reference_pipeline/data_cleaning/FindIUsCode.R
In OxfordRSE/NTDMC_trachoma_pipeline: What the Package Does (One Line, Title Case)
# Load required packages
#https://www.geoconnect.org
if (!require("pacman")) install.packages("pacman")
pkgs = c("sf", "dplyr", "tmap", "emojifont", "readr")
pacman::p_load(pkgs, character.only = T)
DataScenarios = read.csv("DataScenarios.csv")
Predictions = read.csv("trachoma_predictive_locations_updated.csv")
ShapeFile = read.csv("AFRO_shapefile.csv")
Predictions = data.frame(ShapeFile[, 1:7], Predictions)
Predictions = subset(Predictions, Predictions$Country!="Egypt")
Predictions = subset(Predictions, Predictions$Country!="Yemen")
Predictions = subset(Predictions, Predictions$Country!="Morocco")
Predictions = subset(Predictions, Predictions$geoconnect!=0)
africa_ius = st_read("geodata/africa_ius.shp")
unique(africa_ius$ADMIN0[which(!is.na(africa_ius$ADMIN3))])
Predictions$Country = factor(Predictions$Country, levels = unique(c(levels(africa_ius$ADMIN0),levels(Predictions$Country))))
africa_ius$ADMIN0 = factor(africa_ius$ADMIN0, levels = unique(c(levels(africa_ius$ADMIN0),levels(Predictions$Country))))
Uniq = unique(Predictions$Country)
Uniq[which(!(Uniq %in% africa_ius$ADMIN0))]
sort(unique(africa_ius$ADMIN0))
Predictions$Country[which(Predictions$Country == "Democratic Republic of the Congo")] = "Congo, DRC"
Predictions$Country[which(Predictions$Country == "Tanzania")] = "Tanzania (Mainland)"
Predictions$Country[which(Predictions$Country == "Zanzibar")] = "Tanzania (Zanzibar)"
#Uniq = unique(Predictions$Country)
#Uniq[which(!(Uniq %in% africa_ius$ADMIN0))]
africa_ius$IUs_NAME = factor(africa_ius$IUs_NAME, levels = unique(c(levels(africa_ius$IUs_NAME),levels(Predictions$ADMIN2), levels(Predictions$ADMIN3))))
Predictions$ADMIN2 = factor(Predictions$ADMIN2, levels = unique(c(levels(africa_ius$IUs_NAME),levels(Predictions$ADMIN2), levels(Predictions$ADMIN3))))
Predictions$ADMIN3 = factor(Predictions$ADMIN3, levels = unique(c(levels(africa_ius$IUs_NAME),levels(Predictions$ADMIN2), levels(Predictions$ADMIN3))))
africa_ius$ADMIN1 = factor(africa_ius$ADMIN1, levels = unique(c(levels(africa_ius$ADMIN1),levels(Predictions$ADMIN1))))
Predictions$ADMIN1 = factor(Predictions$ADMIN1, levels = unique(c(levels(africa_ius$ADMIN1),levels(Predictions$ADMIN1))))
africa_ius$ADMIN1[which(africa_ius$ADMIN1 == "Oromiya")] = "Oromia"
africa_ius$ADMIN1[which(africa_ius$ADMIN1 == "SNNP")] = "SNNPR"
Uniq = unique(Predictions$ADMIN1)
IUcodes = read.csv("IUcodeTrachomaGroups.csv")
Codes = factor(rep(NA, nrow(Predictions)), levels = unique(c(levels(africa_ius$IU_ID), levels(IUcodes$geo_id))))
for (i in 1:nrow(Predictions))
{
pos = which(IUcodes$geo_id == Predictions$geoconnect[i])
if (length(pos) == 1) {
Codes[i] = IUcodes$IUcode[pos]
} else if (length(pos) > 1) {
Codes[i] = IUcodes$IUcode[pos[1]]
}
}
length(which(!is.na(Codes)))
length(which(!is.na(IUcodes$IUcode)))
