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sudanCMAMdashboard.Rmd
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sudanCMAMdashboard.Rmd
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---
title: "Sudan CMAM Dashboard"
runtime: shiny
output:
flexdashboard::flex_dashboard:
orientation: rows
vertical_layout: scroll
#social: [ "twitter", "linkedin" ]
source_code: https://github.com/katilingban/sudanCMAM
theme: cerulean
---
```{r setup, include = FALSE}
if (!require(flexdashboard)) install.packages("flexdashboard")
if (!require(ggplot2)) install.packages("ggplot2")
if (!require(tidyr)) install.packages("tidyr")
if (!require(magrittr)) install.packages("magrittr")
if (!require(plotly)) install.packages("plotly")
if (!require(lubridate)) install.packages("lubridate")
if (!require(leaflet)) install.packages("leaflet")
if (!require(RColorBrewer)) install.packages("RColorBrewer")
if (!require(remotes)) install.packages("remotes")
if (!require(squeacr)) remotes::install_github(repo = "rapidsurveys/squeacr")
if (!require(sudan)) remotes::install_github(repo = "spatialworks/sudan")
library(flexdashboard)
library(ggplot2)
library(tidyr)
library(magrittr)
library(plotly)
library(lubridate)
library(leaflet)
library(RColorBrewer)
library(remotes)
library(squeacr)
library(sudan)
## Create Mapbox base layer objects for leaflet mapping
mapbox.satellite <- "https://api.mapbox.com/styles/v1/mapbox/satellite-streets-v10/tiles/256/{z}/{x}/{y}?access_token=pk.eyJ1IjoiZXJuZXN0Z3VldmFycmEiLCJhIjoiejRRLXlZdyJ9.sqS1zi0rDH5CIzvcn9SXSg"
mapbox.street <- "https://api.mapbox.com/styles/v1/mapbox/streets-v10/tiles/256/{z}/{x}/{y}?access_token=pk.eyJ1IjoiZXJuZXN0Z3VldmFycmEiLCJhIjoiejRRLXlZdyJ9.sqS1zi0rDH5CIzvcn9SXSg"
mapbox.dark <- "https://api.mapbox.com/styles/v1/mapbox/dark-v9/tiles/256/{z}/{x}/{y}?access_token=pk.eyJ1IjoiZXJuZXN0Z3VldmFycmEiLCJhIjoiejRRLXlZdyJ9.sqS1zi0rDH5CIzvcn9SXSg"
mapbox.light <- "https://api.mapbox.com/styles/v1/mapbox/light-v9/tiles/256/{z}/{x}/{y}?access_token=pk.eyJ1IjoiZXJuZXN0Z3VldmFycmEiLCJhIjoiejRRLXlZdyJ9.sqS1zi0rDH5CIzvcn9SXSg"
mapbox.moonlight <- "https://api.mapbox.com/styles/v1/ernestguevarra/cj3nban30001z2rpahc10c9ef/tiles/256/{z}/{x}/{y}?access_token=pk.eyJ1IjoiZXJuZXN0Z3VldmFycmEiLCJhIjoiejRRLXlZdyJ9.sqS1zi0rDH5CIzvcn9SXSg"
mapbox.northstar <- "https://api.mapbox.com/styles/v1/ernestguevarra/cj4ke832y4sng2spe2ds4fs55/tiles/256/{z}/{x}/{y}?access_token=pk.eyJ1IjoiZXJuZXN0Z3VldmFycmEiLCJhIjoiejRRLXlZdyJ9.sqS1zi0rDH5CIzvcn9SXSg"
mapbox.standard <- "https://api.mapbox.com/styles/v1/ernestguevarra/cj5di36jn0gxg2rphjn3yetpt/tiles/256/{z}/{x}/{y}?access_token=pk.eyJ1IjoiZXJuZXN0Z3VldmFycmEiLCJhIjoiejRRLXlZdyJ9.sqS1zi0rDH5CIzvcn9SXSg"
mapbox.decimal <- "https://api.mapbox.com/styles/v1/ernestguevarra/cj5ms1akt3pbi2smtcewsex9m/tiles/256/{z}/{x}/{y}?access_token=pk.eyJ1IjoiZXJuZXN0Z3VldmFycmEiLCJhIjoiejRRLXlZdyJ9.sqS1zi0rDH5CIzvcn9SXSg"
mapbox.terminal <- "https://api.mapbox.com/styles/v1/ernestguevarra/cj6g0tzbd30kc2sph2wyh666m/tiles/256/{z}/{x}/{y}?access_token=pk.eyJ1IjoiZXJuZXN0Z3VldmFycmEiLCJhIjoiejRRLXlZdyJ9.sqS1zi0rDH5CIzvcn9SXSg"
