library(readxl) library(readr) sponsordata_114_house <- read_csv("~/Documents/Active Projects/Primaries and Polarization/data/Bill Sponsorship/govtrack_cosponsor_data_house/sponsordata_114_house.csv") sponsordata_113_house <- read_csv("~/Documents/Active Projects/Primaries and Polarization/data/Bill Sponsorship/govtrack_cosponsor_data_house/sponsordata_113_house.csv") sponsordata_112_house <- read_csv("~/Documents/Active Projects/Primaries and Polarization/data/Bill Sponsorship/govtrack_cosponsor_data_house/sponsordata_112_house.csv") sponsordata_111_house <- read_csv("~/Documents/Active Projects/Primaries and Polarization/data/Bill Sponsorship/govtrack_cosponsor_data_house/sponsordata_111_house.csv") sponsordata_110_house <- read_csv("~/Documents/Active Projects/Primaries and Polarization/data/Bill Sponsorship/govtrack_cosponsor_data_house/sponsordata_110_house.csv") sponsordata_109_house <- read_csv("~/Documents/Active Projects/Primaries and Polarization/data/Bill Sponsorship/govtrack_cosponsor_data_house/sponsordata_109_house.csv") sponsordata_108_house <- read_csv("~/Documents/Active Projects/Primaries and Polarization/data/Bill Sponsorship/govtrack_cosponsor_data_house/sponsordata_108_house.csv") sponsordata_107_house <- read_csv("~/Documents/Active Projects/Primaries and Polarization/data/Bill Sponsorship/govtrack_cosponsor_data_house/sponsordata_107_house.csv") sponsordata_106_house <- read_csv("~/Documents/Active Projects/Primaries and Polarization/data/Bill Sponsorship/govtrack_cosponsor_data_house/sponsordata_106_house.csv") sponsordata_105_house <- read_csv("~/Documents/Active Projects/Primaries and Polarization/data/Bill Sponsorship/govtrack_cosponsor_data_house/sponsordata_105_house.csv") sponsordata_104_house <- read_csv("~/Documents/Active Projects/Primaries and Polarization/data/Bill Sponsorship/govtrack_cosponsor_data_house/sponsordata_104_house.csv") sponsordata_103_house <- read_csv("~/Documents/Active Projects/Primaries and Polarization/data/Bill Sponsorship/govtrack_cosponsor_data_house/sponsordata_103_house.csv") sponsordata_102_house <- read_csv("~/Documents/Active Projects/Primaries and Polarization/data/Bill Sponsorship/govtrack_cosponsor_data_house/sponsordata_102_house.csv") sponsordata_101_house <- read_csv("~/Documents/Active Projects/Primaries and Polarization/data/Bill Sponsorship/govtrack_cosponsor_data_house/sponsordata_101_house.csv") sponsordata_100_house <- read_csv("~/Documents/Active Projects/Primaries and Polarization/data/Bill Sponsorship/govtrack_cosponsor_data_house/sponsordata_100_house.csv") sponsordata_99_house <- read_csv("~/Documents/Active Projects/Primaries and Polarization/data/Bill Sponsorship/govtrack_cosponsor_data_house/sponsordata_99_house.csv") sponsordata_98_house <- read_csv("~/Documents/Active Projects/Primaries and Polarization/data/Bill Sponsorship/govtrack_cosponsor_data_house/sponsordata_98_house.csv") sponsordata_97_house <- read_csv("~/Documents/Active Projects/Primaries and Polarization/data/Bill Sponsorship/govtrack_cosponsor_data_house/sponsordata_97_house.csv") sponsordata_96_house <- read_csv("~/Documents/Active Projects/Primaries and Polarization/data/Bill Sponsorship/govtrack_cosponsor_data_house/sponsordata_96_house.csv") sponsordata_95_house <- read_csv("~/Documents/Active Projects/Primaries and Polarization/data/Bill Sponsorship/govtrack_cosponsor_data_house/sponsordata_95_house.csv") sponsordata_94_house <- read_csv("~/Documents/Active Projects/Primaries and Polarization/data/Bill Sponsorship/govtrack_cosponsor_data_house/sponsordata_94_house.csv") sponsordata_93_house <- read_csv("~/Documents/Active Projects/Primaries and Polarization/data/Bill Sponsorship/govtrack_cosponsor_data_house/sponsordata_93_house.csv") billsponsordata <- read_csv("~/Documents/Active Projects/Primaries and Polarization/data/Bill Sponsorship/billsponsordata.csv") icpsrcodes_legislators <- read_csv("~/Documents/Active Projects/Primaries and Polarization/data/Bill Sponsorship/housemem_Thomas_icpsr.csv") sponsordata_114_house$icpsr <- icpsrcodes_legislators$icpsr_id[match(sponsordata_114_house$bioguide_id, icpsrcodes_legislators$bioguide_id)] sponsordata_113_house$icpsr <- icpsrcodes_legislators$icpsr_id[match(sponsordata_113_house$thomas_id, icpsrcodes_legislators$thomas_id)] sponsordata_112_house$icpsr <- icpsrcodes_legislators$icpsr_id[match(sponsordata_112_house$thomas_id, icpsrcodes_legislators$thomas_id)] sponsordata_111_house$icpsr <- icpsrcodes_legislators$icpsr_id[match(sponsordata_111_house$thomas_id, icpsrcodes_legislators$thomas_id)] sponsordata_110_house$icpsr <- icpsrcodes_legislators$icpsr_id[match(sponsordata_110_house$thomas_id, icpsrcodes_legislators$thomas_id)] sponsordata_109_house$icpsr <- icpsrcodes_legislators$icpsr_id[match(sponsordata_109_house$thomas_id, icpsrcodes_legislators$thomas_id)] sponsordata_108_house$icpsr <- icpsrcodes_legislators$icpsr_id[match(sponsordata_108_house$thomas_id, icpsrcodes_legislators$thomas_id)] sponsordata_107_house$icpsr <- icpsrcodes_legislators$icpsr_id[match(sponsordata_107_house$thomas_id, icpsrcodes_legislators$thomas_id)] sponsordata_106_house$icpsr <- icpsrcodes_legislators$icpsr_id[match(sponsordata_106_house$thomas_id, icpsrcodes_legislators$thomas_id)] sponsordata_105_house$icpsr <- icpsrcodes_legislators$icpsr_id[match(sponsordata_105_house$thomas_id, icpsrcodes_legislators$thomas_id)] sponsordata_104_house$icpsr <- icpsrcodes_legislators$icpsr_id[match(sponsordata_104_house$thomas_id, icpsrcodes_legislators$thomas_id)] sponsordata_103_house$icpsr <- icpsrcodes_legislators$icpsr_id[match(sponsordata_103_house$thomas_id, icpsrcodes_legislators$thomas_id)] sponsordata_102_house$icpsr <- icpsrcodes_legislators$icpsr_id[match(sponsordata_102_house$thomas_id, icpsrcodes_legislators$thomas_id)] sponsordata_101_house$icpsr <- icpsrcodes_legislators$icpsr_id[match(sponsordata_101_house$thomas_id, icpsrcodes_legislators$thomas_id)] sponsordata_100_house$icpsr <- icpsrcodes_legislators$icpsr_id[match(sponsordata_100_house$thomas_id, icpsrcodes_legislators$thomas_id)] sponsordata_99_house$icpsr <- icpsrcodes_legislators$icpsr_id[match(sponsordata_99_house$thomas_id, icpsrcodes_legislators$thomas_id)] sponsordata_98_house$icpsr <- icpsrcodes_legislators$icpsr_id[match(sponsordata_98_house$thomas_id, icpsrcodes_legislators$thomas_id)] sponsordata_97_house$icpsr <- icpsrcodes_legislators$icpsr_id[match(sponsordata_97_house$thomas_id, icpsrcodes_legislators$thomas_id)] sponsordata_96_house$icpsr <- icpsrcodes_legislators$icpsr_id[match(sponsordata_96_house$thomas_id, icpsrcodes_legislators$thomas_id)] sponsordata_95_house$icpsr <- icpsrcodes_legislators$icpsr_id[match(sponsordata_95_house$thomas_id, icpsrcodes_legislators$thomas_id)] sponsordata_94_house$icpsr <- icpsrcodes_legislators$icpsr_id[match(sponsordata_94_house$thomas_id, icpsrcodes_legislators$thomas_id)] sponsordata_93_house$icpsr <- icpsrcodes_legislators$icpsr_id[match(sponsordata_93_house$thomas_id, icpsrcodes_legislators$thomas_id)] sponsordata_114_house$party <- billsponsordata$party_code[match(sponsordata_114_house$icpsr, billsponsordata$icpsr)] sponsordata_113_house$party <- billsponsordata$party_code[match(sponsordata_113_house$icpsr, billsponsordata$icpsr)] sponsordata_112_house$party <- billsponsordata$party_code[match(sponsordata_112_house$icpsr, billsponsordata$icpsr)] sponsordata_111_house$party <- billsponsordata$party_code[match(sponsordata_111_house$icpsr, billsponsordata$icpsr)] sponsordata_110_house$party <- billsponsordata$party_code[match(sponsordata_110_house$icpsr, billsponsordata$icpsr)] sponsordata_109_house$party <- billsponsordata$party_code[match(sponsordata_109_house$icpsr, billsponsordata$icpsr)] sponsordata_108_house$party <- billsponsordata$party_code[match(sponsordata_108_house$icpsr, billsponsordata$icpsr)] sponsordata_107_house$party <- billsponsordata$party_code[match(sponsordata_107_house$icpsr, billsponsordata$icpsr)] sponsordata_106_house$party <- billsponsordata$party_code[match(sponsordata_106_house$icpsr, billsponsordata$icpsr)] sponsordata_105_house$party <- billsponsordata$party_code[match(sponsordata_105_house$icpsr, billsponsordata$icpsr)] sponsordata_104_house$party <- billsponsordata$party_code[match(sponsordata_104_house$icpsr, billsponsordata$icpsr)] sponsordata_103_house$party <- billsponsordata$party_code[match(sponsordata_103_house$icpsr, billsponsordata$icpsr)] sponsordata_102_house$party <- billsponsordata$party_code[match(sponsordata_102_house$icpsr, billsponsordata$icpsr)] sponsordata_101_house$party <- billsponsordata$party_code[match(sponsordata_101_house$icpsr, billsponsordata$icpsr)] sponsordata_100_house$party <- billsponsordata$party_code[match(sponsordata_100_house$icpsr, billsponsordata$icpsr)] sponsordata_99_house$party <- billsponsordata$party_code[match(sponsordata_99_house$icpsr, billsponsordata$icpsr)] sponsordata_98_house$party <- billsponsordata$party_code[match(sponsordata_98_house$icpsr, billsponsordata$icpsr)] sponsordata_97_house$party <- billsponsordata$party_code[match(sponsordata_97_house$icpsr, billsponsordata$icpsr)] sponsordata_96_house$party <- billsponsordata$party_code[match(sponsordata_96_house$icpsr, billsponsordata$icpsr)] sponsordata_95_house$party <- billsponsordata$party_code[match(sponsordata_95_house$icpsr, billsponsordata$icpsr)] sponsordata_94_house$party <- billsponsordata$party_code[match(sponsordata_94_house$icpsr, billsponsordata$icpsr)] sponsordata_93_house$party <- billsponsordata$party_code[match(sponsordata_93_house$icpsr, billsponsordata$icpsr)] sponsordata_114_house$dem <- sponsordata_114_house$party sponsordata_114_house$dem[sponsordata_114_house$dem==100] <- 1 sponsordata_114_house$dem[sponsordata_114_house$dem==200] <- 0 sponsordata_114_house$rep <- sponsordata_114_house$party sponsordata_114_house$rep[sponsordata_114_house$rep==100] <- 0 sponsordata_114_house$rep[sponsordata_114_house$rep==200] <- 1 bills114.data <- aggregate(dem ~ bill_number + Congress, data=sponsordata_114_house, FUN=sum) r114.data <- aggregate(rep ~ bill_number + Congress, data=sponsordata_114_house, FUN=sum) bills114.data$rep <- r114.data$rep[match(bills114.data$bill_number, r114.data$bill_number)] bills114.data$total <- bills114.data$dem + bills114.data$rep bills114.data <- subset.data.frame(bills114.data, total>1) bills114.data$demshare <- bills114.data$dem/(bills114.data$dem + bills114.data$rep) bills114.data$repshare <- bills114.data$rep/(bills114.data$dem + bills114.data$rep) sponsordata_114_house$demshare <- bills114.data$demshare[match(sponsordata_114_house$bill_number, bills114.data$bill_number)] sponsordata_114_house$repshare <- bills114.data$repshare[match(sponsordata_114_house$bill_number, bills114.data$bill_number)] dem_cosponsorshare_114 <- aggregate(demshare ~ icpsr + name + Congress + party , data=sponsordata_114_house, FUN=mean) sponsordata_113_house$dem <- sponsordata_113_house$party sponsordata_113_house$dem[sponsordata_113_house$dem==100] <- 1 sponsordata_113_house$dem[sponsordata_113_house$dem==200] <- 0 sponsordata_113_house$rep <- sponsordata_113_house$party sponsordata_113_house$rep[sponsordata_113_house$rep==100] <- 0 sponsordata_113_house$rep[sponsordata_113_house$rep==200] <- 1 bills113.data <- aggregate(dem ~ bill_number + Congress, data=sponsordata_113_house, FUN=sum) r113.data <- aggregate(rep ~ bill_number + Congress, data=sponsordata_113_house, FUN=sum) bills113.data$rep <- r113.data$rep[match(bills113.data$bill_number, r113.data$bill_number)] bills113.data$total <- bills113.data$dem + bills113.data$rep bills113.data <- subset.data.frame(bills113.data, total>1) bills113.data$demshare <- bills113.data$dem/(bills113.data$dem + bills113.data$rep) bills113.data$repshare <- bills113.data$rep/(bills113.data$dem + bills113.data$rep) sponsordata_113_house$demshare <- bills113.data$demshare[match(sponsordata_113_house$bill_number, bills113.data$bill_number)] sponsordata_113_house$repshare <- bills113.data$repshare[match(sponsordata_113_house$bill_number, bills113.data$bill_number)] dem_cosponsorshare_113 <- aggregate(demshare ~ icpsr + name + Congress + party , data=sponsordata_113_house, FUN=mean) sponsordata_112_house$dem <- sponsordata_112_house$party sponsordata_112_house$dem[sponsordata_112_house$dem==100] <- 1 sponsordata_112_house$dem[sponsordata_112_house$dem==200] <- 0 sponsordata_112_house$rep <- sponsordata_112_house$party sponsordata_112_house$rep[sponsordata_112_house$rep==100] <- 0 sponsordata_112_house$rep[sponsordata_112_house$rep==200] <- 1 bills112.data <- aggregate(dem ~ bill_number + Congress, data=sponsordata_112_house, FUN=sum) r112.data <- aggregate(rep ~ bill_number + Congress, data=sponsordata_112_house, FUN=sum) bills112.data$rep <- r112.data$rep[match(bills112.data$bill_number, r112.data$bill_number)] bills112.data$total <- bills112.data$dem + bills112.data$rep bills112.data <- subset.data.frame(bills112.data, total>1) bills112.data$demshare <- bills112.data$dem/(bills112.data$dem + bills112.data$rep) bills112.data$repshare <- bills112.data$rep/(bills112.data$dem + bills112.data$rep) sponsordata_112_house$demshare <- bills112.data$demshare[match(sponsordata_112_house$bill_number, bills112.data$bill_number)] sponsordata_112_house$repshare <- bills112.data$repshare[match(sponsordata_112_house$bill_number, bills112.data$bill_number)] dem_cosponsorshare_112 <- aggregate(demshare ~ icpsr + name + Congress + party , data=sponsordata_112_house, FUN=mean) sponsordata_111_house$dem <- sponsordata_111_house$party sponsordata_111_house$dem[sponsordata_111_house$dem==100] <- 1 sponsordata_111_house$dem[sponsordata_111_house$dem==200] <- 0 sponsordata_111_house$rep <- sponsordata_111_house$party sponsordata_111_house$rep[sponsordata_111_house$rep==100] <- 0 sponsordata_111_house$rep[sponsordata_111_house$rep==200] <- 1 bills111.data <- aggregate(dem ~ bill_number + Congress, data=sponsordata_111_house, FUN=sum) r111.data <- aggregate(rep ~ bill_number + Congress, data=sponsordata_111_house, FUN=sum) bills111.data$rep <- r111.data$rep[match(bills111.data$bill_number, r111.data$bill_number)] bills111.data$total <- bills111.data$dem + bills111.data$rep bills111.data <- subset.data.frame(bills111.data, total>1) bills111.data$demshare <- bills111.data$dem/(bills111.data$dem + bills111.data$rep) bills111.data$repshare <- bills111.data$rep/(bills111.data$dem + bills111.data$rep) sponsordata_111_house$demshare <- bills111.data$demshare[match(sponsordata_111_house$bill_number, bills111.data$bill_number)] sponsordata_111_house$repshare <- bills111.data$repshare[match(sponsordata_111_house$bill_number, bills111.data$bill_number)] dem_cosponsorshare_111 <- aggregate(demshare ~ icpsr + name + Congress + party , data=sponsordata_111_house, FUN=mean) sponsordata_110_house$dem <- sponsordata_110_house$party sponsordata_110_house$dem[sponsordata_110_house$dem==100] <- 1 sponsordata_110_house$dem[sponsordata_110_house$dem==200] <- 0 sponsordata_110_house$rep <- sponsordata_110_house$party sponsordata_110_house$rep[sponsordata_110_house$rep==100] <- 0 sponsordata_110_house$rep[sponsordata_110_house$rep==200] <- 1 bills110.data <- aggregate(dem ~ bill_number + Congress, data=sponsordata_110_house, FUN=sum) r110.data <- aggregate(rep ~ bill_number + Congress, data=sponsordata_110_house, FUN=sum) bills110.data$rep <- r110.data$rep[match(bills110.data$bill_number, r110.data$bill_number)] bills110.data$total <- bills110.data$dem + bills110.data$rep bills110.data <- subset.data.frame(bills110.data, total>1) bills110.data$demshare <- bills110.data$dem/(bills110.data$dem + bills110.data$rep) bills110.data$repshare <- bills110.data$rep/(bills110.data$dem + bills110.data$rep) sponsordata_110_house$demshare <- bills110.data$demshare[match(sponsordata_110_house$bill_number, bills110.data$bill_number)] sponsordata_110_house$repshare <- bills110.data$repshare[match(sponsordata_110_house$bill_number, bills110.data$bill_number)] dem_cosponsorshare_110 <- aggregate(demshare ~ icpsr + name + Congress + party , data=sponsordata_110_house, FUN=mean) sponsordata_109_house$dem <- sponsordata_109_house$party sponsordata_109_house$dem[sponsordata_109_house$dem==100] <- 1 sponsordata_109_house$dem[sponsordata_109_house$dem==200] <- 0 sponsordata_109_house$rep <- sponsordata_109_house$party sponsordata_109_house$rep[sponsordata_109_house$rep==100] <- 0 sponsordata_109_house$rep[sponsordata_109_house$rep==200] <- 1 bills109.data <- aggregate(dem ~ bill_number + Congress, data=sponsordata_109_house, FUN=sum) r109.data <- aggregate(rep ~ bill_number + Congress, data=sponsordata_109_house, FUN=sum) bills109.data$rep <- r109.data$rep[match(bills109.data$bill_number, r109.data$bill_number)] bills109.data$total <- bills109.data$dem + bills109.data$rep bills109.data <- subset.data.frame(bills109.data, total>1) bills109.data$demshare <- bills109.data$dem/(bills109.data$dem + bills109.data$rep) bills109.data$repshare <- bills109.data$rep/(bills109.data$dem + bills109.data$rep) sponsordata_109_house$demshare <- bills109.data$demshare[match(sponsordata_109_house$bill_number, bills109.data$bill_number)] sponsordata_109_house$repshare <- bills109.data$repshare[match(sponsordata_109_house$bill_number, bills109.data$bill_number)] dem_cosponsorshare_109 <- aggregate(demshare ~ icpsr + name + Congress + party , data=sponsordata_109_house, FUN=mean) sponsordata_108_house$dem <- sponsordata_108_house$party sponsordata_108_house$dem[sponsordata_108_house$dem==100] <- 1 sponsordata_108_house$dem[sponsordata_108_house$dem==200] <- 0 sponsordata_108_house$rep <- sponsordata_108_house$party sponsordata_108_house$rep[sponsordata_108_house$rep==100] <- 0 sponsordata_108_house$rep[sponsordata_108_house$rep==200] <- 1 bills108.data <- aggregate(dem ~ bill_number + Congress, data=sponsordata_108_house, FUN=sum) r108.data <- aggregate(rep ~ bill_number + Congress, data=sponsordata_108_house, FUN=sum) bills108.data$rep <- r108.data$rep[match(bills108.data$bill_number, r108.data$bill_number)] bills108.data$total <- bills108.data$dem + bills108.data$rep bills108.data <- subset.data.frame(bills108.data, total>1) bills108.data$demshare <- bills108.data$dem/(bills108.data$dem + bills108.data$rep) bills108.data$repshare <- bills108.data$rep/(bills108.data$dem + bills108.data$rep) sponsordata_108_house$demshare <- bills108.data$demshare[match(sponsordata_108_house$bill_number, bills108.data$bill_number)] sponsordata_108_house$repshare <- bills108.data$repshare[match(sponsordata_108_house$bill_number, bills108.data$bill_number)] dem_cosponsorshare_108 <- aggregate(demshare ~ icpsr + name + Congress + party , data=sponsordata_108_house, FUN=mean) sponsordata_107_house$dem <- sponsordata_107_house$party sponsordata_107_house$dem[sponsordata_107_house$dem==100] <- 1 sponsordata_107_house$dem[sponsordata_107_house$dem==200] <- 0 sponsordata_107_house$rep <- sponsordata_107_house$party sponsordata_107_house$rep[sponsordata_107_house$rep==100] <- 0 sponsordata_107_house$rep[sponsordata_107_house$rep==200] <- 1 bills107.data <- aggregate(dem ~ bill_number + Congress, data=sponsordata_107_house, FUN=sum) r107.data <- aggregate(rep ~ bill_number + Congress, data=sponsordata_107_house, FUN=sum) bills107.data$rep <- r107.data$rep[match(bills107.data$bill_number, r107.data$bill_number)] bills107.data$total <- bills107.data$dem + bills107.data$rep bills107.data <- subset.data.frame(bills107.data, total>1) bills107.data$demshare <- bills107.data$dem/(bills107.data$dem + bills107.data$rep) bills107.data$repshare <- bills107.data$rep/(bills107.data$dem + bills107.data$rep) sponsordata_107_house$demshare <- bills107.data$demshare[match(sponsordata_107_house$bill_number, bills107.data$bill_number)] sponsordata_107_house$repshare <- bills107.data$repshare[match(sponsordata_107_house$bill_number, bills107.data$bill_number)] dem_cosponsorshare_107 <- aggregate(demshare ~ icpsr + name + Congress + party , data=sponsordata_107_house, FUN=mean) sponsordata_106_house$dem <- sponsordata_106_house$party sponsordata_106_house$dem[sponsordata_106_house$dem==100] <- 1 sponsordata_106_house$dem[sponsordata_106_house$dem==200] <- 0 sponsordata_106_house$rep <- sponsordata_106_house$party sponsordata_106_house$rep[sponsordata_106_house$rep==100] <- 