start = 1
# start = 6365
for (i in start:nrow(Predictions))
{
if (is.na(Codes[i]) & (Predictions$Country[i]!="Algeria" & Predictions$Country[i]!="Burundi")){
countrypos = which(africa_ius$ADMIN0 == Predictions$Country[i])
if (length(countrypos)>0)
{
if (Predictions$ADMIN3[i] =="" | (Predictions$Country[i] != "Ethiopia" & Predictions$Country[i] != "Congo, DRC")){
iupos = countrypos[which(gsub("-", " ", tolower(africa_ius$IUs_NAME[countrypos])) == gsub("-", " ", tolower(iconv(Predictions$ADMIN2[i],"WINDOWS-1252","UTF-8"))))]
if (length(iupos)==0)
{
statepos = countrypos[which(africa_ius$ADMIN1[countrypos] == Predictions$ADMIN1[i])]
if (length(statepos)!=0)
{
matchsum = rep(NA, length(statepos))
for (j in 1:length(statepos))
{
a = unlist(strsplit(tolower(as.character(africa_ius$IUs_NAME[statepos[j]])),""))
b = unlist(strsplit(tolower(as.character(iconv(Predictions$ADMIN2[i],"WINDOWS-1252","UTF-8"))),""))
matchsum[j] = sum(!is.na(pmatch(a, b)))
}
flag = 1
maxi = max(matchsum)
uniquematch = unique(matchsum)
uniquematch = uniquematch[-which(unique(uniquematch)==maxi)]
while(flag==1){
iupos = statepos[which(matchsum == maxi)]
if (length(iupos)>1){
print(data.frame(i, Predictions$Country[i], africa_ius$IUs_NAME[iupos],africa_ius$ADMIN1[iupos], africa_ius$IU_ID[iupos], Predictions$ADMIN2[i], Predictions$ADMIN1[i]))
continue = readline(prompt="Continue: ")
} else {continue = "y"}
if (continue!="n"){
for (j in 1:length(iupos))
{
print(data.frame(i, Predictions$Country[i], africa_ius$IUs_NAME[iupos[j]], africa_ius$ADMIN1[iupos[j]], africa_ius$IU_ID[iupos[j]], Predictions$ADMIN2[i], Predictions$ADMIN1[i]))
accept = readline(prompt="Accept: ")
if (accept == "n"){
} else {Codes[i] = africa_ius$IU_ID[iupos[j]]
flag = 0
break}
}
}
if (flag == 1 & maxi >=2 & length(uniquematch)>1) {
maxi = max(uniquematch)
uniquematch = uniquematch[-which(unique(uniquematch)==maxi)]
} else if (maxi <2 | length(uniquematch)==1) {
flag = 0
}
}
}
} else {
Codes[i] = africa_ius$IU_ID[iupos]
}
} else {
iupos = countrypos[which(gsub("-", " ", tolower(africa_ius$IUs_NAME[countrypos])) == gsub("-", " ", tolower(Predictions$ADMIN3[i])))]
if (length(iupos)==0)
{
statepos = countrypos[which(africa_ius$ADMIN1[countrypos] == Predictions$ADMIN1[i])]
if (length(statepos)!=0)
{
matchsum = rep(NA, length(statepos))
for (j in 1:length(statepos))
{
a = unlist(strsplit(tolower(as.character(africa_ius$IUs_NAME[statepos[j]])),""))
b = unlist(strsplit(tolower(as.character(Predictions$ADMIN3[i])),""))
matchsum[j] = sum(!is.na(pmatch(a, b)))
}
flag = 1
maxi = max(matchsum)
uniquematch = unique(matchsum)
uniquematch = uniquematch[-which(unique(uniquematch)==maxi)]
while(flag==1){
iupos = statepos[which(matchsum == maxi)]
if (length(iupos)>1){
print(data.frame(i, Predictions$Country[i], africa_ius$IUs_NAME[iupos], africa_ius$ADMIN2[iupos], africa_ius$IU_ID[iupos], Predictions$ADMIN3[i], Predictions$ADMIN2[i]))