mapbox.leshine <- "https://api.mapbox.com/styles/v1/ernestguevarra/cjdlr8pvl0xiv2sqvq1evk1pl/tiles/256/{z}/{x}/{y}?access_token=pk.eyJ1IjoiZXJuZXN0Z3VldmFycmEiLCJhIjoiejRRLXlZdyJ9.sqS1zi0rDH5CIzvcn9SXSg"
## Load UNICEF palette
unicef_blue <- "#1CABE2"
unicef_darkgreen <- "#00833D"
unicef_green <- "#80BD41"
unicef_yellow <- "#FFC20E"
unicef_orange <- "#F26A21"
unicef_red <- "#E2231A"
unicef_darkred <- "#961A49"
unicef_purple <- "#6A1E74"
unicef_warmgrey <- "#D8D1C9"
unicef_coolgrey <- "#777779"
unicef_black <- "#2D2926"
unicef_darkblue <- "#374EA2"
## UNICEF ggplot theme settings
unicef_theme <- theme_bw() +
theme(text = element_text(family = "Helvetica"),
plot.title = element_text(size = 16, colour = unicef_darkblue),
plot.subtitle = element_text(size = 14, colour = unicef_blue),
panel.border = element_rect(colour = unicef_darkblue,
size = 0.5),
panel.grid.major = element_line(linetype = 0),
panel.grid.minor = element_line(linetype = 0),
strip.background = element_rect(colour = unicef_darkblue,
fill = unicef_darkblue),
strip.text = element_text(face = "bold", colour = "white", size = 10, vjust = 1),
legend.background = element_rect(colour = NA, fill = NA),
legend.key = element_rect(linetype = 0),
legend.key.size = unit(x = 8, units = "points"),
legend.spacing = unit(x = 4, units = "points"),
legend.text = element_text(size = 8),
legend.position = "top",
axis.line.x = element_line(colour = unicef_darkblue, size = 0.5),
axis.text.x = element_text(size = 10, colour = unicef_darkblue),
axis.title.x = element_text(size = 12, colour = unicef_blue),
axis.text.y = element_text(size = 10, colour = unicef_darkblue),
axis.title.y = element_text(size = 12, colour = unicef_blue),
axis.ticks = element_line(colour = unicef_darkblue, size = 0.25))
## Katilingban theme
katilingban_theme <- theme_bw() +
theme(panel.border = element_rect(colour = "gray50",
size = 0.5),
panel.grid.major = element_line(linetype = 1,
size = 0.1,
colour = "gray90"),
panel.grid.minor = element_line(linetype = 0),
strip.background = element_rect(colour = "gray50",
fill = "gray70"),
strip.text = element_text(colour = "white", size = 12),
legend.text = element_text(size = 12),
legend.key = element_rect(linetype = 0),
legend.key.size = unit(0.5, "cm"),
legend.position = "top",
axis.title = element_text(size = 12),
axis.text.x = element_text(size = 10),
axis.text.y = element_text(size = 10),
axis.ticks = element_line(colour = "gray50", size = 0.5))
legend.format <- function (prefix = "",
suffix = "",
between = " – ",
digits = 3,
big.mark = ",",
transform = identity) {
formatNum <- function(x) {
format(round(transform(x), digits), trim = TRUE,
scientific = FALSE, big.mark = big.mark)
}
function(type, ...) {
switch(type, numeric = (function(cuts) {
paste0(prefix, formatNum(cuts), suffix)
})(...), bin = (function(cuts) {
n = length(cuts)
paste0(prefix, formatNum(cuts[-n]), between, formatNum(cuts[-1]),
suffix)
})(...), quantile = (function(cuts, p) {
n = length(cuts)
p = paste0(round(p * 100), "%")
cuts = paste0(formatNum(cuts[-n]), between, formatNum(cuts[-1]), suffix)
})(...), factor = (function(cuts) {
paste0(prefix, as.character(transform(cuts)), suffix)
})(...))
