updata

ESRofCA.R

@@ -10,6 +10,7 @@ pusa <- fread("~/desktop/project1/csv_pus/ss13pusa.csv", select = cols)
 pusb <- fread("~/desktop/project1/csv_pus/ss13pusb.csv", select = cols)
 pus<- rbind(pusa, pusb)
 
+##Select the data
 Male <- pus %>%
   na.omit()%>%
   filter(MSP %in% c(3,4,5,6)) %>%
@@ -58,8 +59,17 @@ statecode
 
 Malejob1<- mutate(Male, value = Malejob$count/Male$count*100)
 Malejob1
+Malejob1[5]
+#     ST   count    value
+#(int)   (int)    (dbl)
+# 1   6   3623480  48.75851
 Femalejob1<- mutate(Femalejob, value = Femalejob$count/Female$count*100)
 Femalejob1
+Femalejob1[5]
+#   ST   count    value
+#(int)   (int)    (dbl)
+#1  6  1546252  48.80578
+
 # join state code in table
 Malejob1 <- left_join(Malejob1 , statecode, by.x=c("ST"))
 Femalejob1 <- left_join(Femalejob1 , statecode, by.x=c("ST"))
@@ -71,10 +81,13 @@ visual <- rbind(Malejob1,Femalejob1)
 #plot graph
 AllPlot<- ggplot(visual, aes(x=State, y=value, fill=factor(gender))) +
   geom_bar(stat="identity",position="dodge") + scale_fill_hue(l=40) +
-  ylab("Average emplyoment") + 
-  xlab("state") + ggtitle(paste("Average Employment"," by State")) +
+  ylab("emplyoment ratio") + 
+  xlab("state") + ggtitle(paste("Employment ratio")) +
   theme(axis.text.x = element_text(angle = 30, hjust = 1),
         panel.background = element_rect(fill = 'white' ))
 ggsave(paste("Plot_","_",".png", sep = ""), width = 20, height = 15)
 AllPlot
-##
+##
+##
+#the employment rate of male in CA is 48.75851%
+#the employment rate of female in CA is 48.80578%