lfortin-117

#Construction and General Labor

library(readr)
library(dplyr)
library(ggplot2)
library(readr)
library(RColorBrewer)
library(ggmap)
library(maptools)
library(gtools)

lfortin-117

#Part A For Boxplot and Line
library(readr)
library(dplyr)
library(ggplot2)
library(RColorBrewer)
library(scales)

setwd('/users/emily/dropbox/hist90_01/fall2016/labs/10_27')

lfortin-117

#Part 1
library(readr)
library(dplyr)
library(ggplot2)
library(RColorBrewer)


#Reading in the data, filtering out children and creating region
#excluding Hawaii and Alaska before 1960, and renaming race variable
first <- read_csv('Lab6_4.csv', col_types = cols(HHWT = col_double(), PERWT = col_double())) 

lfortin-117

library(readr)
library(dplyr)
library(ggplot2)
library(readr)
library(RColorBrewer)
library(ggmap)
library(maptools)
library(gtools)

#Loading in the blank map of the United States and plotting

lfortin-117

library(dplyr)
library(ggplot2)
library(readr)
library(RColorBrewer)

#Read in the IPUMS data
x <- read_csv('LAB4.csv') %>% filter((BPL>=500 & BPL<=502) | (MBPL>=500 & MBPL<=502) | (FBPL>=500 & FBPL<=502))


#Create a vector for age category labels

lfortin-117

library(dplyr)
library(ggplot2)
library(readr)
library(RColorBrewer)

x <- read_csv('LAB3.csv') %>% filter(AGE>=15 & AGE<=65 & !(STATEFIP %in% c(2,15)))

#Recode race variable
a <- x %>% mutate(RACEC= factor(ifelse (RACE==1, 1,
                                ifelse(RACE==2, 2,