source | dataset | .html | .RData |
---|---|---|---|
insee | IPC-2015 | 2024-04-18 | 2024-04-09 |
ipp | ret_etat | 2024-04-20 | 2024-04-20 |
ipp | revalorisation_pension | 2024-04-14 | 2024-04-14 |
source | dataset | .html | .RData |
---|---|---|---|
insee | CNA-2014-RDB | 2024-04-18 | 2024-04-18 |
insee | CNT-2014-CSI | 2024-04-18 | 2024-04-18 |
insee | conso-eff-fonction | 2024-04-18 | 2022-06-14 |
insee | reve-niv-vie-individu-activite | 2024-04-18 | NA |
insee | t_7401 | 2024-04-18 | 2023-12-23 |
insee | t_men_val | 2024-04-18 | 2024-03-04 |
insee | t_pouvachat_val | 2024-04-18 | 2024-03-04 |
insee | t_recapAgent_val | 2024-04-18 | 2024-04-02 |
insee | t_salaire_val | 2024-04-18 | 2024-03-04 |
oecd | HH_DASH | 2024-04-16 | 2023-09-09 |
ret_etat %>%
select(-taux_employeur_explicite.ati) %>%
gather(variable, value, -date) %>%
group_by(variable) %>%
complete(date = seq.Date(min(date), max(date), by = "day")) %>%
fill(value) %>%
mutate(value = ifelse(date >= as.Date("2006-01-01") & variable == "taux_implicite", NA, value)) %>%
left_join(variable, by = "variable") %>%
ggplot() + geom_line(aes(x = date, y = value, color = Variable)) +
theme_minimal() +
scale_x_date(breaks = seq(1920, 2100, 5) %>% paste0("-01-01") %>% as.Date,
labels = date_format("%Y")) +
theme(legend.position = c(0.3, 0.9),
legend.title = element_blank()) +
scale_y_continuous(breaks = 0.01*seq(0, 200, 10),
labels = percent_format()) +
ylab("Taux employeur (%)") + xlab("")