}
}
```
Performance
================================================================================
Inputs {.sidebar}
--------------------------------------------------------------------------------
```{r}
div(style="display: inline-block;vertical-align:middle;",
h4("Filters"))
div(style="display: inline-block;vertical-align:top;",
actionLink(inputId = "filters_info",
label = "",
icon = icon(name = "info-sign", lib = "glyphicon")))
observeEvent(input$filters_info, {
showModal(
modalDialog(
HTML(
"<h4>Select state</h4>
<p>From the drop-down menu, select the state for which state-specific analysis
and/or visualisations are to be shown such as <strong>performance over
time from 2016-2019</strong>, <strong>admissions over time from 2016-2019</strong>
and <strong>defaulters over time from 2016-2019</strong>.</p>
<p>Selected state will also determine which localities are provided as
options in the <em>Select locality</em> settings and which localities
are presented in the locality level <strong>performance over time for a
specific year</strong>, <strong>admissions over time for a specific
year</strong>, <strong>defaulters over time for a specific year</strong>
and <strong>choropleth map of performance for a specific month and year</strong>.</p>
<p>Click on drop-down menu to see list of states and select state. Gazera
state is selected on dashboard startup.</p>
<br>
<h4>Select locality</h4>
<p>From the drop-down menu, select the locality for which locality-specific
analysis and/or visualisations are to be shown such as <strong>performance
over time from 2016-2019</strong>, <strong>admissions over time from
2016-2019</strong> and <strong>defaulters over time from 2016-2019</strong>.</p>
<p>The list of localities to choose from the drop-down menu depends on
the selected state. No locality is selected on dashboard startup.</p>
<br>
<h4>Select month</h4>
<p>From the drop-down menu, select the month for which selected performance
indicators are to be mapped.</p>
<p>Click on the drop-down menu to see the choices of months from January to
December. On dashboard startup, January is selected.</p>
<br>
<h4>Select year</h4>
<p>From the drop-down menu, select the year for which year-specific analysis
and/or visualisations are to be shown such as <strong>performance over
time at national, state and locality level</strong>, <strong>admissions
over time at national, state and locality level</strong>,
<strong>defaulters over time at national, state and locality level</strong>,
and <strong>choropleth map of performance by selected month and year</strong>.
<p>Click on the drop-down menu to see the choices of years from 2016 to
2019. On dashboard startup, year 2016 is selected.</p>
"
),
title = "Filters",
footer = modalButton("Close")
)
)
})
selectInput(inputId = "state_name",
label = "Select state",
choices = unique(monitoring$State),
selected = NULL)
output$select_locality <- renderUI({
req(input$state_name)
selectInput(inputId = "locality_name",
label = "Select locality",
choices = unique(monitoring$Locality[monitoring$State == input$state_name]),
selected = NULL)
})
uiOutput("select_locality")
selectInput(inputId = "chosen_month",
label = "Select month",
choices = c("January" = "Jan",
"February" = "Feb",
"March" = "Mar",
"April" = "Apr",
"May" = "May",
"June" = "Jun",
"July" = "Jul",
"August" = "Aug",
"September" = "Sep",
"October" = "Oct",
"November" = "Nov",
"December" = "Dec"),
selected = NULL)
selectInput(inputId = "chosen_year",
label = "Select year",
choices = unique(monitoring$Year),
selected = NULL)
hr()
```
```{r}
div(style="display: inline-block;vertical-align:middle;",
h4("Performance settings"))
div(style="display: inline-block;vertical-align:top;",
actionLink(inputId = "performance_settings_info",