0 sponsordata_106_house$rep[sponsordata_106_house$rep==200] <- 1 bills106.data <- aggregate(dem ~ bill_number + Congress, data=sponsordata_106_house, FUN=sum) r106.data <- aggregate(rep ~ bill_number + Congress, data=sponsordata_106_house, FUN=sum) bills106.data$rep <- r106.data$rep[match(bills106.data$bill_number, r106.data$bill_number)] bills106.data$total <- bills106.data$dem + bills106.data$rep bills106.data <- subset.data.frame(bills106.data, total>1) bills106.data$demshare <- bills106.data$dem/(bills106.data$dem + bills106.data$rep) bills106.data$repshare <- bills106.data$rep/(bills106.data$dem + bills106.data$rep) sponsordata_106_house$demshare <- bills106.data$demshare[match(sponsordata_106_house$bill_number, bills106.data$bill_number)] sponsordata_106_house$repshare <- bills106.data$repshare[match(sponsordata_106_house$bill_number, bills106.data$bill_number)] dem_cosponsorshare_106 <- aggregate(demshare ~ icpsr + name + Congress + party , data=sponsordata_106_house, FUN=mean) sponsordata_105_house$dem <- sponsordata_105_house$party sponsordata_105_house$dem[sponsordata_105_house$dem==100] <- 1 sponsordata_105_house$dem[sponsordata_105_house$dem==200] <- 0 sponsordata_105_house$rep <- sponsordata_105_house$party sponsordata_105_house$rep[sponsordata_105_house$rep==100] <- 0 sponsordata_105_house$rep[sponsordata_105_house$rep==200] <- 1 bills105.data <- aggregate(dem ~ bill_number + Congress, data=sponsordata_105_house, FUN=sum) r105.data <- aggregate(rep ~ bill_number + Congress, data=sponsordata_105_house, FUN=sum) bills105.data$rep <- r105.data$rep[match(bills105.data$bill_number, r105.data$bill_number)] bills105.data$total <- bills105.data$dem + bills105.data$rep bills105.data <- subset.data.frame(bills105.data, total>1) bills105.data$demshare <- bills105.data$dem/(bills105.data$dem + bills105.data$rep) bills105.data$repshare <- bills105.data$rep/(bills105.data$dem + bills105.data$rep) sponsordata_105_house$demshare <- bills105.data$demshare[match(sponsordata_105_house$bill_number, bills105.data$bill_number)] sponsordata_105_house$repshare <- bills105.data$repshare[match(sponsordata_105_house$bill_number, bills105.data$bill_number)] dem_cosponsorshare_105 <- aggregate(demshare ~ icpsr + name + Congress + party , data=sponsordata_105_house, FUN=mean) sponsordata_104_house$dem <- sponsordata_104_house$party sponsordata_104_house$dem[sponsordata_104_house$dem==100] <- 1 sponsordata_104_house$dem[sponsordata_104_house$dem==200] <- 0 sponsordata_104_house$rep <- sponsordata_104_house$party sponsordata_104_house$rep[sponsordata_104_house$rep==100] <- 0 sponsordata_104_house$rep[sponsordata_104_house$rep==200] <- 1 bills104.data <- aggregate(dem ~ bill_number + Congress, data=sponsordata_104_house, FUN=sum) r104.data <- aggregate(rep ~ bill_number + Congress, data=sponsordata_104_house, FUN=sum) bills104.data$rep <- r104.data$rep[match(bills104.data$bill_number, r104.data$bill_number)] bills104.data$total <- bills104.data$dem + bills104.data$rep bills104.data <- subset.data.frame(bills104.data, total>1) bills104.data$demshare <- bills104.data$dem/(bills104.data$dem + bills104.data$rep) bills104.data$repshare <- bills104.data$rep/(bills104.data$dem + bills104.data$rep) sponsordata_104_house$demshare <- bills104.data$demshare[match(sponsordata_104_house$bill_number, bills104.data$bill_number)] sponsordata_104_house$repshare <- bills104.data$repshare[match(sponsordata_104_house$bill_number, bills104.data$bill_number)] dem_cosponsorshare_104 <- aggregate(demshare ~ icpsr + name + Congress + party , data=sponsordata_104_house, FUN=mean) sponsordata_103_house$dem <- sponsordata_103_house$party sponsordata_103_house$dem[sponsordata_103_house$dem==100] <- 1 sponsordata_103_house$dem[sponsordata_103_house$dem==200] <- 0 sponsordata_103_house$rep <- sponsordata_103_house$party sponsordata_103_house$rep[sponsordata_103_house$rep==100] <- 0 sponsordata_103_house$rep[sponsordata_103_house$rep==200] <- 1 bills103.data <- aggregate(dem ~ bill_number + Congress, data=sponsordata_103_house, FUN=sum) r103.data <- aggregate(rep ~ bill_number + Congress, data=sponsordata_103_house, FUN=sum) bills103.data$rep <- r103.data$rep[match(bills103.data$bill_number, r103.data$bill_number)] bills103.data$total <- bills103.data$dem + bills103.data$rep bills103.data <- subset.data.frame(bills103.data, total>1) bills103.data$demshare <- bills103.data$dem/(bills103.data$dem + bills103.data$rep) bills103.data$repshare <- bills103.data$rep/(bills103.data$dem + bills103.data$rep) sponsordata_103_house$demshare <- bills103.data$demshare[match(sponsordata_103_house$bill_number, bills103.data$bill_number)] sponsordata_103_house$repshare <- bills103.data$repshare[match(sponsordata_103_house$bill_number, bills103.data$bill_number)] dem_cosponsorshare_103 <- aggregate(demshare ~ icpsr + name + Congress + party , data=sponsordata_103_house, FUN=mean) sponsordata_102_house$dem <- sponsordata_102_house$party sponsordata_102_house$dem[sponsordata_102_house$dem==100] <- 1 sponsordata_102_house$dem[sponsordata_102_house$dem==200] <- 