---
output:
html_document:
toc: true
toc_float: true
params:
CRH: NA
CRH_seance: NA
CRH_sans_seance: NA
---
```{r init, warning = F, message = F, echo = F}
library(tidyverse)
library(DT)
library(magrittr)
library(stringr)
library(knitr)
library(lubridate)
library(plotly)
opts_chunk$set(warning = F,
message = F,
fig.width = 9,
fig.height = 6,
echo = F)
options(DT.options = list(paging = F,
info = F,
searching = F,
dom = "Bfrtip",
buttons = c('copy', 'excel')))
```
```{r data, echo = F, message = F, warning = F}
mois_label <- c("Janvier",
"Février",
"Mars",
"Avril",
"Mai",
"Juin",
"Juillet",
"Août",
"Septembre",
"Octobre",
"Novembre",
"Décembre")
pdf(NULL)
```
# Tous RUMs confondus
## Par mois
```{r}
CRH() %>%
count(Mois, Notes) %>%
mutate(Notes = ifelse(is.na(Notes), "Manquant", Notes)) %>%
spread(Notes, n) %>%
full_join(CRH() %>% count(Mois)) %>%
select(Mois, RUM = n, CRHP, CRHA, Manquant) %>%
full_join(CRH() %>% group_by(Mois) %>% summarise(`Délai médian (j)` = median(Delai))) %>%
mutate(CRHA = ifelse(is.na(CRHA), integer(1), CRHA),
CRHP = ifelse(is.na(CRHP), integer(1), CRHP),
`% absents` = CRHA / RUM) %>%
datatable(rownames = F,
extensions = 'Buttons',
colnames = c("Non renseigné" = "Manquant",
"#CRHA" = "CRHA",
"#CRHP" = "CRHP")) %>%
formatPercentage(7)
```
```{r}
CRH() %>%
ggplot(aes(x = Mois, fill = Notes)) +
geom_bar(position = "fill") +
ylab("Proportion") +
theme(axis.text.x = element_text(angle = -45, hjust = 1)) +
ggtitle("Proportion des #CRHA et #CRHP par mois de sortie du RSS") -> p
ggplotly(p)
```
## Par Pôle
```{r}
CRH() %>%
count(Pole, Notes) %>%
mutate(Notes = ifelse(is.na(Notes), "Manquant", Notes)) %>%
spread(Notes, n) %>%
full_join(CRH() %>% count(Pole)) %>%
select(Pole, RUM = n, CRHP, CRHA, Manquant) %>%
full_join(CRH() %>% group_by(Pole) %>% summarise(`Délai médian (j)` = median(Delai))) %>%
mutate(CRHA = ifelse(is.na(CRHA), integer(1), CRHA),
CRHP = ifelse(is.na(CRHP), integer(1), CRHP),
`% absents` = CRHA / RUM) %>%
datatable(rownames = F,
extensions = 'Buttons',
colnames = c("Pôle" = "Pole",
"Non renseigné" = "Manquant",
"#CRHA" = "CRHA",
"#CRHP" = "CRHP")) %>%
formatPercentage(7)
```
```{r}
CRH() %>%
ggplot(aes(x = Pole, fill = Notes)) +
geom_bar(position = "fill") +
ylab("Proportion") +
ggtitle("Proportion des #CRHA et #CRHP par pôle, depuis avril 2016") +
theme(axis.text.x = element_text(angle = -45, hjust = 1)) -> p
ggplotly(p)
```
## Par Pôle, par service et par mois
```{r}
CRH() %>%
count(Pole, Service, Mois, Notes) %>%
mutate(Notes = ifelse(is.na(Notes), "Manquant", Notes)) %>%
spread(Notes, n) %>%
full_join(CRH() %>% count(Pole, Service, Mois)) %>%
ungroup %>%
select(Pole, Service, Mois, RUM = n, CRHP, CRHA, Manquant) %>%
full_join(CRH() %>% group_by(Pole, Service, Mois) %>% summarise(`Délai médian (j)` = median(Delai))) %>%
mutate(CRHA = ifelse(is.na(CRHA), integer(1), CRHA),
CRHP = ifelse(is.na(CRHP), integer(1), CRHP),
`% absents` = CRHA / RUM,
Pole = Pole %>% factor,
Mois = Mois %>% factor) %>%
datatable(rownames = F,
extensions = 'Buttons',
colnames = c("Pôle" = "Pole",
"Non renseigné" = "Manquant",
"#CRHA" = "CRHA",
"#CRHP" = "CRHP"),
filter = "top",
options = list(searching = T, paging = T)) %>%
formatPercentage(9)
```
```{r}
CRH() %>%
count(Pole, Mois, Notes) %>%
mutate(Notes = ifelse(is.na(Notes), "Manquant", Notes)) %>%
spread(Notes, n) %>%
mutate(Manquant = ifelse(is.na(Manquant), integer(1), Manquant),
CRHA = ifelse(is.na(CRHA), integer(1), CRHA),
CRHP = ifelse(is.na(CRHP), integer(1), CRHP),