label = "",
icon = icon(name = "info-sign", lib = "glyphicon")))
observeEvent(input$performance_settings_info, {
showModal(
modalDialog(
HTML(
"<p>These settings are used for the <strong>performance indicators</strong>
section of this dashboard.</p>
<br>
<h4>Show Sphere standards</h4>
<p>This checkbox indicates whether
<a href='https://handbook.spherestandards.org/en/sphere/#ch007' target='_blank'>Sphere standards</a>
for <strong> performance indicators</strong> should be shown on the plots.</p>
<p>On dashboard startup, the checkbox is unchecked and performance indicator
values for
<a href='https://handbook.spherestandards.org/en/sphere/#ch007' target='_blank'>Sphere standards</a>
are not shown on the plots.</p>
"
),
title = "Performance settings",
footer = modalButton("Close")
)
)
})
checkboxInput(inputId = "standards",
label = "Show Sphere standards",
value = FALSE)
hr()
```
```{r}
div(style="display: inline-block;vertical-align:middle;",
h4("Spatial settings"))
div(style="display: inline-block;vertical-align:top;",
actionLink(inputId = "spatial_settings_info",
label = "",
icon = icon(name = "info-sign", lib = "glyphicon")))
observeEvent(input$spatial_settings_info, {
showModal(
modalDialog(
HTML(
"<p>These settings are used for the <strong>spatial</strong> outputs of
this dashboard.</p>
<br>
<h4>Select indicator to map</h4>
<p>From the drop-down menu, select the performance indicator to be mapped.</p>
<p>Click on the drop-down menu to see the choices of performance indicators
from <strong>cured</strong>, <strong>defaulted</strong>,
<strong>dead</strong> or <strong>non-responder</strong>. On dashboard
startup, <strong>cured</strong> is selected.</p>
<br>
<h4>Select map background</h4>
<p>From the drop-down menu, select the map baselayer to use.</p>
<p>Click on the drop-down menu to see the choices of 10 map baselayers
from <a href='https://www.mapbox.com' target='_blank'>Mapbox</a>. On dashboard
startup, <strong>Terminal</strong> is selected.</p>
"
),
title = "Spatial settings",
footer = modalButton("Close")
)
)
})
selectInput(inputId = "indicator",
label = "Select indicator to map",
choices = c("Performance: Cured" = "cured_perc",
"Performance: Defaulted" = "defaulted_perc",
"Performance: Dead" = "dead_perc",
"Performance: Non-responder" = "nonresponder_perc"),
selected = NULL)
selectInput(inputId = "map_tiles",
label = "Select map background",
choices = c("Terminal" = "mapbox.terminal",
"Le Shine" = "mapbox.leshine",
"Satellite" = "mapbox.satellite",
"Street" = "mapbox.street",
"Dark" = "mapbox.dark",
"Light" = "mapbox.light",
"Moonlight" = "mapbox.moonlight",
"Northstar" = "mapbox.northstar",
"Standard" = "mapbox.standard",
"Decmial" = "mapbox.decimal"),
selected = "map.terminal")
hr()
```
Row {.tabset .tabset-fade}
--------------------------------------------------------------------------------
### National
```{r, fig.height = 5}
xOverall <- reactive({
aggregate(cbind(Cured, Death, Default, `Non-Responder`) ~ Month + Year,
data = monitoring, FUN = sum) %>%
calculate_performance() %>%
mutate(`Cured %` = cured_prop * 100,
`Defaulted %` = defaulter_prop * 100,
`Dead %` = dead_prop * 100,
`Non-responder %` = nr_prop * 100,
MonthYear = paste(Month, Year, sep = " "),
MonthYear = factor(x = MonthYear,
levels = c(paste(month.abb, "2016"),
paste(month.abb, "2017"),
paste(month.abb, "2018"),
paste(month.abb, "2019"))))
})
output$performanceOverall <- renderPlotly({
z <- xOverall() %>%
ggplot(mapping = aes(x = MonthYear, group = 1)) +
geom_line(mapping = aes(y = `Cured %`, colour = "Cured",
text = paste("Cured: ",
round(`Cured %`,
digits = 1), "%\n",
MonthYear, sep = "")),
size = 1) +
geom_line(mapping = aes(y = `Dead %`, colour = "Dead",
text = paste("Dead: ",
round(`Dead %`,