0 sponsordata_102_house$rep <- sponsordata_102_house$party sponsordata_102_house$rep[sponsordata_102_house$rep==100] <- 0 sponsordata_102_house$rep[sponsordata_102_house$rep==200] <- 1 bills102.data <- aggregate(dem ~ bill_number + Congress, data=sponsordata_102_house, FUN=sum) r102.data <- aggregate(rep ~ bill_number + Congress, data=sponsordata_102_house, FUN=sum) bills102.data$rep <- r102.data$rep[match(bills102.data$bill_number, r102.data$bill_number)] bills102.data$total <- bills102.data$dem + bills102.data$rep bills102.data <- subset.data.frame(bills102.data, total>1) bills102.data$demshare <- bills102.data$dem/(bills102.data$dem + bills102.data$rep) bills102.data$repshare <- bills102.data$rep/(bills102.data$dem + bills102.data$rep) sponsordata_102_house$demshare <- bills102.data$demshare[match(sponsordata_102_house$bill_number, bills102.data$bill_number)] sponsordata_102_house$repshare <- bills102.data$repshare[match(sponsordata_102_house$bill_number, bills102.data$bill_number)] dem_cosponsorshare_102 <- aggregate(demshare ~ icpsr + name + Congress + party , data=sponsordata_102_house, FUN=mean) sponsordata_101_house$dem <- sponsordata_101_house$party sponsordata_101_house$dem[sponsordata_101_house$dem==100] <- 1 sponsordata_101_house$dem[sponsordata_101_house$dem==200] <- 0 sponsordata_101_house$rep <- sponsordata_101_house$party sponsordata_101_house$rep[sponsordata_101_house$rep==100] <- 0 sponsordata_101_house$rep[sponsordata_101_house$rep==200] <- 1 bills101.data <- aggregate(dem ~ bill_number + Congress, data=sponsordata_101_house, FUN=sum) r101.data <- aggregate(rep ~ bill_number + Congress, data=sponsordata_101_house, FUN=sum) bills101.data$rep <- r101.data$rep[match(bills101.data$bill_number, r101.data$bill_number)] bills101.data$total <- bills101.data$dem + bills101.data$rep bills101.data <- subset.data.frame(bills101.data, total>1) bills101.data$demshare <- bills101.data$dem/(bills101.data$dem + bills101.data$rep) bills101.data$repshare <- bills101.data$rep/(bills101.data$dem + bills101.data$rep) sponsordata_101_house$demshare <- bills101.data$demshare[match(sponsordata_101_house$bill_number, bills101.data$bill_number)] sponsordata_101_house$repshare <- bills101.data$repshare[match(sponsordata_101_house$bill_number, bills101.data$bill_number)] dem_cosponsorshare_101 <- aggregate(demshare ~ icpsr + name + Congress + party , data=sponsordata_101_house, FUN=mean) sponsordata_100_house$dem <- sponsordata_100_house$party sponsordata_100_house$dem[sponsordata_100_house$dem==100] <- 1 sponsordata_100_house$dem[sponsordata_100_house$dem==200] <- 0 sponsordata_100_house$rep <- sponsordata_100_house$party sponsordata_100_house$rep[sponsordata_100_house$rep==100] <- 0 sponsordata_100_house$rep[sponsordata_100_house$rep==200] <- 1 bills100.data <- aggregate(dem ~ bill_number + Congress, data=sponsordata_100_house, FUN=sum) r100.data <- aggregate(rep ~ bill_number + Congress, data=sponsordata_100_house, FUN=sum) bills100.data$rep <- r100.data$rep[match(bills100.data$bill_number, r100.data$bill_number)] bills100.data$total <- bills100.data$dem + bills100.data$rep bills100.data <- subset.data.frame(bills100.data, total>1) bills100.data$demshare <- bills100.data$dem/(bills100.data$dem + bills100.data$rep) bills100.data$repshare <- bills100.data$rep/(bills100.data$dem + bills100.data$rep) sponsordata_100_house$demshare <- bills100.data$demshare[match(sponsordata_100_house$bill_number, bills100.data$bill_number)] sponsordata_100_house$repshare <- bills100.data$repshare[match(sponsordata_100_house$bill_number, bills100.data$bill_number)] dem_cosponsorshare_100 <- aggregate(demshare ~ icpsr + name + Congress + party , data=sponsordata_100_house, FUN=mean) sponsordata_99_house$dem <- sponsordata_99_house$party sponsordata_99_house$dem[sponsordata_99_house$dem==100] <- 1 sponsordata_99_house$dem[sponsordata_99_house$dem==200] <- 0 sponsordata_99_house$rep <- sponsordata_99_house$party sponsordata_99_house$rep[sponsordata_99_house$rep==100] <- 0 sponsordata_99_house$rep[sponsordata_99_house$rep==200] <- 1 bills99.data <- aggregate(dem ~ bill_number + Congress, data=sponsordata_99_house, FUN=sum) r99.data <- aggregate(rep ~ bill_number + Congress, data=sponsordata_99_house, FUN=sum) bills99.data$rep <- r99.data$rep[match(bills99.data$bill_number, r99.data$bill_number)] bills99.data$total <- bills99.data$dem + bills99.data$rep bills99.data <- subset.data.frame(bills99.data, total>1) bills99.data$demshare <- bills99.data$dem/(bills99.data$dem + bills99.data$rep) bills99.data$repshare <- bills99.data$rep/(bills99.data$dem + bills99.data$rep) sponsordata_99_house$demshare <- bills99.data$demshare[match(sponsordata_99_house$bill_number, bills99.data$bill_number)] sponsordata_99_house$repshare <- bills99.data$repshare[match(sponsordata_99_house$bill_number, bills99.data$bill_number)] dem_cosponsorshare_99 <- aggregate(demshare ~ icpsr + name + Congress + party , data=sponsordata_99_house, FUN=mean) sponsordata_98_house$dem <- sponsordata_98_house$party