continue = readline(prompt="Continue: ")
} else {continue = "y"}
if (continue!="n"){
for (j in 1:length(iupos))
{
print(data.frame(i, Predictions$Country[i], africa_ius$IUs_NAME[iupos[j]], africa_ius$ADMIN2[iupos[j]], africa_ius$IU_ID[iupos[j]], Predictions$ADMIN3[i], Predictions$ADMIN2[i]))
accept = readline(prompt="Accept: ")
if (accept == "n"){
} else {Codes[i] = africa_ius$IU_ID[iupos[j]]
flag = 0
break}
}
}
if (flag == 1 & maxi >=2 & length(uniquematch)>1) {
maxi = max(uniquematch)
uniquematch = uniquematch[-which(unique(uniquematch)==maxi)]
} else if (maxi <2 | length(uniquematch)==1) {
flag = 0
}
}
}
} else {
Codes[i] = africa_ius$IU_ID[iupos]
}
}
}
}
}
Codes[163] = "ETH19082"
Codes[1559] = "SDN53248"
Codes[5861] = "COG12829"
CodesFinal = Codes
#write.csv(data.frame(Predictions, Codes), file = "PredictionsIUcodes.csv", row.names = F)
DataFinal = read.csv("PredictionsIUcodesFinal.csv")
DataScenarios = read.csv("DataScenarios.csv")
Scenarios = matrix(NA, nrow = nrow(DataFinal), ncol = 3)
for (i in 1:nrow(DataFinal))
{
pos = which(DataFinal$geoconnect[i] == DataScenarios$Geoconnect_ID)
if (length(pos) == 1){
Scenarios[i, ] = unlist(DataScenarios[pos, 55:57])
} else if (length(pos) > 1){
Scen = which.max(DataScenarios[pos, 57])
Scenarios[i, ] = unlist(DataScenarios[pos[Scen], 55:57])
}
}
length(which(is.na(Scenarios[, 1])))
DataAll = data.frame(Country = DataFinal$Country, Region = DataFinal$Region,
District = DataFinal$District, Subdistrict = DataFinal$Subdistrict,
Geoconnect_ID = DataFinal$geoconnect, Pop_point = DataFinal$pop_point,
Pop_district = DataFinal$pop_district, Logit = DataFinal$logit,
Sds = DataFinal$standard.errors, IUCodes = DataFinal$Codes, start_MDA = Scenarios[, 1],
last_MDA = Scenarios[, 2], Scenario = Scenarios[, 3])
DataAll = subset(DataAll, !is.na(IUCodes))
DataAll = subset(DataAll, !is.na(Scenario))
dim(DataAll)
length(unique(DataAll$IUCodes))
CodeUni = unique(DataAll$IUCodes)
for (i in 1:length(CodeUni))
{
pos = which(DataAll$IUCodes == CodeUni[i])
if (length(pos)>1)
{
print(pos)
print(DataAll[pos, ])
readline("Enter")
}
}
DataAll$IUCodes = factor(DataAll$IUCodes, levels = unique(c(levels(africa_ius$IU_ID),levels(DataAll$IUCodes))))
DataAll$IUCodes[422] = "ETH18932"
DataAll$IUCodes[613] = "ETH18652"
DataAll$IUCodes[36] = "ETH19098"
DataAll$IUCodes[3789] = "SEN40178"
DataAll$IUCodes[431] = "ETH18889"
DataAll$IUCodes[432] = "ETH19334"
DataAll$IUCodes[439] = "ETH18775"
DataAll$IUCodes[480] = "ETH19331"
DataAll$IUCodes[103] = "ETH18887"
DataAll$IUCodes[475] = "ETH18780"
DataAll$IUCodes[517] = "ETH18914"
DataAll$IUCodes[573] = NA
DataAll$IUCodes[481] = "ETH18808"
DataAll$IUCodes[554] = "ETH18939"
DataAll$IUCodes[571] = "ETH18856"
DataAll$IUCodes[1329] = NA
DataAll$IUCodes[610] = "ETH19323"
DataAll$IUCodes[2968] = NA
DataAll$IUCodes[c(37, 80, 149, 38, 39, 40, 643, 644, 747, 722, 723, 724, 731, 725, 733, 734, 726, 735, 736, 1296, 1297, 1298,
