--- 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")) ```