library(tidyverse)

text <- c("Personnummer: 123456-1234",
          "Inte personnummer: 12345-123",
          "Personnummer igen fler på rad 123456-1234  123456-1234",
          "Lite blandat 123456-1234 lite text 123-1234 mer text 123456-1234",
          "Två exempel till 1234567-1234 123456-12345",
          "123456-1234")
pattern <- "(\\s|^)(\\d{6}-)\\d{4}(\\s|$)"
pattern_fel <- "\\d{6}-\\d{4}"

matches <- str_match_all(text, pattern = pattern)
#str_match_all(text, pattern = pattern_fel)

locations <- str_locate_all(text, pattern = pattern)
for(row in 1:length(locations)) {
  print("Ny rad:")
  print(text[row])
  if(nrow(matches[[row]]) == 0) next
  for(m in 1:nrow(matches[[row]])) {
    remove_space <- str_length(matches[[row]][m,4])
    str_sub(text[row], 
            start = locations[[row]][m,2]-3-remove_space, 
            end = locations[[row]][m,2]-remove_space) <- "XXXX"
    
  }
}
text

str_replace_all(string = text, pattern = pattern, replacement = "\\1\\2XXXX\\3")
ymd("år 2025 månad 5 dag 21")


library(pxweb)
# PXWEB query 
pxweb_query_list <- 
  list("Region"=c("0114","0115","0117","0120","0123","0125","0126","0127","0128","0136","0138","0139","0140","0160","0162","0163","0180","0181","0182","0183","0184","0186","0187","0188","0191","0192","0305","0319","0330","0331","0360","0380","0381","0382","0428","0461","0480","0481","0482","0483","0484","0486","0488","0509","0512","0513","0560","0561","0562","0563","0580","0581","0582","0583","0584","0586","0604","0617","0642","0643","0662","0665","0680","0682","0683","0684","0685","0686","0687","0760","0761","0763","0764","0765","0767","0780","0781","0821","0834","0840","0860","0861","0862","0880","0881","0882","0883","0884","0885","0980","1060","1080","1081","1082","1083","1214","1230","1231","1233","1256","1257","1260","1261","1262","1263","1264","1265","1266","1267","1270","1272","1273","1275","1276","1277","1278","1280","1281","1282","1283","1284","1285","1286","1287","1290","1291","1292","1293","1315","1380","1381","1382","1383","1384","1401","1402","1407","1415","1419","1421","1427","1430","1435","1438","1439","1440","1441","1442","1443","1444","1445","1446","1447","1452","1460","1461","1462","1463","1465","1466","1470","1471","1472","1473","1480","1481","1482","1484","1485","1486","1487","1488","1489","1490","1491","1492","1493","1494","1495","1496","1497","1498","1499","1715","1730","1737","1760","1761","1762","1763","1764","1765","1766","1780","1781","1782","1783","1784","1785","1814","1860","1861","1862","1863","1864","1880","1881","1882","1883","1884","1885","1904","1907","1960","1961","1962","1980","1981","1982","1983","1984","2021","2023","2026","2029","2031","2034","2039","2061","2062","2080","2081","2082","2083","2084","2085","2101","2104","2121","2132","2161","2180","2181","2182","2183","2184","2260","2262","2280","2281","2282","2283","2284","2303","2305","2309","2313","2321","2326","2361","2380","2401","2403","2404","2409","2417","2418","2421","2422","2425","2460","2462","2463","2480","2481","2482","2505","2506","2510","2513","2514","2518","2521","2523","2560","2580","2581","2582","2583","2584"),
       "Alder"=c("tot"),
       "Kon"=c("1","2"),
       "ContentsCode"=c("BE0101A9"),
       "Tid"=c("2024"))

# Download data 
px_data <- 
  pxweb_get(url = "https://api.scb.se/OV0104/v1/doris/sv/ssd/BE/BE0101/BE0101A/FolkmangdNov",
            query = pxweb_query_list)

