Worked on Data proc script

Scripts/Data_Load.r

@@ -109,7 +109,7 @@ CITY_POP <- rbind(CITY_TBL,CITY_POP)
 #Cleanup names
 CITY_POP$City <- gsub("LaGrange","La_Grange",CITY_POP$City)
 COUNTY_POP <- rbind(COUNTY_TBL,COUNTY_POP)
-####################County and City Population DAta for 1990-2000
+####################County and City Population Data for 1990-2000
 if(!file.exists("./Data/Pop_1990s.xls")){download.file('http://eadiv.state.wy.us/pop/c&sc90_00.xls',"./Data/Pop_1990s.xls")}
 TEMP <- read_xls("Data/Pop_1990s.xls",skip=2)[-1:-4,]
 colnames(TEMP)[1] <- "County"
@@ -129,7 +129,7 @@ CITY_POP %>% pull(City) %>% unique %>% sort
 COUNTY_POP <- rbind(TEMP_COUNTY,COUNTY_POP)
 #ggplot(aes(x=Year,y=Population,group=County,color=County),data=COUNTY_POP)+geom_line()
 try(rm(TEMP_CITY,TEMP_COUNTY,TEMP))
-####################County and City Population DAta for 1980-1990
+####################County and City Population Data for 1980-1990
 if(!file.exists("./Data/Pop_1980s.xls")){download.file('http://eadiv.state.wy.us/pop/C&SC8090.xls',"./Data/Pop_1980s.xls")}
 TEMP <- read_xls("Data/Pop_1980s.xls",skip=2)[-1:-4,]
 colnames(TEMP)[1] <- "County"
@@ -148,7 +148,99 @@ COUNTY_POP <- rbind(TEMP_COUNTY,COUNTY_POP)
 #ggplot(aes(x=Year,y=Population,group=County,color=County),data=COUNTY_POP)+geom_line()
 try(rm(TEMP_CITY,TEMP_COUNTY,TEMP))
 
+####################County Population Data for 1980-1990
+if(!file.exists("./Data/Pop_1970s.xls")){download.file('http://eadiv.state.wy.us/pop/Cnty7080.xls',"./Data/Pop_1970s.xls")}
+TEMP <- read_xls("Data/Pop_1970s.xls",skip=2)[-1:-4,]
+colnames(TEMP)[1] <- "County"
+TEMP <- TEMP[1:which(TEMP[,1]=="Weston"),]
+TEMP <- pivot_longer(TEMP,all_of(colnames(TEMP)[-1]),names_to="Year",values_to="Population") %>% mutate(Year=as.integer(Year),Population=as.numeric(Population))
+
+TEMP$County <- gsub(" ","_",TEMP$County)
+
+COUNTY_POP <- rbind(TEMP,COUNTY_POP)
+#ggplot(aes(x=Year,y=Population,group=County,color=County),data=COUNTY_POP)+geom_line()
+try(rm(TEMP))
+###########Old data addtion:Period Ends in 1970
+	#See in part http://eadiv.state.wy.us/demog_data/cntycity_hist.htm
+	LN_OLD <- c(12487,10894,10286,9023,9018,8640) #Missing in 1910
+	Year <-  seq(1920,1970,by=10)
+	TEMP <-	cbind(Year,rep("Lincoln",6),LN_OLD)
+	colnames(TEMP ) <- c("Year","County","Population")
+	TEMP <- as_tibble(TEMP)
+	COUNTY_POP <- rbind(TEMP,COUNTY_POP) %>% arrange(County,Year)
 