727, 732, 728, 737, 738, 729, 740, 730, 739, 741, 742, 751, 752, 753,
743, 744, 745, 746, 748, 749, 750, 754, 755, 756, 757, 758,
759, 760, 761, 762, 763, 1278, 1279, 1280, 1281, 1282, 1283, 1284,
1285, 1292, 1286, 1289, 1287, 1290, 1288, 1291, 1293, 1294, 1295,
1299, 1303, 1300, 1304, 1301, 1305, 1302, 1306, 1307, 1308, 1309, 1324,
1310, 1321,1311, 1322, 1312, 1319, 1313, 1323, 1314, 1325, 1315, 1320,
1316, 1326, 1317, 1318)] = NA
DataAll$IUCodes[767] = "COD13903"
DataAll$IUCodes[876] = "COD14057"
DataAll$IUCodes[1201] = NA
DataAll$IUCodes[2693] = "NGA36831"
DataAll$IUCodes[2697] = "NGA36835"
DataAll$IUCodes[2671] = "NGA36808"
DataAll$IUCodes[4380] = NA
DataAll$IUCodes[2718] = "NGA36872"
DataAll$IUCodes[2498] = "NGA36472"
DataAll$IUCodes[2716] = "NGA36870"
DataAll$IUCodes[3762] = "SEN40182"
DataAll$IUCodes[3908] = NA
DataAll$IUCodes[4410] = NA
DataAll$IUCodes[1327] = "ETH18633"
DataAll$IUCodes[531] = "ETH18885"
DataAll = subset(DataAll, !is.na(IUCodes))
dim(DataAll)
length(unique(DataAll$IUCodes))
CodeUni = unique(DataAll$IUCodes)
for (i in 1:length(CodeUni))
{
pos = which(DataAll$IUCodes == CodeUni[i])
if (length(pos)>1)
{
print(pos)
print(DataAll[pos, ])
readline("Enter")
}
}
DataAll$IUCodes[c(156,1509,3434, 3666)] = NA
DataAll$IUCodes[c(363,2926, 3646, 3810)] = NA
DataAll = subset(DataAll, !is.na(IUCodes))
dim(DataAll)
length(unique(DataAll$IUCodes))
write.csv(DataAll, file = "FinalData.csv", row.names = F)
OxfordRSE/NTDMC_trachoma_pipeline documentation built on Dec. 18, 2021, 5:42 a.m.
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# Load required packages
#https://www.geoconnect.org
if (!require("pacman")) install.packages("pacman")
pkgs = c("sf", "dplyr", "tmap", "emojifont", "readr")
pacman::p_load(pkgs, character.only = T)
DataScenarios = read.csv("DataScenarios.csv")
Predictions = read.csv("trachoma_predictive_locations_updated.csv")
ShapeFile = read.csv("AFRO_shapefile.csv")
Predictions = data.frame(ShapeFile[, 1:7], Predictions)
Predictions = subset(Predictions, Predictions$Country!="Egypt")
Predictions = subset(Predictions, Predictions$Country!="Yemen")
Predictions = subset(Predictions, Predictions$Country!="Morocco")
Predictions = subset(Predictions, Predictions$geoconnect!=0)
africa_ius = st_read("geodata/africa_ius.shp")
unique(africa_ius$ADMIN0[which(!is.na(africa_ius$ADMIN3))])
Predictions$Country = factor(Predictions$Country, levels = unique(c(levels(africa_ius$ADMIN0),levels(Predictions$Country))))
africa_ius$ADMIN0 = factor(africa_ius$ADMIN0, levels = unique(c(levels(africa_ius$ADMIN0),levels(Predictions$Country))))
Uniq = unique(Predictions$Country)
Uniq[which(!(Uniq %in% africa_ius$ADMIN0))]
sort(unique(africa_ius$ADMIN0))
Predictions$Country[which(Predictions$Country == "Democratic Republic of the Congo")] = "Congo, DRC"
Predictions$Country[which(Predictions$Country == "Tanzania")] = "Tanzania (Mainland)"
