Family Database - FAMILY

Data - OECD

Author

François Geerolf


Info

source dataset Title .html .rData
oecd FAMILY Family Database - FAMILY 2026-08-11 2026-08-02

Données sur la demographie

source dataset Title .html .rData
eurostat demo_minfind Infant mortality rates 2026-08-11 2026-08-11
ined fm_t70_2019.fr Evolution de la mortalité infantile et de ses nombreuses composantes, 2019 2026-08-01 2026-08-01
ined fm_t70_2021.fr Evolution de la mortalité infantile et de ses nombreuses composantes, 2021 2026-08-01 2026-08-01
ined p2d_2019.fr Mortalité infantile par département et région - p2d_2019.fr 2026-08-01 2026-08-01
insee DECES-MORTALITE Décès et mortalité 2026-08-12 2026-08-11
insee NAISSANCES-FECONDITE Naissances et fécondité 2026-08-12 2026-08-11
oecd FAMILY Family Database - FAMILY 2026-08-11 2026-08-02

Last

Code 
FAMILY |>
  group_by(TIME_PERIOD) |>
  summarise(Nobs = n()) |>
  arrange(desc(TIME_PERIOD)) |>
  head(1) |>
  print_table_conditional()
TIME_PERIOD Nobs
2022 522

COU

Code 
FAMILY |>
  left_join(FAMILY_var$COU, by = "COU") |>
  group_by(COU, Cou) |>
  summarise(Nobs = n()) |>
  arrange(-Nobs) |>
  mutate(Flag = gsub(" ", "-", str_to_lower(Cou)),
         Flag = paste0('<img src="../../icon/flag/vsmall/', Flag, '.png" alt="Flag">')) |>
  select(Flag, everything()) %>%
  {if (is_html_output()) datatable(., filter = 'top', rownames = F, escape = F) else .}

SEX

Code 
FAMILY |>
  left_join(FAMILY_var$SEX, by = "SEX") |>
  group_by(SEX, Sex) |>
  summarise(Nobs = n()) |>
  arrange(-Nobs) |>
  print_table_conditional()
SEX Sex Nobs
TOTAL Total 7790
FEMALE Female 1490
MALE Male 1490

IND

Code 
FAMILY |>
  left_join(FAMILY_var$IND, by = "IND") |>
  group_by(IND, Ind) |>
  summarise(Nobs = n()) |>
  arrange(-Nobs) |>
  print_table_conditional()

obsTime

Code 
FAMILY |>
  group_by(TIME_PERIOD) |>
  summarise(Nobs = n()) |>
  arrange(desc(TIME_PERIOD)) |>
  print_table_conditional()
TIME_PERIOD Nobs
2022 522
2021 839
2020 1072
2019 1261
2018 1930
2017 1200
2016 804
2015 898
2014 576
2013 222
2012 436
2011 182
2010 194
2009 292
2008 13
2007 10
2006 279
2005 15
2004 3
2003 8
2002 7
2001 3
2000 2
1997 1
1996 1

Total fertility rate - FAM1

Table

Code 
FAMILY |>
  filter(IND == "FAM1") |>
  left_join(FAMILY_var$COU, by = "COU") |>
  group_by(COU, Cou) |>
  summarise(Nobs = n(),
            TIME_PERIOD = last(TIME_PERIOD),
            obsValue = last(obsValue)) |>
  mutate(Flag = gsub(" ", "-", str_to_lower(Cou)),
         Flag = paste0('<img src="../../icon/flag/vsmall/', Flag, '.png" alt="Flag">')) |>
  select(Flag, everything()) %>%
  {if (is_html_output()) datatable(., filter = 'top', rownames = F, escape = F) else .}

France, Italy, Germany

Code 
FAMILY |>
  filter(IND == "FAM1",
         COU %in% c("FRA", "DEU", "ITA")) |>
  year_to_date() |>
  left_join(FAMILY_var$COU, by = "COU") |>
  rename(Location = Cou) |>
  left_join(colors, by = c("Location" = "country")) |>
  ggplot() + theme_minimal() + scale_color_identity() +
  geom_line(aes(x = date, y = obsValue, color = color)) + 
  xlab("") + ylab("") + add_3flags +
  scale_x_date(breaks = seq(1940, 2100, 5) |> paste0("-01-01") |> as.Date(),
               labels = date_format("%Y")) +
  scale_y_continuous(breaks = seq(0, 10, 0.2))

Crude marriage rate (marriages per 1000 people) - FAM4A

Table

Code 
FAMILY |>
  filter(IND == "FAM4A") |>
  left_join(FAMILY_var$COU, by = "COU") |>
  group_by(COU, Cou) |>
  summarise(Nobs = n(),
            TIME_PERIOD = last(TIME_PERIOD),
            obsValue = last(obsValue)) |>
  mutate(Flag = gsub(" ", "-", str_to_lower(Cou)),
         Flag = paste0('<img src="../../icon/flag/vsmall/', Flag, '.png" alt="Flag">')) |>
  select(Flag, everything()) %>%
  {if (is_html_output()) datatable(., filter = 'top', rownames = F, escape = F) else .}

