correction factor for 1990 and after
	prisontotal <- f %>% group_by(YEAR, STATEFIP, Race) %>% summarise(NumberTotal=sum(PERWT)) %>% mutate(NumberAdj=ifelse(YEAR>=1990, ifelse(Race=='Black', NumberTotal0.72, ifelse(Race=='White', NumberTotal.40, NumberTotal*.58)), NumberTotal))

	#get total for year
	prisonyr <- prisontotal %>% group_by(YEAR,STATEFIP) %>% summarise(NumberYear=sum(NumberAdj))

	#join so I can calculate percent later
	prisonpop <- left_join(prisontotal, prisonyr, by = c('YEAR','STATEFIP'))

	#calculate percent
	prisonpct <- prisonpop %>% mutate(Percent = NumberAdj/NumberYear)

	#filter for just black
	prisonblackpct <- prisonpct %>% filter(Race == 'Black')

	#used to determine "bins"
	cuts <- quantcut(prisonblackpct$Percent, q=seq(0,1,.2))

	#joining data to map dataframe
	#change STATEFIP to integer
	newmap <- mapdata %>% mutate(STATEI=as.integer(STATEFIP))

	#create "bins"
	prisoncats <- prisonblackpct %>% mutate(Percentage = factor(ifelse(Percent<=.10, 1,
	ifelse(Percent<=.30, 2,
	ifelse(Percent<=.50, 3,
	ifelse(Percent<=.70, 4,5))))))
	levels(prisoncats$Percentage) <- c('0-10%', '>10-30%', '>30-50%', '>50-70%', '70%+')

	#joing with map
	prisonmap <- left_join(prisoncats, newmap, by = c('STATEFIP' = 'STATEI')) %>% arrange(order)

	#Animating map
	anmap <- map1 +
	geom_polygon(data=prisonmap, aes(x=long, y=lat, group=group, fill=Percentage, frame=YEAR), color='black') +
	labs(title= 'Percent of Male African Americans of Total Male Prison Population By State, ')

	gg_animate(anmap, ani.width=1500, ani.height=1000, 'AfAmofTotalPrison.gif')

	getPalette = colorRampPalette(brewer.pal(9, 'Reds'))

	map2 <- map1 + scale_fill_manual(values=getPalette(5)) +
	geom_polygon(data=filter(prisonmap, YEAR==1940), aes(x=long, y=lat, group=group, fill=Percentage), color= 'black')
	png('mapviz2YAY.png', width= 1500, height=1000)
	print(map2)
	dev.off()

	#for loop for a map of each year
	for (year in unique(prisonmap$YEAR)) {
	map2 <-map1 + theme_bw(base_size=24) +
	geom_polygon(data=filter(prisonmap, YEAR==year),
	aes(x=long, y=lat, group=group, fill=Percentage), color='black') +
	labs(title=paste('Percent of Male African Americans of Total Male Prison Population By State,',year, sep=' '))
	png(paste('mapviz2YAY_', year,'.png', sep=''), width=1500, height=1000)
	print(map2)
	dev.off()
	}


	#FIGURE 4: Animated Map of Percent of Males in Prison By State, 1920-2010

	#load packages
	library(readr)
	library(dplyr)
	library(ggplot2)
	library(RColorBrewer)
	library(ggmap)
	library(maptools)
	library(gtools)
	library(devtools)
	library(gganimate)

	#read in map dataframe
	mapdata <-read_csv('data/map.csv')

	#Create map base
	map1 <-ggplot() + scale_fill_brewer(palette='Purples') + theme_nothing(legend=TRUE) +
	geom_polygon(data=mapdata, aes(x=long, y=lat, group=group), fill='white', color='black')
	png('mapped.png', width=1500, height=1000)
	print(map1)
	dev.off()

	#read in data extract
	ipums <- read_csv('data/FINALFINALDATA.csv', col_types = cols(PERWT=col_double()))

	#filter age and exclude Alaska and Hawaii prior to 1960 and DC
	a <- ipums %>% filter((AGE>=15 & AGE<=70) & (STATEFIP!=11) & ((!(STATEFIP %in% c(2,15)) \| YEAR >=1960)))


	#recode GQTYPE--create Institution
	c <- a %>% mutate(Institution = factor(ifelse(GQTYPE==1, 1,
	ifelse(GQTYPE==2, 2, 3)),
	labels = c('Institution','Prison prior to 1990', 'Other Group Quarters')))

	#data frame for total men in state
	totalmale <- c %>% filter(SEX==1) %>% group_by(YEAR, STATEFIP) %>% summarise(Number=sum(PERWT))

