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# Own Children by Family Type
# ACS Tables: B09001, B09002
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# Call the acs package for data processing
library(acs)

# Variables to specify end year of ACS to pull from, as well as the span, which specifies the estimates to pull for that end year (1-year, 3-year, or 5-year), and the geographic level
year_endyear = 2015
year_span = 5 # 1-year estimates are not available at the tract or block group level
fileGeo = "County"

# Additional geography fields for output
countyFIPS = ""
countyName = ""
stateFIPS = ""
stateAbbr = ""
	
if (fileGeo == "BlockGroup") {
	# Block Group Geographies
	mo.geo=geo.make(state=29, county=c(3,13,21,25,37,47,49,63,95,101,107,165,177), tract="*", block.group="*") 
	ks.geo=geo.make(state=20, county=c(1,5,43,45,59,91,103,107,121,209), tract="*", block.group="*")
	
	# Combine the Missouri and Kansas geographies, so we're pulling all data in a single request
	geo = mo.geo + ks.geo
} else if (fileGeo == "Tract") {
	# Tract Geographies:
	mo.geo=geo.make(state=29, county=c(3,13,21,25,37,47,49,63,95,101,107,165,177), tract="*") 
	ks.geo=geo.make(state=20, county=c(1,5,43,45,59,91,103,107,121,209), tract="*")

	# Combine the Missouri and Kansas geographies, so we're pulling all data in a single request
	geo = mo.geo + ks.geo
} else if (fileGeo == "Place") {
	# Place Geographies:
	mo.geo=geo.make(state=29, place="*")
	ks.geo=geo.make(state=20, place="*")

	# Combine the Missouri and Kansas geographies, so we're pulling all data in a single request
	geo = mo.geo + ks.geo
} else if (fileGeo == "County") {
	# County Geographies: 
	# Top 2 are for counties in the MSA, plus counties needed for REACH data (Allen County, KS and Lafayette County, MO)]
	# Bottom 2 are the counties in the MARC region only
	
	#All Counties in the CSA (??) (plus Allen County, KS)
	if (year_span == 5){
		mo.geo=geo.make(state=29, county=c(3,13,21,25,37,47,49,63,95,101,107,165,177)) 
		ks.geo=geo.make(state=20, county=c(1,5,43,45,59,91,103,107,121,209))
	} else {
		#Counties Available within the 1-Year ACS Estimates
		mo.geo=geo.make(state=29, county=c(21,37,47,95,165)) 
		ks.geo=geo.make(state=20, county=c(45,91,103,209))	
	}
	
	# Combine the Missouri and Kansas geographies, so we're pulling all data in a single request
	geo = mo.geo + ks.geo
} else if (fileGeo == "MSA") {
	# MSA Geographies - cannot be pulled by County or State, so getting all
	geo <- geo.make(msa="*") 
	# Set the stateFIPS so that data appends correctly
	stateFIPS = 99
}

# Clean up variables that are no longer needed.
if (fileGeo != "MSA") {	
	rm(mo.geo, ks.geo)
}

# Set up acs.lookup objects for data we want to retrieve
population.under18 = acs.lookup(table.name = "B09001", span=year_span, endyear = year_endyear)
ownChildren.byFamilyType = acs.lookup(table.name="B09002", span=year_span, endyear=year_endyear)

# Select out just those variables we want
population.under18.vars = population.under18[1:10]
ownchildren.byfamilytype.vars = ownChildren.byFamilyType[1:20]
children.vars = population.under18.vars + ownchildren.byfamilytype.vars

# Request/fetch the data, and then add to a dataframe for output
children.data = acs.fetch(endyear=year_endyear, span=year_span, geography=geo, variable=children.vars, dataset="acs")

# Create a complete FIPS code ID for the block group, tract, place, or county - this is what is used to join this data to geography
if (fileGeo == "Tract") {
	myFIPS = paste(geography(children.data)$state, sprintf("%03d",geography(children.data)$county), geography(children.data)$tract, sep="")
} else if (fileGeo == "County") {
	myFIPS = paste(geography(children.data)$state, sprintf("%03s",geography(children.data)$county), sep="")
} else if (fileGeo == "Place") {
	myFIPS = paste(geography(children.data)$state, sprintf("%05s",geography(children.data)$place), sep="")
} else if (fileGeo == "BlockGroup") {
	myFIPS = paste(geography(children.data)$state, sprintf("%03d",geography(children.data)$county), sprintf("%06d",geography(children.data)$tract), geography(children.data)$blockgroup, sep="")
} else if (fileGeo == "MSA") {
	myFIPS = geography(children.data)$metropolitanstatisticalareamicropolitanstatisticalarea
}

if (fileGeo != "MSA" && fileGeo != "Place") {
	countyFIPS = paste(geography(children.data)$state, sprintf("%03s",geography(children.data)$county), sep="")
	stateFIPS = geography(children.data)$state
} else if(fileGeo != "MSA") {
	stateFIPS = geography(children.data)$state
}

children.df = data.frame(geography(children.data)$NAME, myFIPS, countyFIPS, countyName, stateFIPS, stateAbbr, year_endyear, year_span, estimate(children.data))

# Overwrite default ACS field names with English
cols_children = c("GeoStr", "FIPS", "CountyFIPS", "CountyName", "StateFIPS", "StateAbbr", "Period", "Dataset", "PopulationUnder18", "Under18InHouseholds", "AgeUnder3Years", "Age3to4", "Age5", "Age6to8", "Age9to11", "Age12to14", "Age15to17", "Under18InGroupQuarters", "OwnChildrenUnder18", "InMarriedCouples","InMarriedCouples_Under3years","InMarriedCouples_3to4years","InMarriedCouples_5years","InMarriedCouples_6to11years","InMarriedCouples_12to17years","InOtherFamilies","MaleHoH","MaleHoH_Under3years","MaleHoH_3to4years","MaleHoH_5years","MaleHoH_6to11years","MaleHoH_12to17years","FemaleHoH","FemaleHoH_Under3years","FemaleHoH_3to4years","FemaleHoH_5years","FemaleHoH_6to11years","FemaleHoH_12to17years")
colnames(children.df)=cols_children

# Set rownames to NULL, so it defaults to a sequential numeric output
rownames(children.df) <- NULL

#Clean up unneeded variables
rm(ownChildren.byFamilytype, ownchildren.byfamilytype.vars, population.under18, population.under18.vars, children.vars, children.data, children.df)