France, Italy, Germany

Code 
FAMILY |>
  filter(IND == "FAM4A",
         COU %in% c("FRA", "DEU", "ITA")) |>
  year_to_date() |>
  left_join(FAMILY_var$COU, by = "COU") |>
  rename(Location = Cou) |>
  left_join(colors, by = c("Location" = "country")) |>
  ggplot() + theme_minimal() + scale_color_identity() +
  geom_line(aes(x = date, y = obsValue, color = color)) + 
  xlab("") + ylab("") + add_3flags +
  scale_x_date(breaks = seq(1940, 2100, 5) |> paste0("-01-01") |> as.Date(),
               labels = date_format("%Y")) +
  scale_y_continuous(breaks = seq(0, 10, 1))

Crude divorce rate (divorces per 1000 people) - FAM4B

Table

Code 
FAMILY |>
  filter(IND == "FAM4B") |>
  left_join(FAMILY_var$COU, by = "COU") |>
  group_by(COU, Cou) |>
  summarise(Nobs = n(),
            TIME_PERIOD = last(TIME_PERIOD),
            obsValue = last(obsValue)) |>
  mutate(Flag = gsub(" ", "-", str_to_lower(Cou)),
         Flag = paste0('<img src="../../icon/flag/vsmall/', Flag, '.png" alt="Flag">')) |>
  select(Flag, everything()) %>%
  {if (is_html_output()) datatable(., filter = 'top', rownames = F, escape = F) else .}

France, Italy, Germany

Code 
FAMILY |>
  filter(IND == "FAM4B",
         COU %in% c("FRA", "DEU", "ITA")) |>
  year_to_date() |>
  left_join(FAMILY_var$COU, by = "COU") |>
  rename(Location = Cou) |>
  left_join(colors, by = c("Location" = "country")) |>
  ggplot() + theme_minimal() + scale_color_identity() +
  geom_line(aes(x = date, y = obsValue, color = color)) + 
  xlab("") + ylab("") + add_3flags +
  scale_x_date(breaks = seq(1940, 2100, 5) |> paste0("-01-01") |> as.Date(),
               labels = date_format("%Y")) +
  scale_y_continuous(breaks = seq(0, 10, .2))

Infant mortality rate - FAM16A

Table

Code 
FAMILY |>
  filter(IND == "FAM16A") |>
  left_join(FAMILY_var$COU, by = "COU") |>
  group_by(COU, Cou) |>
  summarise(Nobs = n(),
            TIME_PERIOD = last(TIME_PERIOD),
            obsValue = last(obsValue)) |>
  arrange(obsValue) |>
  mutate(Flag = gsub(" ", "-", str_to_lower(Cou)),
         Flag = paste0('<img src="../../icon/flag/vsmall/', Flag, '.png" alt="Flag">')) |>
  select(Flag, everything()) %>%
  {if (is_html_output()) datatable(., filter = 'top', rownames = F, escape = F) else .}

France

All

Code 
FAMILY |>
  filter(IND == "FAM16A",
         COU %in% c("FRA")) |>
  add_row(TIME_PERIOD = "2020", obsValue = 3.6 ) |>
  add_row(TIME_PERIOD = "2021", obsValue = 3.7 ) |>
  add_row(TIME_PERIOD = "2022", obsValue = 3.9 ) |>
  add_row(TIME_PERIOD = "2023", obsValue = 4 ) |>
  year_to_date() |>
  left_join(FAMILY_var$COU, by = "COU") |>
  rename(Location = Cou) |>
  left_join(colors, by = c("Location" = "country")) |>
  ggplot() + theme_minimal() + scale_color_identity() +
  geom_line(aes(x = date, y = obsValue)) + 
  xlab("") + ylab("") + add_3flags +
  scale_x_date(breaks = seq(1940, 2100, 5) |> paste0("-01-01") |> as.Date(),
               labels = date_format("%Y")) +
  scale_y_continuous(breaks = seq(0, 100, 5),
                     labels = dollar_format(a = .1, pre = "", su = "‰"))

1980-

Code 
FAMILY |>
  filter(IND == "FAM16A",
         COU %in% c("FRA")) |>
  add_row(TIME_PERIOD = "2020", obsValue = 3.6 ) |>
  add_row(TIME_PERIOD = "2021", obsValue = 3.7 ) |>
  add_row(TIME_PERIOD = "2022", obsValue = 3.9 ) |>
  add_row(TIME_PERIOD = "2023", obsValue = 4 ) |>
  year_to_date() |>
  filter(date >= as.Date("1991-01-01")) |>
  left_join(FAMILY_var$COU, by = "COU") |>
  rename(Location = Cou) |>
  left_join(colors, by = c("Location" = "country")) |>
  ggplot() + theme_minimal() + scale_color_identity() +
  geom_line(aes(x = date, y = obsValue)) + 
  ylab("Taux de mortalité infantile (pour mille)") + xlab("") + add_3flags +
  scale_x_date(breaks = seq(1991, 2100, 2) |> paste0("-01-01") |> as.Date(),
               labels = date_format("%Y")) +
  scale_y_continuous(breaks = seq(0, 100, 1),
                     labels = dollar_format(a = .1, pre = "", su = "‰")) +
  theme(legend.position = c(0.2, 0.7),
        legend.title = element_blank(),
        axis.text.x = element_text(angle = 45, vjust = 1, hjust = 1))