sponsordata_98_house$dem[sponsordata_98_house$dem==100] <- 1 sponsordata_98_house$dem[sponsordata_98_house$dem==200] <- 0 sponsordata_98_house$rep <- sponsordata_98_house$party sponsordata_98_house$rep[sponsordata_98_house$rep==100] <- 0 sponsordata_98_house$rep[sponsordata_98_house$rep==200] <- 1 bills98.data <- aggregate(dem ~ bill_number + Congress, data=sponsordata_98_house, FUN=sum) r98.data <- aggregate(rep ~ bill_number + Congress, data=sponsordata_98_house, FUN=sum) bills98.data$rep <- r98.data$rep[match(bills98.data$bill_number, r98.data$bill_number)] bills98.data$total <- bills98.data$dem + bills98.data$rep bills98.data <- subset.data.frame(bills98.data, total>1) bills98.data$demshare <- bills98.data$dem/(bills98.data$dem + bills98.data$rep) bills98.data$repshare <- bills98.data$rep/(bills98.data$dem + bills98.data$rep) sponsordata_98_house$demshare <- bills98.data$demshare[match(sponsordata_98_house$bill_number, bills98.data$bill_number)] sponsordata_98_house$repshare <- bills98.data$repshare[match(sponsordata_98_house$bill_number, bills98.data$bill_number)] dem_cosponsorshare_98 <- aggregate(demshare ~ icpsr + name + Congress + party , data=sponsordata_98_house, FUN=mean) sponsordata_97_house$dem <- sponsordata_97_house$party sponsordata_97_house$dem[sponsordata_97_house$dem==100] <- 1 sponsordata_97_house$dem[sponsordata_97_house$dem==200] <- 0 sponsordata_97_house$rep <- sponsordata_97_house$party sponsordata_97_house$rep[sponsordata_97_house$rep==100] <- 0 sponsordata_97_house$rep[sponsordata_97_house$rep==200] <- 1 bills97.data <- aggregate(dem ~ bill_number + Congress, data=sponsordata_97_house, FUN=sum) r97.data <- aggregate(rep ~ bill_number + Congress, data=sponsordata_97_house, FUN=sum) bills97.data$rep <- r97.data$rep[match(bills97.data$bill_number, r97.data$bill_number)] bills97.data$total <- bills97.data$dem + bills97.data$rep bills97.data <- subset.data.frame(bills97.data, total>1) bills97.data$demshare <- bills97.data$dem/(bills97.data$dem + bills97.data$rep) bills97.data$repshare <- bills97.data$rep/(bills97.data$dem + bills97.data$rep) sponsordata_97_house$demshare <- bills97.data$demshare[match(sponsordata_97_house$bill_number, bills97.data$bill_number)] sponsordata_97_house$repshare <- bills97.data$repshare[match(sponsordata_97_house$bill_number, bills97.data$bill_number)] dem_cosponsorshare_97 <- aggregate(demshare ~ icpsr + name + Congress + party , data=sponsordata_97_house, FUN=mean) sponsordata_96_house$dem <- sponsordata_96_house$party sponsordata_96_house$dem[sponsordata_96_house$dem==100] <- 1 sponsordata_96_house$dem[sponsordata_96_house$dem==200] <- 0 sponsordata_96_house$rep <- sponsordata_96_house$party sponsordata_96_house$rep[sponsordata_96_house$rep==100] <- 0 sponsordata_96_house$rep[sponsordata_96_house$rep==200] <- 1 bills96.data <- aggregate(dem ~ bill_number + Congress, data=sponsordata_96_house, FUN=sum) r96.data <- aggregate(rep ~ bill_number + Congress, data=sponsordata_96_house, FUN=sum) bills96.data$rep <- r96.data$rep[match(bills96.data$bill_number, r96.data$bill_number)] bills96.data$total <- bills96.data$dem + bills96.data$rep bills96.data <- subset.data.frame(bills96.data, total>1) bills96.data$demshare <- bills96.data$dem/(bills96.data$dem + bills96.data$rep) bills96.data$repshare <- bills96.data$rep/(bills96.data$dem + bills96.data$rep) sponsordata_96_house$demshare <- bills96.data$demshare[match(sponsordata_96_house$bill_number, bills96.data$bill_number)] sponsordata_96_house$repshare <- bills96.data$repshare[match(sponsordata_96_house$bill_number, bills96.data$bill_number)] dem_cosponsorshare_96 <- aggregate(demshare ~ icpsr + name + Congress + party , data=sponsordata_96_house, FUN=mean) sponsordata_95_house$dem <- sponsordata_95_house$party sponsordata_95_house$dem[sponsordata_95_house$dem==100] <- 1 sponsordata_95_house$dem[sponsordata_95_house$dem==200] <- 0 sponsordata_95_house$rep <- sponsordata_95_house$party sponsordata_95_house$rep[sponsordata_95_house$rep==100] <- 0 sponsordata_95_house$rep[sponsordata_95_house$rep==200] <- 1 bills95.data <- aggregate(dem ~ bill_number + Congress, data=sponsordata_95_house, FUN=sum) r95.data <- aggregate(rep ~ bill_number + Congress, data=sponsordata_95_house, FUN=sum) bills95.data$rep <- r95.data$rep[match(bills95.data$bill_number, r95.data$bill_number)] bills95.data$total <- bills95.data$dem + bills95.data$rep bills95.data <- subset.data.frame(bills95.data, total>1) bills95.data$demshare <- bills95.data$dem/(bills95.data$dem + bills95.data$rep) bills95.data$repshare <- bills95.data$rep/(bills95.data$dem + bills95.data$rep) sponsordata_95_house$demshare <- bills95.data$demshare[match(sponsordata_95_house$bill_number, bills95.data$bill_number)] sponsordata_95_house$repshare <- bills95.data$repshare[match(sponsordata_95_house$bill_number, bills95.data$bill_number)] dem_cosponsorshare_95 <- aggregate(demshare ~ icpsr + name + Congress + party , data=sponsordata_95_house, FUN=mean) sponsordata_94_house$dem <- sponsordata_94_house$party sponsordata_94_house$dem[sponsordata_94_house$dem==100] <- 1 