Predictions$Country[which(Predictions$Country == "Zanzibar")] = "Tanzania (Zanzibar)"
#Uniq = unique(Predictions$Country)
#Uniq[which(!(Uniq %in% africa_ius$ADMIN0))]
africa_ius$IUs_NAME = factor(africa_ius$IUs_NAME, levels = unique(c(levels(africa_ius$IUs_NAME),levels(Predictions$ADMIN2), levels(Predictions$ADMIN3))))
Predictions$ADMIN2 = factor(Predictions$ADMIN2, levels = unique(c(levels(africa_ius$IUs_NAME),levels(Predictions$ADMIN2), levels(Predictions$ADMIN3))))
Predictions$ADMIN3 = factor(Predictions$ADMIN3, levels = unique(c(levels(africa_ius$IUs_NAME),levels(Predictions$ADMIN2), levels(Predictions$ADMIN3))))
africa_ius$ADMIN1 = factor(africa_ius$ADMIN1, levels = unique(c(levels(africa_ius$ADMIN1),levels(Predictions$ADMIN1))))
Predictions$ADMIN1 = factor(Predictions$ADMIN1, levels = unique(c(levels(africa_ius$ADMIN1),levels(Predictions$ADMIN1))))
africa_ius$ADMIN1[which(africa_ius$ADMIN1 == "Oromiya")] = "Oromia"
africa_ius$ADMIN1[which(africa_ius$ADMIN1 == "SNNP")] = "SNNPR"
Uniq = unique(Predictions$ADMIN1)
IUcodes = read.csv("IUcodeTrachomaGroups.csv")
Codes = factor(rep(NA, nrow(Predictions)), levels = unique(c(levels(africa_ius$IU_ID), levels(IUcodes$geo_id))))
for (i in 1:nrow(Predictions))
{
pos = which(IUcodes$geo_id == Predictions$geoconnect[i])
if (length(pos) == 1) {
Codes[i] = IUcodes$IUcode[pos]
} else if (length(pos) > 1) {
Codes[i] = IUcodes$IUcode[pos[1]]
}
}
length(which(!is.na(Codes)))
length(which(!is.na(IUcodes$IUcode)))
start = 1
# start = 6365
for (i in start:nrow(Predictions))
{
if (is.na(Codes[i]) & (Predictions$Country[i]!="Algeria" & Predictions$Country[i]!="Burundi")){
countrypos = which(africa_ius$ADMIN0 == Predictions$Country[i])
if (length(countrypos)>0)
{
if (Predictions$ADMIN3[i] =="" | (Predictions$Country[i] != "Ethiopia" & Predictions$Country[i] != "Congo, DRC")){
iupos = countrypos[which(gsub("-", " ", tolower(africa_ius$IUs_NAME[countrypos])) == gsub("-", " ", tolower(iconv(Predictions$ADMIN2[i],"WINDOWS-1252","UTF-8"))))]
if (length(iupos)==0)
{
statepos = countrypos[which(africa_ius$ADMIN1[countrypos] == Predictions$ADMIN1[i])]
if (length(statepos)!=0)
{
matchsum = rep(NA, length(statepos))
for (j in 1:length(statepos))
{
a = unlist(strsplit(tolower(as.character(africa_ius$IUs_NAME[statepos[j]])),""))
b = unlist(strsplit(tolower(as.character(iconv(Predictions$ADMIN2[i],"WINDOWS-1252","UTF-8"))),""))
matchsum[j] = sum(!is.na(pmatch(a, b)))
}
flag = 1
maxi = max(matchsum)
uniquematch = unique(matchsum)
uniquematch = uniquematch[-which(unique(uniquematch)==maxi)]
while(flag==1){
iupos = statepos[which(matchsum == maxi)]
if (length(iupos)>1){
print(data.frame(i, Predictions$Country[i], africa_ius$IUs_NAME[iupos],africa_ius$ADMIN1[iupos], africa_ius$IU_ID[iupos], Predictions$ADMIN2[i], Predictions$ADMIN1[i]))
continue = readline(prompt="Continue: ")
} else {continue = "y"}
if (continue!="n"){
for (j in 1:length(iupos))
{