digits = 1), "%\n",
MonthYear, sep = "")),
size = 1) +
geom_line(mapping = aes(y = `Defaulted %`, colour = "Defaulted",
text = paste("Defaulted: ",
round(`Defaulted %`,
digits = 1), "%\n",
MonthYear, sep = "")),
size = 1) +
geom_line(mapping = aes(y = `Non-responder %`, colour = "Non-responder",
text = paste("Non-responder: ",
round(`Non-responder %`,
digits = 1), "%\n",
MonthYear, sep = "")),
alpha = 0.5, size = 1) +
scale_colour_manual(name = "",
values = c("Cured" = "darkgreen",
"Dead" = "black",
"Defaulted" = "red",
"Non-responder" = "gray50")) +
scale_y_continuous(limits = c(0, 100),
breaks = seq(from = 0, to = 100, by = 10)) +
labs(title = "National monthly performance over time - 2016 to 2019",
y = "%",
x = "")
sphere_cure <- geom_hline(yintercept = 75,
colour = "darkgreen",
linetype = 2, size = 0.25)
sphere_default <- geom_hline(yintercept = 15,
colour = "red",
linetype = 2, size = 0.25)
sphere_dead <- geom_hline(yintercept = 10,
colour = "black",
linetype = 2, size = 0.25)
## Assemble plot
if (input$standards) {
z <- z + sphere_cure + sphere_default + sphere_dead +
unicef_theme +
theme(axis.text.x = element_text(size = 8, angle = 90),
axis.text.y = element_text(size = 8))
} else {
z <- z +
unicef_theme +
theme(axis.text.x = element_text(size = 8, angle = 90),
axis.text.y = element_text(size = 8))
}
ggplotly(p = z, tooltip = "text") %>%
layout(legend = list(orientation = "h", y = 1.075))
})
plotlyOutput(outputId = "performanceOverall")
```
### State
```{r, fig.height = 5}
xStateOverall <- reactive({
req(input$state_name)
aggregate(cbind(Cured, Death, Default, `Non-Responder`) ~ State + Month + Year,
data = monitoring, FUN = sum) %>%
calculate_performance() %>%
filter(State == input$state_name) %>%
mutate(`Cured %` = cured_prop * 100,
`Defaulted %` = defaulter_prop * 100,
`Dead %` = dead_prop * 100,
`Non-responder %` = nr_prop * 100,
MonthYear = paste(Month, Year, sep = " "),
MonthYear = factor(x = MonthYear,
levels = c(paste(month.abb, "2016"),
paste(month.abb, "2017"),
paste(month.abb, "2018"),
paste(month.abb, "2019"))))
})
output$performanceStateOverall <- renderPlotly({
req(input$state_name)
z <- xStateOverall() %>%
ggplot(mapping = aes(x = MonthYear, group = State)) +
geom_line(mapping = aes(y = `Cured %`, colour = "Cured",
text = paste("Cured: ",
round(`Cured %`,
digits = 1), "%\n",
MonthYear, sep = "")),
size = 1) +
geom_line(mapping = aes(y = `Dead %`, colour = "Dead",
text = paste("Dead: ",
round(`Dead %`,
digits = 1), "%\n",
MonthYear, sep = "")),
size = 1) +
geom_line(mapping = aes(y = `Defaulted %`, colour = "Defaulted",
text = paste("Defaulted: ",
round(`Defaulted %`,
digits = 1), "%\n",
MonthYear, sep = "")),
size = 1) +
geom_line(mapping = aes(y = `Non-responder %`, colour = "Non-responder",
text = paste("Non-responder: ",
round(`Non-responder %`,
digits = 1), "%\n",
MonthYear, sep = "")),
alpha = 0.5, size = 1) +
scale_colour_manual(name = "",
values = c("Cured" = "darkgreen",
"Dead" = "black",
"Defaulted" = "red",
"Non-responder" = "gray50")) +
scale_y_continuous(limits = c(0, 100),
breaks = seq(from = 0, to = 100, by = 10)) +
labs(title = paste(input$state_name,
" State monthly performance over time - 2016 to 2019",
sep = ""),
y = "%",
x = "")
sphere_cure <- geom_hline(yintercept = 75,
colour = "darkgreen",
linetype = 2, size = 0.25)
sphere_default <- geom_hline(yintercept = 15,
colour = "red",
linetype = 2, size = 0.25)
sphere_dead <- geom_hline(yintercept = 10,
colour = "black",
linetype = 2, size = 0.25)
## Assemble plot
if (input$standards) {
z <- z + sphere_cure + sphere_default + sphere_dead +
unicef_theme +
theme(axis.text.x = element_text(size = 8, angle = 90),
axis.text.y = element_text(size = 8))
} else {
z <- z +
unicef_theme +