pourcent = CRHA / (CRHA + CRHP + Manquant)) %>%
ggplot(aes(x = Mois, y = pourcent, colour = Pole, group = Pole)) +
geom_line(stat = "identity") +
geom_point() +
theme(axis.text.x = element_text(angle = -45, hjust = 1)) +
ylab("Proportion de #CRHA") +
ggtitle("Évolution des proportions de #CRHA par pôle") -> p
ggplotly(p, tooltip = c("x", "y", "colour"))
```
----
# RUMs non séance
## Par mois
```{r}
CRH_sans_seance() %>%
count(Mois, Notes) %>%
mutate(Notes = ifelse(is.na(Notes), "Manquant", Notes)) %>%
spread(Notes, n) %>%
full_join(CRH_sans_seance() %>% count(Mois)) %>%
select(Mois, RUM = n, CRHP, CRHA, Manquant) %>%
full_join(CRH_sans_seance() %>% group_by(Mois) %>% summarise(`Délai médian (j)` = median(Delai))) %>%
mutate(CRHA = ifelse(is.na(CRHA), integer(1), CRHA),
CRHP = ifelse(is.na(CRHP), integer(1), CRHP),
`% absents` = CRHA / RUM) %>%
datatable(rownames = F,
extensions = 'Buttons',
colnames = c("Non renseigné" = "Manquant",
"#CRHA" = "CRHA",
"#CRHP" = "CRHP")) %>%
formatPercentage(7)
```
```{r}
CRH_sans_seance() %>%
ggplot(aes(x = Mois, fill = Notes)) +
geom_bar(position = "fill") +
theme(axis.text.x = element_text(angle = -45, hjust = 1)) +
ylab("Proportion") +
ggtitle("Proportion des #CRHA et #CRHP par mois de sortie du RSS") -> p
ggplotly(p)
```
## Par Pôle
```{r}
CRH_sans_seance() %>%
count(Pole, Notes) %>%
mutate(Notes = ifelse(is.na(Notes), "Manquant", Notes)) %>%
spread(Notes, n) %>%
full_join(CRH_sans_seance() %>% count(Pole)) %>%
select(Pole, RUM = n, CRHP, CRHA, Manquant) %>%
full_join(CRH_sans_seance() %>% group_by(Pole) %>% summarise(`Délai médian (j)` = median(Delai))) %>%
mutate(CRHA = ifelse(is.na(CRHA), integer(1), CRHA),
CRHP = ifelse(is.na(CRHP), integer(1), CRHP),
`% absents` = CRHA / RUM) %>%
datatable(rownames = F,
extensions = 'Buttons',
colnames = c("Pôle" = "Pole",
"Non renseigné" = "Manquant",
"#CRHA" = "CRHA",
"#CRHP" = "CRHP")) %>%
formatPercentage(7)
```
```{r}
CRH_sans_seance() %>%
ggplot(aes(x = Pole, fill = Notes)) +
geom_bar(position = "fill") +
ylab("Proportion") +
ggtitle("Proportion des #CRHA et #CRHP par pôle, depuis avril 2016") +
theme(axis.text.x = element_text(angle = -45, hjust = 1)) -> p
ggplotly(p)
```
## Par Pôle, par service et par mois
```{r}
CRH_sans_seance() %>%
count(Pole, Service, Mois, Notes) %>%
mutate(Notes = ifelse(is.na(Notes), "Manquant", Notes)) %>%
spread(Notes, n) %>%
full_join(CRH_sans_seance() %>% count(Pole, Service, Mois)) %>%
ungroup %>%
select(Pole, Service, Mois, RUM = n, CRHP, CRHA, Manquant) %>%
full_join(CRH_sans_seance() %>% group_by(Pole, Service, Mois) %>% summarise(`Délai médian (j)` = median(Delai))) %>%
mutate(CRHA = ifelse(is.na(CRHA), integer(1), CRHA),
CRHP = ifelse(is.na(CRHP), integer(1), CRHP),
`% absents` = CRHA / RUM,
Pole = Pole %>% factor,
Mois = Mois %>% factor) %>%
datatable(rownames = F,
extensions = 'Buttons',
colnames = c("Pôle" = "Pole",
"Non renseigné" = "Manquant",
"#CRHA" = "CRHA",
"#CRHP" = "CRHP"),
filter = "top",
options = list(searching = T, paging = T)) %>%
formatPercentage(9)
```
```{r}
CRH_sans_seance() %>%
count(Pole, Mois, Notes) %>%
mutate(Notes = ifelse(is.na(Notes), "Manquant", Notes)) %>%
spread(Notes, n) %>%
mutate(Manquant = ifelse(is.na(Manquant), integer(1), Manquant),
CRHA = ifelse(is.na(CRHA), integer(1), CRHA),
CRHP = ifelse(is.na(CRHP), integer(1), CRHP),
pourcent = CRHA / (CRHA + CRHP + Manquant)) %>%
ggplot(aes(x = Mois, y = pourcent, colour = Pole, group = Pole)) +
geom_line(stat = "identity") +