print(data.frame(i, Predictions$Country[i], africa_ius$IUs_NAME[iupos[j]], africa_ius$ADMIN1[iupos[j]], africa_ius$IU_ID[iupos[j]], Predictions$ADMIN2[i], Predictions$ADMIN1[i]))
accept = readline(prompt="Accept: ")
if (accept == "n"){
} else {Codes[i] = africa_ius$IU_ID[iupos[j]]
flag = 0
break}
}
}
if (flag == 1 & maxi >=2 & length(uniquematch)>1) {
maxi = max(uniquematch)
uniquematch = uniquematch[-which(unique(uniquematch)==maxi)]
} else if (maxi <2 | length(uniquematch)==1) {
flag = 0
}
}
}
} else {
Codes[i] = africa_ius$IU_ID[iupos]
}
} else {
iupos = countrypos[which(gsub("-", " ", tolower(africa_ius$IUs_NAME[countrypos])) == gsub("-", " ", tolower(Predictions$ADMIN3[i])))]
if (length(iupos)==0)
{
statepos = countrypos[which(africa_ius$ADMIN1[countrypos] == Predictions$ADMIN1[i])]
if (length(statepos)!=0)
{
matchsum = rep(NA, length(statepos))
for (j in 1:length(statepos))
{
a = unlist(strsplit(tolower(as.character(africa_ius$IUs_NAME[statepos[j]])),""))
b = unlist(strsplit(tolower(as.character(Predictions$ADMIN3[i])),""))
matchsum[j] = sum(!is.na(pmatch(a, b)))
}
flag = 1
maxi = max(matchsum)
uniquematch = unique(matchsum)
uniquematch = uniquematch[-which(unique(uniquematch)==maxi)]
while(flag==1){
iupos = statepos[which(matchsum == maxi)]
if (length(iupos)>1){
print(data.frame(i, Predictions$Country[i], africa_ius$IUs_NAME[iupos], africa_ius$ADMIN2[iupos], africa_ius$IU_ID[iupos], Predictions$ADMIN3[i], Predictions$ADMIN2[i]))
continue = readline(prompt="Continue: ")
} else {continue = "y"}
if (continue!="n"){
for (j in 1:length(iupos))
{
print(data.frame(i, Predictions$Country[i], africa_ius$IUs_NAME[iupos[j]], africa_ius$ADMIN2[iupos[j]], africa_ius$IU_ID[iupos[j]], Predictions$ADMIN3[i], Predictions$ADMIN2[i]))
accept = readline(prompt="Accept: ")
if (accept == "n"){
} else {Codes[i] = africa_ius$IU_ID[iupos[j]]
flag = 0
break}
}
}
if (flag == 1 & maxi >=2 & length(uniquematch)>1) {
maxi = max(uniquematch)
uniquematch = uniquematch[-which(unique(uniquematch)==maxi)]
} else if (maxi <2 | length(uniquematch)==1) {
flag = 0
}
}
}
} else {
Codes[i] = africa_ius$IU_ID[iupos]
}
}
}
}
}
Codes[163] = "ETH19082"
Codes[1559] = "SDN53248"
Codes[5861] = "COG12829"
CodesFinal = Codes
#write.csv(data.frame(Predictions, Codes), file = "PredictionsIUcodes.csv", row.names = F)
DataFinal = read.csv("PredictionsIUcodesFinal.csv")
DataScenarios = read.csv("DataScenarios.csv")
Scenarios = matrix(NA, nrow = nrow(DataFinal), ncol = 3)
for (i in 1:nrow(DataFinal))
{
pos = which(DataFinal$geoconnect[i] == DataScenarios$Geoconnect_ID)
if (length(pos) == 1){
Scenarios[i, ] = unlist(DataScenarios[pos, 55:57])
} else if (length(pos) > 1){
Scen = which.max(DataScenarios[pos, 57])
Scenarios[i, ] = unlist(DataScenarios[pos[Scen], 55:57])
}
}
length(which(is.na(Scenarios[, 1])))
DataAll = data.frame(Country = DataFinal$Country, Region = DataFinal$Region,
District = DataFinal$District, Subdistrict = DataFinal$Subdistrict,
