Family Database - FAMILY

Data - OECD

Author

François Geerolf


Info

source dataset .html .RData

oecd

FAMILY

 2024-09-11 2024-02-13

Données sur la demographie

source dataset .html .RData

eurostat

demo_minfind

 2024-09-14 2024-09-14

ined

fm_t70_2019.fr

 2024-06-20 2022-01-31

ined

fm_t70_2021.fr

 2024-06-20 2023-10-10

ined

p2d_2019.fr

 2024-06-20 2021-12-18

insee

DECES-MORTALITE

 2024-09-14 2024-09-14

insee

NAISSANCES-FECONDITE

 2024-09-14 2024-09-14

oecd

FAMILY

 2024-09-11 2024-02-13

Last

Code 
FAMILY %>%
  group_by(obsTime) %>%
  summarise(Nobs = n()) %>%
  arrange(desc(obsTime)) %>%
  head(1) %>%
  print_table_conditional()
obsTime 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 42900
MALE Male 3914
FEMALE Female 3910

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(obsTime) %>%
  summarise(Nobs = n()) %>%
  arrange(desc(obsTime)) %>%
  print_table_conditional()

Total fertility rate - FAM1

Table

Code 
FAMILY %>%
  filter(IND == "FAM1") %>%
  left_join(FAMILY_var$COU, by = "COU") %>%
  group_by(COU, Cou) %>%
  summarise(Nobs = n(),
            obsTime = last(obsTime),
            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, 2050, 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(),
            obsTime = last(obsTime),
            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, 2050, 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(),
            obsTime = last(obsTime),
            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, 2050, 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(),
            obsTime = last(obsTime),
            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(obsTime = "2020", obsValue = 3.6 ) %>%
  add_row(obsTime = "2021", obsValue = 3.7 ) %>%
  add_row(obsTime = "2022", obsValue = 3.9 ) %>%
  add_row(obsTime = "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, 2050, 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(obsTime = "2020", obsValue = 3.6 ) %>%
  add_row(obsTime = "2021", obsValue = 3.7 ) %>%
  add_row(obsTime = "2022", obsValue = 3.9 ) %>%
  add_row(obsTime = "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, 2050, 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, 2050, 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", obsTime = "2020", obsValue = 3.1 ) %>%
  add_row(COU = "DEU", obsTime = "2021", obsValue = 3 ) %>%
  add_row(COU = "ITA", obsTime = "2020", obsValue = 2.4 ) %>%
  add_row(COU = "ITA", obsTime = "2021", obsValue = 2.3 ) %>%
  add_row(COU = "ESP", obsTime = "2020", obsValue = 2.6 ) %>%
  add_row(COU = "ESP", obsTime = "2021", obsValue = 2.5 ) %>%
  add_row(COU = "FRA", obsTime = "2020", obsValue = 3.6 ) %>%
  add_row(COU = "FRA", obsTime = "2021", obsValue = 3.7 ) %>%
  add_row(COU = "FRA", obsTime = "2022", obsValue = 3.9 ) %>%
  add_row(COU = "FRA", obsTime = "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, 2050, 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, 2050, 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, 2050, 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 = "‰"))