theme(axis.text.x = element_text(size = 8, angle = 90),
axis.text.y = element_text(size = 8))
}
ggplotly(p = z, tooltip = "text") %>%
layout(legend = list(orientation = "h", y = 1.075))
})
plotlyOutput(outputId = "performanceStateOverall")
```
### Locality
```{r, fig.height = 5}
xLocalityOverall <- reactive({
req(input$state_name, input$locality_name)
monitoring %>%
calculate_performance() %>%
filter(State == input$state_name,
Locality == input$locality_name) %>%
mutate(`Cured %` = cured_prop * 100,
`Defaulted %` = defaulter_prop * 100,
`Dead %` = dead_prop * 100,
`Non-responder %` = nr_prop * 100,
MonthYear = paste(Month, Year, sep = " "),
MonthYear = factor(x = MonthYear,
levels = c(paste(month.abb, "2016"),
paste(month.abb, "2017"),
paste(month.abb, "2018"),
paste(month.abb, "2019"))))
})
output$performanceLocalityOverall <- renderPlotly({
req(xLocalityOverall(), input$locality_name)
z <- xLocalityOverall() %>%
ggplot(mapping = aes(x = MonthYear, group = State)) +
geom_line(mapping = aes(y = `Cured %`, colour = "Cured",
text = paste("Cured: ",
round(`Cured %`,
digits = 1), "%\n",
MonthYear, sep = "")),
size = 1) +
geom_line(mapping = aes(y = `Dead %`, colour = "Dead",
text = paste("Dead: ",
round(`Dead %`,
digits = 1), "%\n",
MonthYear, sep = "")),
size = 1) +
geom_line(mapping = aes(y = `Defaulted %`, colour = "Defaulted",
text = paste("Defaulted: ",
round(`Defaulted %`,
digits = 1), "%\n",
MonthYear, sep = "")),
size = 1) +
geom_line(mapping = aes(y = `Non-responder %`, colour = "Non-responder",
text = paste("Non-responder: ",
round(`Non-responder %`,
digits = 1), "%\n",
MonthYear, sep = "")),
alpha = 0.5, size = 1) +
scale_colour_manual(name = "",
values = c("Cured" = "darkgreen",
"Dead" = "black",
"Defaulted" = "red",
"Non-responder" = "gray50")) +
scale_y_continuous(limits = c(0, 100),
breaks = seq(from = 0, to = 100, by = 10)) +
labs(title = paste(input$locality_name, " Locality, ",
input$state_name,
" State monthly performance over time - 2016 to 2019"),
y = "%",
x = "")
sphere_cure <- geom_hline(yintercept = 75,
colour = "darkgreen",
linetype = 2, size = 0.25)
sphere_default <- geom_hline(yintercept = 15,
colour = "red",
linetype = 2, size = 0.25)
sphere_dead <- geom_hline(yintercept = 10,
colour = "black",
linetype = 2, size = 0.25)
## Assemble plot
if (input$standards) {
z <- z + sphere_cure + sphere_default + sphere_dead +
unicef_theme +
theme(axis.text.x = element_text(size = 8, angle = 90),
axis.text.y = element_text(size = 8))
} else {
z <- z +
unicef_theme +
theme(axis.text.x = element_text(size = 8, angle = 90),
axis.text.y = element_text(size = 8))
}
ggplotly(p = z, tooltip = "text") %>%
layout(legend = list(orientation = "h", y = 1.075))
})
plotlyOutput(outputId = "performanceLocalityOverall")
```
Row {.tabset .tabset-fade}
--------------------------------------------------------------------------------
### National
```{r, fig.height = 8}
yearTotal <- reactive({
aggregate(cbind(Cured, Death, Default, `Non-Responder`) ~ Year,
data = monitoring, FUN = sum) %>%
calculate_performance() %>%
select(Year, cured_prop:nr_prop) %>%
mutate(Cured = cured_prop * 100,
Defaulted = defaulter_prop * 100,
Dead = dead_prop * 100,
`Non-responder` = nr_prop * 100) %>%
pivot_longer(cols = Cured:`Non-responder`,
names_to = "Indicator",
values_to = "Performance") %>%
mutate(Indicator = factor(x = Indicator,
levels = c("Cured", "Defaulted",
"Dead", "Non-responder")))
})
output$performanceYearOverall <- renderPlotly({
z <- yearTotal() %>%
ggplot(mapping = aes(x = Year, y = Performance, group = Year)) +
geom_col(mapping = aes(fill = Indicator),
width = 0.5,
alpha = 0.5) +
scale_fill_manual(name = "",
values = c("Cured" = "#1a9850",
"Defaulted" = "#d73027",
"Dead" = "black",
"Non-responder" = "gray80")) +