	#data frame for men institutionalized in state--apply correction factor for 1990 and after
	totalprison <- c %>% filter(SEX==1 & Institution!='Other Group Quarters') %>% group_by(YEAR, STATEFIP) %>% summarise(Prison=sum(PERWT)) %>% mutate(NumberAdj=ifelse(YEAR>=1990, Prison *0.5, Prison))

	#join
	totalmaledif <- left_join(totalmale, totalprison)

	#create percentage variable
	malepct <- totalmaledif %>% mutate(Percent = NumberAdj/Number)

	#used to make "bins"
	cuts <- quantcut(malepct$Percent, q=seq(0, 1, .2))

	#joining data to map dataframe
	newmap <- mapdata %>% mutate(STATEI=as.integer(STATEFIP))

	#create "bins" by percent
	prisoncats <- malepct %>% mutate(Percentage = factor(ifelse(Percent<=.003, 1,
	ifelse(Percent<=.005, 2,
	ifelse(Percent<=.007, 3,
	ifelse(Percent<=.009, 4,5))))))
	levels(prisoncats$Percentage) <- c('0-0.3%', '0.3-0.5%', '0.5-0.7%', '0.7-0.9%', '0.9%+')

	#join to map
	prisonmap <- left_join(prisoncats, newmap, by = c('STATEFIP' = 'STATEI')) %>% arrange(order)

	#Animating map
	anmap <- map1 +
	geom_polygon(data=prisonmap, aes(x=long, y=lat, group=group, fill=Percentage, frame=YEAR), color='black') +
	labs(title= 'Percent of Men in Prison by State, ')

	gg_animate(anmap, ani.width=1500, ani.height=1000, 'MeninPrison.gif')

	getPalette = colorRampPalette(brewer.pal(9, 'Purples'))

	map2 <- map1 + scale_fill_manual(values=getPalette(5)) +
	geom_polygon(data=filter(prisonmap, YEAR==1940), aes(x=long, y=lat, group=group, fill=Percentage), color= 'black')
	png('vizNEW.png', width= 1500, height=1000)
	print(map2)
	dev.off()

	#for loop to make map for each year
	for (year in unique(prisonmap$YEAR)) {
	map2 <-map1 + theme_bw(base_size=24) +
	geom_polygon(data=filter(prisonmap, YEAR==year),
	aes(x=long, y=lat, group=group, fill=Percentage), color='black') +
	labs(title=paste('Percent of Men in Prison by State,',year, sep=' '))
	png(paste('mapvizNEW_', year,'.png', sep=''), width=1500, height=1000)
	print(map2)
	dev.off()
	}

	#FIGURE 5: Animated Map of Percent of African American men in Prison of Total African American By State 1940-2010

	#load packages
	library(readr)
	library(dplyr)
	library(ggplot2)
	library(RColorBrewer)
	library(ggmap)
	library(maptools)
	library(gtools)
	library(devtools)
	library(gganimate)

	#read in map dataframe
	mapdata <-read_csv('data/map.csv')

	#Create map base
	map1 <-ggplot() + scale_fill_brewer(palette='Blues') + theme_nothing(legend=TRUE) +
	geom_polygon(data=mapdata, aes(x=long, y=lat, group=group), fill='white', color='black')
	png('mapped.png', width=1500, height=1000)
	print(map1)
	dev.off()

	#read in data extract
	ipums <- read_csv('data/FINALFINALDATA.csv', col_types = cols(PERWT=col_double()))

	#filter age and exclude Alaska and Hawaii prior to 1960 and DC
	a <- ipums %>% filter((AGE>=15 & AGE<=70) & (STATEFIP!=11) & ((!(STATEFIP %in% c(2,15)) \| YEAR >=1960)))

	#recode RACESING
	b <- a %>% mutate(Race = factor(ifelse(RACESING==2, 1,
	ifelse(RACESING==1, 2, 3)),
	labels = c('Black', 'White', 'Other')))

	#recode GQTYPE--create Institution
	c <- b %>% mutate(Institution = factor(ifelse(GQTYPE==1, 1,
	ifelse(GQTYPE==2, 2, 3)),
	labels = c('Institution','Prison prior to 1990', 'Other Group Quarters')))

	#filter out Female to get only males
	e <- c %>% filter(SEX==1)

	#data frame for total black population by state
	totalblack <- e %>% filter(Race=='Black') %>% group_by(YEAR, STATEFIP) %>% summarise(TotalBlack=sum(PERWT))