France, Italy, Germany, Spain, Portugal

All

Code 
FAMILY |>
  filter(IND == "FAM16A",
         COU %in% c("FRA", "DEU", "ITA", "ESP", "PRT")) |>
  year_to_date() |>
  left_join(FAMILY_var$COU, by = "COU") |>
  rename(Location = Cou) |>
  left_join(colors, by = c("Location" = "country")) |>
  ggplot() + theme_minimal() + scale_color_identity() +
  geom_line(aes(x = date, y = obsValue, color = color)) + 
  xlab("") + ylab("") + add_3flags +
  scale_x_date(breaks = seq(1940, 2100, 5) |> paste0("-01-01") |> as.Date(),
               labels = date_format("%Y")) +
  scale_y_continuous(breaks = seq(0, 100, 5))

Log

Code 
FAMILY |>
  filter(IND == "FAM16A",
         COU %in% c("FRA", "DEU", "ITA", "ESP")) |>
  # Source: 2020,2021 = Eurostat, demo_minfind; 2022-2023: INSEE
  add_row(COU = "DEU", TIME_PERIOD = "2020", obsValue = 3.1 ) |>
  add_row(COU = "DEU", TIME_PERIOD = "2021", obsValue = 3 ) |>
  add_row(COU = "ITA", TIME_PERIOD = "2020", obsValue = 2.4 ) |>
  add_row(COU = "ITA", TIME_PERIOD = "2021", obsValue = 2.3 ) |>
  add_row(COU = "ESP", TIME_PERIOD = "2020", obsValue = 2.6 ) |>
  add_row(COU = "ESP", TIME_PERIOD = "2021", obsValue = 2.5 ) |>
  add_row(COU = "FRA", TIME_PERIOD = "2020", obsValue = 3.6 ) |>
  add_row(COU = "FRA", TIME_PERIOD = "2021", obsValue = 3.7 ) |>
  add_row(COU = "FRA", TIME_PERIOD = "2022", obsValue = 3.9 ) |>
  add_row(COU = "FRA", TIME_PERIOD = "2023", obsValue = 4 ) |>
  year_to_date() |>
  left_join(FAMILY_var$COU, by = "COU") |>
  rename(Location = Cou) |>
  left_join(colors, by = c("Location" = "country")) |>
  mutate(color = ifelse(COU == "PRT", color2, color)) |>
  arrange(desc(date)) |>
  ggplot() + theme_minimal() + scale_color_identity() +
  geom_line(aes(x = date, y = obsValue, color = color)) + 
  xlab("") + ylab("Taux de mortalité infantile (‰)") + add_4flags +
  scale_x_date(breaks = seq(1940, 2100, 10) |> paste0("-01-01") |> as.Date(),
               labels = date_format("%Y")) +
  scale_y_log10(breaks = c(seq(0, 100, 10), 6, 8, 15, 25, seq(1, 5, 1)),
                     labels = dollar_format(a = .1, pre = "", su = "‰"))

2000-

Code 
FAMILY |>
  filter(IND == "FAM16A",
         COU %in% c("FRA", "DEU", "ITA")) |>
  year_to_date() |>
  filter(date >= as.Date("2000-01-01")) |>
  left_join(FAMILY_var$COU, by = "COU") |>
  rename(Location = Cou) |>
  left_join(colors, by = c("Location" = "country")) |>
  ggplot() + theme_minimal() + scale_color_identity() +
  geom_line(aes(x = date, y = obsValue, color = color)) + 
  xlab("") + ylab("Taux de mortalité infantile (‰)") + add_3flags +
  scale_x_date(breaks = seq(1940, 2100, 2) |> paste0("-01-01") |> as.Date(),
               labels = date_format("%Y")) +
  scale_y_continuous(breaks = seq(0, 100, .2),
                     labels = dollar_format(a = .1, pre = "", su = "‰"))

2000-

Code 
FAMILY |>
  filter(IND == "FAM16A",
         COU %in% c("FRA", "DEU", "ITA", "PRT", "ESP")) |>
  year_to_date() |>
  filter(date >= as.Date("2000-01-01")) |>
  left_join(FAMILY_var$COU, by = "COU") |>
  rename(Location = Cou) |>
  left_join(colors, by = c("Location" = "country")) |>
  ggplot() + theme_minimal() + scale_color_identity() +
  geom_line(aes(x = date, y = obsValue, color = color)) + 
  xlab("") + ylab("Taux de mortalité infantile (‰)") + add_5flags +
  scale_x_date(breaks = seq(1940, 2100, 2) |> paste0("-01-01") |> as.Date(),
               labels = date_format("%Y")) +
  scale_y_continuous(breaks = seq(0, 100, .2),
                     labels = dollar_format(a = .1, pre = "", su = "‰"))