France, Portrait Social 2019 - FPS2019

Data - INSEE

Author

variable

Code

FPS2019 %>%
  group_by(variable) %>%
  summarise(Nobs = n()) %>%
  print_table_conditional()

variable	Nobs
1er décile	25
9e décile	25
Actifs	10
Actifs BIT	21
Autres inactifs	10
Autres inactifs BIT	21
Moyenne	25
Médiane	25
PIB par unité de consommation (UC)	42
Retraités	10
Retraités BIT	21

sheet

Code

FPS2019 %>%
  group_by(sheet) %>%
  summarise(Nobs = n()) %>%
  print_table_conditional()

sheet	Nobs
Figure 2	142
Figure 3	93

year

Code

FPS2019 %>%
  group_by(year) %>%
  summarise(Nobs = n()) %>%
  arrange(desc(year)) %>%
  print_table_conditional()

Evolution des déciles et de la moyenne des niveaux de vie - E4

Figure 2

Rapport

Code

i_g("bib/insee/FPS2019/E4-fig2.png")

All

Code

FPS2019 %>%
  filter(sheet == "Figure 2") %>%
  year_to_date2 %>%
  ggplot(.) + theme_minimal() + ylab("Avant Redistribution") + xlab("") +
  geom_line(aes(x = date, y = value, color = variable)) +
  theme(legend.title = element_blank(),
        legend.position = c(0.2, 0.8)) +
  scale_x_date(breaks = seq(1950, 2022, 5) %>% paste0("-01-01") %>% as.Date,
               labels = date_format("%Y")) +
  scale_color_manual(values = viridis(6)[1:5]) +
  scale_y_log10(breaks = seq(0, 200, 10))

1990-

Code

FPS2019 %>%
  filter(sheet == "Figure 2") %>%
  year_to_date2 %>%
  filter(date >= as.Date("1990-01-01")) %>%
  group_by(variable) %>%
  mutate(value = 100*value/value[date == as.Date("1990-01-01")]) %>%
  ggplot(.) + theme_minimal() + ylab("Avant Redistribution") + xlab("") +
  geom_line(aes(x = date, y = value, color = variable)) +
  theme(legend.title = element_blank(),
        legend.position = c(0.2, 0.8)) +
  scale_x_date(breaks = seq(1950, 2022, 2) %>% paste0("-01-01") %>% as.Date,
               labels = date_format("%Y")) +
  scale_color_manual(values = viridis(6)[1:5]) +
  scale_y_log10(breaks = seq(0, 200, 5))

1996-

Code

FPS2019 %>%
  filter(sheet == "Figure 2") %>%
  year_to_date2 %>%
  filter(date >= as.Date("1996-01-01")) %>%
  group_by(variable) %>%
  mutate(value = 100*value/value[date == as.Date("1996-01-01")]) %>%
  ggplot(.) + theme_minimal() + ylab("Avant Redistribution") + xlab("") +
  geom_line(aes(x = date, y = value, color = variable)) +
  theme(legend.title = element_blank(),
        legend.position = c(0.2, 0.8)) +
  scale_x_date(breaks = seq(1950, 2022, 2) %>% paste0("-01-01") %>% as.Date,
               labels = date_format("%Y")) +
  scale_color_manual(values = viridis(6)[1:5]) +
  scale_y_log10(breaks = seq(0, 200, 5))