	#data frame for black prisoners
	prisonblack <- e %>% filter(Race=='Black' & Institution!='Other Group Quarters') %>% group_by(YEAR, STATEFIP) %>% summarise(NumberPrison=sum(PERWT))

	#apply correction factor for 1990 and after
	prisonblackcorrect <- prisonblack %>% group_by(YEAR, STATEFIP) %>% mutate(NumberAdj=ifelse(YEAR>=1990, NumberPrison*0.72, NumberPrison))

	#join data frames
	blackdifprison <- left_join(prisonblackcorrect, totalblack, by = c('YEAR','STATEFIP'))

	#create percentage variable
	blackpct <- blackdifprison %>% mutate(Percent = NumberAdj/TotalBlack)

	#used to make "bins" for percent
	cuts <- quantcut(blackpct$Percent, q=seq(0, 1, .2))

	#joining data to map dataframe
	#change STATEFIP to integer
	newmap <- mapdata %>% mutate(STATEI=as.integer(STATEFIP))

	#create categories by population
	prisoncats <- blackpct %>% mutate(Percentage = factor(ifelse(Percent<=.02, 1,
	ifelse(Percent<=.03, 2,
	ifelse(Percent<=.04, 3,
	ifelse(Percent<=.05, 4,5))))))
	levels(prisoncats$Percentage) <- c('0-2%', '2-3%', '3-4%', '4-5%', '5%+')

	#join to map
	prisonmap <- left_join(prisoncats, newmap, by = c('STATEFIP' = 'STATEI')) %>% arrange(order)

	#Animating map
	anmap <- map1 +
	geom_polygon(data=prisonmap, aes(x=long, y=lat, group=group, fill=Percentage, frame=YEAR), color='black') +
	labs(title= 'Percent of African American Males in Prison of Total Afican American Populaiton By State, ')

	gg_animate(anmap, ani.width=1500, ani.height=1000, 'AnimationStationed.gif')

	getPalette = colorRampPalette(brewer.pal(9, 'Blues'))

	map2 <- map1 + scale_fill_manual(values=getPalette(5)) +
	geom_polygon(data=filter(prisonmap, YEAR==1940), aes(x=long, y=lat, group=group, fill=Percentage), color= 'black')
	png('FINALviz4.png', width= 1500, height=1000)
	print(map2)
	dev.off()

	#for loop to make map for each year
	for (year in unique(prisonmap$YEAR)) {
	map2 <-map1 + theme_bw(base_size=36) +
	geom_polygon(data=filter(prisonmap, YEAR==year),
	aes(x=long, y=lat, group=group, fill=Percentage), color='black') +
	labs(size=36, title=paste('Percent of African American Males in Prison of Total Afican American Populaiton By State,',year, sep=' '))
	png(paste('FINALviz4YAY_', year,'.png', sep=''), width=1500, height=1000)
	print(map2)
	dev.off()
	}

	#FIGURE 6: Map of Segregation Indices By State 1940-2010

	#load packages
	library(readr)
	library(dplyr)
	library(ggplot2)
	library(RColorBrewer)
	library(ggmap)
	library(maptools)
	library(gtools)
	library(devtools)
	library(gganimate)

	#read in map dataframe
	mapdata <-read_csv('data/map.csv')

	#Create map base
	map1 <-ggplot() + scale_fill_brewer(palette='Greens') + theme_nothing(legend=TRUE) +
	geom_polygon(data=mapdata, aes(x=long, y=lat, group=group), fill='white', color='black')
	png('mapped.png', width=1500, height=1000)
	print(map1)
	dev.off()

	#read in data extract
	ipums <- read_csv('data/SegregationIndicesByState.csv')

	ipums <- ipums %>% arrange(State)

	#used to make bins
	cuts <- quantcut(ipums$Index, q=seq(0,1,.2))

	#create "bins" for segregation indices
	segcats <- ipums %>% mutate(Indices = factor(ifelse(Index<=55, 1,
	ifelse(Index<=59, 2,
	ifelse(Index<=62, 3,
	ifelse(Index<=68, 4,5))))))
	levels(segcats$Indices) <- c('0-55', '56-59', '60-62', '63-68', '69+')

	#join to map
	segmap <- left_join(segcats, mapdata, by = c('State' = 'id')) %>% arrange(order)

	map2 <- map1 +
	geom_polygon(data=segmap, aes(x=long, y=lat, group=group, fill=Indices), color= 'black') +
	labs(title = 'Segregation Indices by State 2005-9')
	png('mapseg.png', width= 1500, height=1000)
	print(map2)
	dev.off()

	#THE END