 
+	KEM_OLD <- c(843,1517,1884,2026,1667,2028,2292) #1910 forward until 1970
+	Year <-  seq(1910,1970,by=10)
+	TEMP <-	cbind(Year,rep("kemmerer",7),KEM_OLD)
+	colnames(TEMP ) <- c("Year","City","Population")
+	TEMP <- as_tibble(TEMP)
+	CITY_POP <- rbind(TEMP,CITY_POP) 
+
+
+	DIAMOND_OLD <- c(696,726,812,586,415,398,485)
+	TEMP <-	cbind(Year,rep("Diamondvile",7),DIAMOND_OLD)
+	colnames(TEMP ) <- c("Year","City","Population")
+	TEMP <- as_tibble(TEMP)
+	CITY_POP <- rbind(TEMP,CITY_POP)  %>% arrange(City,Year)
+#Add Other Data
+COUNTY_POP <- COUNTY_POP %>% mutate(Year=as.integer(Year))
+WY_COUNTY_DATA_SET <- COUNTY_POP %>% left_join(WY_COUNTY_DATA_SET )
+###Save Population Results
+write_csv(CITY_POP,file="./Data/Cleaned_Data/Wyoming_City_Population.csv") 
+write_csv(WY_COUNTY_DATA_SET ,file="./Data/Cleaned_Data/Wyoming_County_Population.csv")
+saveRDS(CITY_POP,file="./Data/Cleaned_Data/Wyoming_City_Population.Rds") 
+saveRDS(WY_COUNTY_DATA_SET ,file="./Data/Cleaned_Data/Wyoming_County_Population.Rds") 
+
+
+###################Demographics
+if(!file.exists("./Data/Demo_Single_Year_2020s.xls")){download.file('http://eadiv.state.wy.us/Pop/CO_SYASEX24.xlsx',"./Data/Demo_Single_Year_2020s.xls")}
+TEMP <- read_xlsx("./Data/Demo_Single_Year_2020s.xls",skip=2)[,-1]
+TEMP <- TEMP[1:(min(which(is.na(TEMP[,1])))-1),]
+TEMP$YEAR <- year(as.Date(substr((TEMP$YEAR),1,8),format="%m/%d/%Y"))
+DEM_2020_SINGLE <- TEMP
+###Standard Population to adjust FROM
+	#https://hdpulse.nimhd.nih.gov/data-portal/mortality/table?cod=247&cod_options=cod_15&ratetype=aa&ratetype_options=ratetype_2&race=00&race_options=race_6&sex=2&sex_options=sex_3&age=001&age_options=age_11&ruralurban=0&ruralurban_options=ruralurban_3&yeargroup=5&yeargroup_options=year5yearmort_1&statefips=56&statefips_options=area_states&county=56000&county_options=counties_wyoming&comparison=counties_to_us&comparison_options=comparison_counties&radio_comparison=areas&radio_comparison_options=cods_or_areas
+PAGE <- read_html("https://seer.cancer.gov/stdpopulations/stdpop.20ages.html")
+NODE <- html_element(PAGE ,"table")
+TBL <- html_table(NODE)
+TBL <- TBL[,1:2]
+colnames(TBL) <- c("Age_Group","Population")
+DEM_2020_SINGLE
+
+
+####Demographics 2010-2020
+PAGE <- read_html('http://eadiv.state.wy.us/Pop/CO-AS10-20.htm')
+NODE <- html_element(PAGE ,"table")
+TBL <- html_table(NODE)
+
+NAMES <- gsub(" ","_",TBL[5,] %>% t)
+colnames(TBL ) <- NAMES
+TBL <- TBL[-1:-5,c(-4)]
+TBL$County <- gsub(" ","_",gsub("  "," ",gsub(" County","",TBL$County)))
+
+TEMP <-	pivot_longer(TBL,all_of(colnames(TBL)[-1:-3]),names_to="Year",values_to="Population") %>% mutate(Year=as.integer(Year),Population=parse_number(Population))
+TEMP <- TEMP %>% unique
+TEMP <- TEMP %>% filter(!Age_Group=="")
+TEMP$Age_Group <- gsub(" ","_",TEMP$Age_Group)
+DEM_2010 <- pivot_wider(TEMP,names_from=Age_Group,values_from=Population)
+DEM_2010 
+
+####Demographics 2000-2010
+
+PAGE <- read_html('http://eadiv.state.wy.us/Pop/CO-AS01-09.htm')
+NODE <- html_element(PAGE ,"table")
+TBL <- html_table(NODE)
+TBL <- TBL[-1:-4,c(-4,-15,-16)]
+colnames(TBL) <- c("County","Sex","Age_Group",2000:2009)
+TBL$County <- gsub(" ","_",gsub("  "," ",gsub(" County","",TBL$County)))
+
+TEMP <-	pivot_longer(TBL,all_of(colnames(TBL)[-1:-3]),names_to="Year",values_to="Population") %>% mutate(Year=as.integer(Year),Population=parse_number(Population))
+TEMP <- TEMP %>% unique
+TEMP <- TEMP %>% filter(!Age_Group=="")
+TEMP$Age_Group <- gsub(" ","_",TEMP$Age_Group)
+TEMP <- pivot_wider(TEMP,names_from=Age_Group,values_from=Population)
+
+####Demographics 2000-2010