# Convert to data.frame 
px_data_frame <- as.data.frame(px_data, column.name.type = "text", variable.value.type = "text")

?summarise

befolkning <- px_data_frame %>%
  group_by(region) %>%
  summarise(befolkning = sum(Antal))

befolkning

befolkning2 <- px_data_frame %>%
  group_by(region) %>%
  mutate(
    tot_befolkning = sum(Antal)
  )

befolkning2

# PXWEB query 
pxweb_query_list <- 
  list("Region"=c("0114","0115","0117","0120","0123","0125","0126","0127","0128","0136","0138","0139","0140","0160","0162","0163","0180","0181","0182","0183","0184","0186","0187","0188","0191","0192","0305","0319","0330","0331","0360","0380","0381","0382","0428","0461","0480","0481","0482","0483","0484","0486","0488","0509","0512","0513","0560","0561","0562","0563","0580","0581","0582","0583","0584","0586","0604","0617","0642","0643","0662","0665","0680","0682","0683","0684","0685","0686","0687","0760","0761","0763","0764","0765","0767","0780","0781","0821","0834","0840","0860","0861","0862","0880","0881","0882","0883","0884","0885","0980","1060","1080","1081","1082","1083","1214","1230","1231","1233","1256","1257","1260","1261","1262","1263","1264","1265","1266","1267","1270","1272","1273","1275","1276","1277","1278","1280","1281","1282","1283","1284","1285","1286","1287","1290","1291","1292","1293","1315","1380","1381","1382","1383","1384","1401","1402","1407","1415","1419","1421","1427","1430","1435","1438","1439","1440","1441","1442","1443","1444","1445","1446","1447","1452","1460","1461","1462","1463","1465","1466","1470","1471","1472","1473","1480","1481","1482","1484","1485","1486","1487","1488","1489","1490","1491","1492","1493","1494","1495","1496","1497","1498","1499","1715","1730","1737","1760","1761","1762","1763","1764","1765","1766","1780","1781","1782","1783","1784","1785","1814","1860","1861","1862","1863","1864","1880","1881","1882","1883","1884","1885","1904","1907","1960","1961","1962","1980","1981","1982","1983","1984","2021","2023","2026","2029","2031","2034","2039","2061","2062","2080","2081","2082","2083","2084","2085","2101","2104","2121","2132","2161","2180","2181","2182","2183","2184","2260","2262","2280","2281","2282","2283","2284","2303","2305","2309","2313","2321","2326","2361","2380","2401","2403","2404","2409","2417","2418","2421","2422","2425","2460","2462","2463","2480","2481","2482","2505","2506","2510","2513","2514","2518","2521","2523","2560","2580","2581","2582","2583","2584"),
       "ITtjanster"=c("40"),
       "ContentsCode"=c("KU0101D1"),
       "Tid"=c("2012"))

# Download data 
px_data <- 
  pxweb_get(url = "https://api.scb.se/OV0104/v1/doris/sv/ssd/KU/KU0101/KU0101C/BiblDatorTillgangTot",
            query = pxweb_query_list)

# Convert to data.frame 
px_data_frame <- as.data.frame(px_data, column.name.type = "text", variable.value.type = "text")

px_data_frame$Huvudbibliotek[is.na(px_data_frame$Huvudbibliotek)] <- 0

data_bibliotek <- px_data_frame
data_bibliotek

data_bibliotek %>%
  group_by(region) %>%
  summarise(
    Antal_datorer = Huvudbibliotek
  )

data_bibliotek$`typ av IT-tjänst` <- NULL
data_bibliotek$år <- NULL

tot_df <- full_join(
  data_bibliotek,
  befolkning
)

?left_join

x <- tibble(
  obs = c(1,3,4,5),
  var1 = c(1, 3, 4, 5),
)
y <- tibble(
  obs = c(2,3,4,5),
  var2 = c(2,3,4,5)
)
left_join(x,y)
right_join(x,y)
inner_join(x,y)
full_join(x,y)