geom_point() +
theme(axis.text.x = element_text(angle = -45, hjust = 1)) +
ylab("Proportion de #CRHA") +
ggtitle("Évolution des proportions de #CRHA par pôle") -> p
ggplotly(p, tooltip = c("x", "y", "colour"))
```
----
# RUMs séance
## Par mois
```{r}
CRH_seance() %>%
count(Mois, Notes) %>%
mutate(Notes = ifelse(is.na(Notes), "Manquant", Notes)) %>%
spread(Notes, n) %>%
full_join(CRH_seance() %>% count(Mois)) %>%
select(Mois, RUM = n, CRHP, CRHA, Manquant) %>%
full_join(CRH_seance() %>% group_by(Mois) %>% summarise(`Délai médian (j)` = median(Delai))) %>%
mutate(CRHA = ifelse(is.na(CRHA), integer(1), CRHA),
CRHP = ifelse(is.na(CRHP), integer(1), CRHP),
`% absents` = CRHA / RUM) %>%
datatable(rownames = F,
extensions = 'Buttons',
colnames = c("Non renseigné" = "Manquant",
"#CRHA" = "CRHA",
"#CRHP" = "CRHP")) %>%
formatPercentage(7)
```
```{r}
CRH_seance() %>%
ggplot(aes(x = Mois, fill = Notes)) +
geom_bar(position = "fill") +
theme(axis.text.x = element_text(angle = -45, hjust = 1)) +
ylab("Proportion") +
ggtitle("Proportion des #CRHA et #CRHP par mois de sortie du RSS") -> p
ggplotly(p)
```
## Par Pôle
```{r}
CRH_seance() %>%
count(Pole, Notes) %>%
mutate(Notes = ifelse(is.na(Notes), "Manquant", Notes)) %>%
spread(Notes, n) %>%
full_join(CRH_seance() %>% count(Pole)) %>%
select(Pole, RUM = n, CRHP, CRHA, Manquant) %>%
full_join(CRH_seance() %>% group_by(Pole) %>% summarise(`Délai médian (j)` = median(Delai))) %>%
mutate(CRHA = ifelse(is.na(CRHA), integer(1), CRHA),
CRHP = ifelse(is.na(CRHP), integer(1), CRHP),
`% absents` = CRHA / RUM) %>%
datatable(rownames = F,
extensions = 'Buttons',
colnames = c("Pôle" = "Pole",
"Non renseigné" = "Manquant",
"#CRHA" = "CRHA",
"#CRHP" = "CRHP")) %>%
formatPercentage(7)
```
```{r}
CRH_seance() %>%
ggplot(aes(x = Pole, fill = Notes)) +
geom_bar(position = "fill") +
ylab("Proportion") +
ggtitle("Proportion des #CRHA et #CRHP par pôle, depuis avril 2016") +
theme(axis.text.x = element_text(angle = -45, hjust = 1)) -> p
ggplotly(p)
```
## Par Pôle, par service et par mois
```{r}
CRH_seance() %>%
count(Pole, Service, Mois, Notes) %>%
mutate(Notes = ifelse(is.na(Notes), "Manquant", Notes)) %>%
spread(Notes, n) %>%
full_join(CRH_seance() %>% count(Pole, Service, Mois)) %>%
ungroup %>%
select(Pole, Service, Mois, RUM = n, CRHP, CRHA, Manquant) %>%
full_join(CRH_seance() %>% group_by(Pole, Service, Mois) %>% summarise(`Délai médian (j)` = median(Delai))) %>%
mutate(CRHA = ifelse(is.na(CRHA), integer(1), CRHA),
CRHP = ifelse(is.na(CRHP), integer(1), CRHP),
`% absents` = CRHA / RUM,
Pole = Pole %>% factor,
Mois = Mois %>% factor) %>%
datatable(rownames = F,
extensions = 'Buttons',
colnames = c("Pôle" = "Pole",
"Non renseigné" = "Manquant",
"#CRHA" = "CRHA",
"#CRHP" = "CRHP"),
filter = "top",
options = list(searching = T, paging = T)) %>%
formatPercentage(9)
```
```{r}
CRH_seance() %>%
count(Pole, Mois, Notes) %>%
mutate(Notes = ifelse(is.na(Notes), "Manquant", Notes)) %>%
spread(Notes, n) %>%
mutate(Manquant = ifelse(is.na(Manquant), integer(1), Manquant),
CRHA = ifelse(is.na(CRHA), integer(1), CRHA),
CRHP = ifelse(is.na(CRHP), integer(1), CRHP),
pourcent = CRHA / (CRHA + CRHP + Manquant)) %>%
ggplot(aes(x = Mois, y = pourcent, colour = Pole, group = Pole)) +
geom_line(stat = "identity") +
geom_point() +
theme(axis.text.x = element_text(angle = -45, hjust = 1)) +
ylab("Proportion de #CRHA") +
ggtitle("Évolution des proportions de #CRHA par pôle") -> p
ggplotly(p, tooltip = c("x", "y", "colour"))
```