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@coulmont
Created December 2, 2020 13:02
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deces en france, coordonnées polaires, version animée
# ajout des informations pour l'animation
# ---------------------------------------
library(gganimate)
library(broom)
dc <- bind_rows(dc_jour,dc_insee_jour,deces_ecdc,deces_insee_provisoires)
# on démarre du fichier dc utilisé pour le graphique surmortalité
#
# correction année et mois pour les données de 2020
dc <- dc %>%
mutate(jour = ifelse(annee==2020, day(date_fictive),jour),
mois = ifelse(annee==2020, month(date_fictive),mois))
dc <- dc %>%
arrange(annee,mois,jour) %>%
filter(categorie !="ecdc") # on enleve ecdc pour l'instant
#
# dc %>%
# select(annee,mois,jour,date_fictive,N) %>%
# ggplot(aes(date_fictive,N,group=annee)) +
# geom_line() +
# scale_x_date(expand = expansion(add=c(2,2))) +
# coord_polar()
#
# df <- tibble(jour = seq(ymd("2001-01-01"), ymd("2004-01-30"), by ="day") ,
# valeur = 10 + rnorm(1125)) %>%
# mutate(valeur = valeur + row_number()/100 )
#
#
# df <- df %>%
# mutate(annee = year(jour),
# annee_fictive = 2020,
# restant = str_sub(jour,5,10),
# date_fictive = ymd(glue("{annee_fictive}{restant}")))
#
# df %>%
# ggplot(aes(jour,valeur)) +
# geom_path() +
# coord_polar()
# ralentir 2020
# 4 fois plus lent
dc <- bind_rows( dc %>% filter(annee != 2020) %>% mutate(repetition = 0),
dc %>% filter(annee == 2020) %>% mutate(repetition = 1),
dc %>% filter(annee == 2020) %>% mutate(repetition = 2),
dc %>% filter(annee == 2020) %>% mutate(repetition = 3),
dc %>% filter(annee == 2020) %>% mutate(repetition = 4) ) %>%
arrange(annee,mois,jour) %>%
mutate(groupage = as.numeric(str_sub(annee,3,4)) ) %>%
group_by(annee) %>%
mutate(numero_frame = row_number()) %>%
ungroup() %>%
mutate(numero_frame = 366*(groupage-1) + numero_frame) %>%
mutate(texte = annee)
# pour éviter que le label de l'année bouge dans tous les sens
# on le trace sur la courbe "loess"
#
dc <- dc %>%
left_join( dc %>% group_by(annee) %>%
do(augment(loess(N ~ numero_frame, .,span=.1))) %>%
ungroup() %>%
select(annee,numero_frame,.fitted) ,
by=c("annee","numero_frame"))
# dc <- dc %>%
# mutate(numero_frame = (max(dc$numero_frame) + row_number())) %>%
# mutate(texte = annee)
# graphique animé
# ---------------
p <- dc %>%
#filter(annee %in% c(2001,2002,2003,2019)) %>%
mutate(couleur = case_when(annee == 2003 ~ "navyblue",
annee == 2020 ~ "firebrick1",
TRUE ~ "gray"),
couleur_texte = ifelse(annee<2020,"black","firebrick1"),
transparence = case_when(annee %in% c(2003,2020) ~ 1,
TRUE ~ .5)) %>%
#na.omit() %>%
ggplot(aes(date_fictive, N, group = annee,
color=I(couleur), alpha=I(transparence)) )+
#geom_smooth(data = . %>% filter(annee==2020) , se=F, span = .15) +
geom_ribbon(data = . %>% filter(annee == 2019) ,
aes(ymin = mini, ymax = maxi),
alpha=.5, fill="gray") +
geom_line(size=.5, aes(group=annee)) +
geom_point(color="black") +
# geom_text_repel(aes(date_fictive,.fitted,
# group=annee,
# label = texte,
# color = I(couleur_texte)),
# box.padding= 1,
# nudge_x = 5, alpha=1 ) +
geom_text(aes(date_fictive,.fitted,
group=annee,
label = texte,
color = I(couleur_texte)),
size=6,
nudge_x = 25, alpha=1 ) +
# geom_line(data = dc_insee_jour, aes(date_fictive, N),
# color= "firebrick1") +
# geom_point(data = dc_insee_jour,
# aes(date_fictive, N),
# color= "firebrick1") +
# geom_text(data = dc_insee_jour,
# aes(date_fictive, N, label = texte),
# color= "firebrick1", nudge_x = 5) +
# scale_x_date(date_labels = "%b",
# minor_breaks = NULL) +
coord_polar() +
scale_x_date(date_breaks = "1 month", date_labels = "%b", expand=expansion(add=c(0,-26))) +
scale_y_continuous(limits = c(0,3655),
breaks = c(0,500,1000,1500,2000,2500),
minor_breaks = NULL,
expand=expansion(add=c(0,-800))) +
labs(title = "Nombre quotidien de décès en France, 2001-2020",
subtitle = "En rouge, l'année 2020, en bleu 2003, en gris les années 2001 à 2019.",
y=NULL,x=NULL,
caption = "Sources : Fichier des décès sur data.gouv.fr et Fichier des décès sur insee.fr | Graphique : B. Coulmont") +
theme_ipsum(plot_margin = margin(5, 5, 0, 5),
plot_title_margin=5 ,
subtitle_margin=5,
base_family = "Helvetica") +
theme(plot.title.position="plot") +
transition_reveal(along = numero_frame, keep_last = FALSE)
#p
animate(p, nframes = 10,fps=1)
#animate(p, nframes = 1000,width=800,height=500,fps=5, end_pause = 73)
animate(p , nframes= 8442, fps= 60,
width=1200,height=1200, end_pause = 200,
res = 130,
renderer = av_renderer(glue("~/Desktop/output-deces-{today()}.mp4"), codec = "libx264"))
# animate(p , nframes= 245, fps=6,
# width=1200,height=676, end_pause = 200,
# res = 130,
# renderer = av_renderer("~/Desktop/output-deces-2.mp4", codec = "libx264"))
#
@coulmont
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coulmont commented Dec 7, 2020

> head(dc)
# A tibble: 6 x 10
  date_deces     N  jour  mois annee  maxi  mini type     categorie date_fictive
  <date>     <dbl> <int> <dbl> <dbl> <int> <int> <chr>    <chr>     <date>      
1 2001-01-01  1670     1     1  2001  2206  1640 deces_c… fichier_… 2020-01-01  
2 2001-01-02  1777     2     1  2001  2371  1537 deces_c… fichier_… 2020-01-02  
3 2001-01-03  1775     3     1  2001  2353  1672 deces_c… fichier_… 2020-01-03  
4 2001-01-04  1701     4     1  2001  2251  1605 deces_c… fichier_… 2020-01-04  
5 2001-01-05  1697     5     1  2001  2271  1569 deces_c… fichier_… 2020-01-05  
6 2001-01-06  1651     6     1  2001  2260  1588 deces_c… fichier_… 2020-01-06  

@romunov
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romunov commented Dec 7, 2020

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