Geoconnect_ID = DataFinal$geoconnect, Pop_point = DataFinal$pop_point,
Pop_district = DataFinal$pop_district, Logit = DataFinal$logit,
Sds = DataFinal$standard.errors, IUCodes = DataFinal$Codes, start_MDA = Scenarios[, 1],
last_MDA = Scenarios[, 2], Scenario = Scenarios[, 3])
DataAll = subset(DataAll, !is.na(IUCodes))
DataAll = subset(DataAll, !is.na(Scenario))
dim(DataAll)
length(unique(DataAll$IUCodes))
CodeUni = unique(DataAll$IUCodes)
for (i in 1:length(CodeUni))
{
pos = which(DataAll$IUCodes == CodeUni[i])
if (length(pos)>1)
{
print(pos)
print(DataAll[pos, ])
readline("Enter")
}
}
DataAll$IUCodes = factor(DataAll$IUCodes, levels = unique(c(levels(africa_ius$IU_ID),levels(DataAll$IUCodes))))
DataAll$IUCodes[422] = "ETH18932"
DataAll$IUCodes[613] = "ETH18652"
DataAll$IUCodes[36] = "ETH19098"
DataAll$IUCodes[3789] = "SEN40178"
DataAll$IUCodes[431] = "ETH18889"
DataAll$IUCodes[432] = "ETH19334"
DataAll$IUCodes[439] = "ETH18775"
DataAll$IUCodes[480] = "ETH19331"
DataAll$IUCodes[103] = "ETH18887"
DataAll$IUCodes[475] = "ETH18780"
DataAll$IUCodes[517] = "ETH18914"
DataAll$IUCodes[573] = NA
DataAll$IUCodes[481] = "ETH18808"
DataAll$IUCodes[554] = "ETH18939"
DataAll$IUCodes[571] = "ETH18856"
DataAll$IUCodes[1329] = NA
DataAll$IUCodes[610] = "ETH19323"
DataAll$IUCodes[2968] = NA
DataAll$IUCodes[c(37, 80, 149, 38, 39, 40, 643, 644, 747, 722, 723, 724, 731, 725, 733, 734, 726, 735, 736, 1296, 1297, 1298,
727, 732, 728, 737, 738, 729, 740, 730, 739, 741, 742, 751, 752, 753,
743, 744, 745, 746, 748, 749, 750, 754, 755, 756, 757, 758,
759, 760, 761, 762, 763, 1278, 1279, 1280, 1281, 1282, 1283, 1284,
1285, 1292, 1286, 1289, 1287, 1290, 1288, 1291, 1293, 1294, 1295,
1299, 1303, 1300, 1304, 1301, 1305, 1302, 1306, 1307, 1308, 1309, 1324,
1310, 1321,1311, 1322, 1312, 1319, 1313, 1323, 1314, 1325, 1315, 1320,
1316, 1326, 1317, 1318)] = NA
DataAll$IUCodes[767] = "COD13903"
DataAll$IUCodes[876] = "COD14057"
DataAll$IUCodes[1201] = NA
DataAll$IUCodes[2693] = "NGA36831"
DataAll$IUCodes[2697] = "NGA36835"
DataAll$IUCodes[2671] = "NGA36808"
DataAll$IUCodes[4380] = NA
DataAll$IUCodes[2718] = "NGA36872"
DataAll$IUCodes[2498] = "NGA36472"
DataAll$IUCodes[2716] = "NGA36870"
DataAll$IUCodes[3762] = "SEN40182"
DataAll$IUCodes[3908] = NA
DataAll$IUCodes[4410] = NA
DataAll$IUCodes[1327] = "ETH18633"
DataAll$IUCodes[531] = "ETH18885"
DataAll = subset(DataAll, !is.na(IUCodes))
dim(DataAll)
length(unique(DataAll$IUCodes))
CodeUni = unique(DataAll$IUCodes)
for (i in 1:length(CodeUni))
{
pos = which(DataAll$IUCodes == CodeUni[i])
if (length(pos)>1)
{
print(pos)
print(DataAll[pos, ])
readline("Enter")
}
}
DataAll$IUCodes[c(156,1509,3434, 3666)] = NA
DataAll$IUCodes[c(363,2926, 3646, 3810)] = NA
DataAll = subset(DataAll, !is.na(IUCodes))
dim(DataAll)
length(unique(DataAll$IUCodes))
write.csv(DataAll, file = "FinalData.csv", row.names = F)
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