sponsordata_94_house$dem[sponsordata_94_house$dem==200] <- 0 sponsordata_94_house$rep <- sponsordata_94_house$party sponsordata_94_house$rep[sponsordata_94_house$rep==100] <- 0 sponsordata_94_house$rep[sponsordata_94_house$rep==200] <- 1 bills94.data <- aggregate(dem ~ bill_number + Congress, data=sponsordata_94_house, FUN=sum) r94.data <- aggregate(rep ~ bill_number + Congress, data=sponsordata_94_house, FUN=sum) bills94.data$rep <- r94.data$rep[match(bills94.data$bill_number, r94.data$bill_number)] bills94.data$total <- bills94.data$dem + bills94.data$rep bills94.data <- subset.data.frame(bills94.data, total>1) bills94.data$demshare <- bills94.data$dem/(bills94.data$dem + bills94.data$rep) bills94.data$repshare <- bills94.data$rep/(bills94.data$dem + bills94.data$rep) sponsordata_94_house$demshare <- bills94.data$demshare[match(sponsordata_94_house$bill_number, bills94.data$bill_number)] sponsordata_94_house$repshare <- bills94.data$repshare[match(sponsordata_94_house$bill_number, bills94.data$bill_number)] dem_cosponsorshare_94 <- aggregate(demshare ~ icpsr + name + Congress + party , data=sponsordata_94_house, FUN=mean) sponsordata_93_house$dem <- sponsordata_93_house$party sponsordata_93_house$dem[sponsordata_93_house$dem==100] <- 1 sponsordata_93_house$dem[sponsordata_93_house$dem==200] <- 0 sponsordata_93_house$rep <- sponsordata_93_house$party sponsordata_93_house$rep[sponsordata_93_house$rep==100] <- 0 sponsordata_93_house$rep[sponsordata_93_house$rep==200] <- 1 bills93.data <- aggregate(dem ~ bill_number + Congress, data=sponsordata_93_house, FUN=sum) r93.data <- aggregate(rep ~ bill_number + Congress, data=sponsordata_93_house, FUN=sum) bills93.data$rep <- r93.data$rep[match(bills93.data$bill_number, r93.data$bill_number)] bills93.data$total <- bills93.data$dem + bills93.data$rep bills93.data <- subset.data.frame(bills93.data, total>1) bills93.data$demshare <- bills93.data$dem/(bills93.data$dem + bills93.data$rep) bills93.data$repshare <- bills93.data$rep/(bills93.data$dem + bills93.data$rep) sponsordata_93_house$demshare <- bills93.data$demshare[match(sponsordata_93_house$bill_number, bills93.data$bill_number)] sponsordata_93_house$repshare <- bills93.data$repshare[match(sponsordata_93_house$bill_number, bills93.data$bill_number)] dem_cosponsorshare_93 <- aggregate(demshare ~ icpsr + name + Congress + party , data=sponsordata_93_house, FUN=mean) dem_cosponsorshare.full <- rbind(dem_cosponsorshare_114 , dem_cosponsorshare_113 ) dem_cosponsorshare.full <- rbind( dem_cosponsorshare.full, dem_cosponsorshare_112) dem_cosponsorshare.full <- rbind( dem_cosponsorshare.full, dem_cosponsorshare_111) dem_cosponsorshare.full <- rbind( dem_cosponsorshare.full, dem_cosponsorshare_110) dem_cosponsorshare.full <- rbind( dem_cosponsorshare.full, dem_cosponsorshare_109) dem_cosponsorshare.full <- rbind( dem_cosponsorshare.full, dem_cosponsorshare_108) dem_cosponsorshare.full <- rbind( dem_cosponsorshare.full, dem_cosponsorshare_107) dem_cosponsorshare.full <- rbind( dem_cosponsorshare.full, dem_cosponsorshare_106) dem_cosponsorshare.full <- rbind( dem_cosponsorshare.full, dem_cosponsorshare_105) dem_cosponsorshare.full <- rbind( dem_cosponsorshare.full, dem_cosponsorshare_104) dem_cosponsorshare.full <- rbind( dem_cosponsorshare.full, dem_cosponsorshare_103) dem_cosponsorshare.full <- rbind( dem_cosponsorshare.full, dem_cosponsorshare_102) dem_cosponsorshare.full <- rbind( dem_cosponsorshare.full, dem_cosponsorshare_101) dem_cosponsorshare.full <- rbind( dem_cosponsorshare.full, dem_cosponsorshare_100) dem_cosponsorshare.full <- rbind( dem_cosponsorshare.full, dem_cosponsorshare_99) dem_cosponsorshare.full <- rbind( dem_cosponsorshare.full, dem_cosponsorshare_98) dem_cosponsorshare.full <- rbind( dem_cosponsorshare.full, dem_cosponsorshare_97) dem_cosponsorshare.full <- rbind( dem_cosponsorshare.full, dem_cosponsorshare_96) dem_cosponsorshare.full <- rbind( dem_cosponsorshare.full, dem_cosponsorshare_95) dem_cosponsorshare.full <- rbind( dem_cosponsorshare.full, dem_cosponsorshare_94) cosponsor.hou <- rbind( dem_cosponsorshare.full, dem_cosponsorshare_93) View(dem_cosponsorshare.full) cosponsor.hou["congress"] <- cosponsor.hou$Congress cosponsor.hou <- pdata.frame(dem_cosponsorshare.full, index = c("icpsr", "cong"), drop.index = FALSE, row.names = TRUE, stringsAsFactors = default.stringsAsFactors()) table(index(cosponsor.hou), useNA = "ifany") save(cosponsor.hou, file = "~/Documents/Active Projects/Primaries and Polarization/data/Bill Sponsorship/sponsor_house.Rdata") cosponsor.hou$party[cosponsor.hou$party==100] <- 1 cosponsor.hou$party[cosponsor.hou$party==200] <- 2 library(foreign) write.dta(cosponsor.hou, "~/Documents/Active Projects/Primaries and Polarization/data/Bill Sponsorship/sponsor_house.dta") options(max.print = 99999) library(haven) hewlett_final_justlegislators <- read_dta("~/Documents/Active Projects/Primaries and Polarization/hewlett_final_justlegislators.dta") Therms_MOSpaper <- read_dta("~/Documents/Active Projects/Primaries and Polarization/data/Therms_MOSpaper.dta")