scale_y_continuous(limits = c(0, 100),
breaks = seq(from = 0, to = 100, by = 10)) +
labs(title = "National yearly performance over time - 2016 to 2019",
y = "%",
x = "")
## Assemble plot
z <- z + unicef_theme
ggplotly(p = z) %>%
layout(legend = list(orientation = "h", y = 1.04))
})
plotlyOutput(outputId = "performanceYearOverall")
```
### State
```{r, fig.height = 5}
yearStateTotal <- reactive({
req(input$state_name)
aggregate(cbind(Cured, Death, Default, `Non-Responder`) ~ Year + State,
data = monitoring, FUN = sum) %>%
calculate_performance() %>%
select(Year:State, cured_prop:nr_prop) %>%
mutate(Cured = cured_prop * 100,
Defaulted = defaulter_prop * 100,
Dead = dead_prop * 100,
`Non-responder` = nr_prop * 100) %>%
pivot_longer(cols = Cured:`Non-responder`,
names_to = "Indicator",
values_to = "Performance") %>%
mutate(Indicator = factor(x = Indicator,
levels = c("Cured", "Defaulted",
"Dead", "Non-responder")))
})
output$performanceYearStateOverall <- renderPlotly({
z <- yearStateTotal() %>%
ggplot(mapping = aes(x = Year, y = Performance, group = State)) +
geom_col(mapping = aes(fill = Indicator),
width = 0.5,
alpha = 0.5) +
scale_fill_manual(name = "",
values = c("Non-responder" = "gray80",
"Dead" = "black",
"Defaulted" = "#d73027",
"Cured" = "#1a9850")) +
scale_y_continuous(limits = c(0, 100),
breaks = seq(from = 0, to = 100, by = 10)) +
labs(title = "National yearly performance by state over time - 2016 to 2019",
y = "%",
x = "")
add_facets <- facet_wrap( ~ State, ncol = 6)
## Assemble plot
z <- z +
add_facets +
unicef_theme +
theme(axis.text.x = element_text(size = 8, angle = 90),
axis.text.y = element_text(size = 8))
ggplotly(p = z) %>%
layout(legend = list(orientation = "h", y = -0.055))
})
plotlyOutput(outputId = "performanceYearStateOverall")
```
### Locality
```{r, fig.height = 5}
yearLocalityTotal <- reactive({
req(input$state_name, input$locality_name)
aggregate(cbind(Cured, Death, Default, `Non-Responder`) ~ Year + State + Locality,
data = monitoring, FUN = sum) %>%
filter(State == input$state_name) %>%
calculate_performance() %>%
select(Year:Locality, cured_prop:nr_prop) %>%
mutate(Cured = cured_prop * 100,
Defaulted = defaulter_prop * 100,
Dead = dead_prop * 100,
`Non-responder` = nr_prop * 100) %>%
pivot_longer(cols = Cured:`Non-responder`,
names_to = "Indicator",
values_to = "Performance") %>%
mutate(Indicator = factor(x = Indicator,
levels = c("Cured", "Defaulted",
"Dead", "Non-responder")))
})
output$performanceYearLocalityOverall <- renderPlotly({
z <- yearLocalityTotal() %>%
ggplot(mapping = aes(x = Year, y = Performance, group = Locality)) +
geom_col(mapping = aes(fill = Indicator),
width = 0.5,
alpha = 0.5) +
scale_fill_manual(name = "",
values = c("Cured" = "#1a9850",
"Defaulted" = "#d73027",
"Dead" = "black",
"Non-responder" = "gray80")) +
scale_y_continuous(limits = c(0, 100),
breaks = seq(from = 0, to = 100, by = 10)) +
labs(title = "National yearly performance by locality over time - 2016 to 2019",
y = "%",
x = "")
add_facets <- facet_wrap( ~ Locality, ncol = 3)
## Assemble plot
z <- z +
add_facets +
unicef_theme +
theme(axis.text.x = element_text(size = 8, angle = 90),
axis.text.y = element_text(size = 8))
ggplotly(p = z) %>%
layout(legend = list(orientation = "h", y = -0.055))
})
plotlyOutput(outputId = "performanceYearLocalityOverall")
```
Row {.tabset .tabset-fade}
--------------------------------------------------------------------------------
### National
```{r, fig.height = 8}
x <- reactive({
aggregate(cbind(Cured, Death, Default, `Non-Responder`) ~ Month + Year,
data = monitoring, FUN = sum) %>%
calculate_performance() %>%
filter(Year == input$chosen_year) %>%
mutate(`Cured %` = cured_prop * 100,
`Defaulted %` = defaulter_prop * 100,
`Dead %` = dead_prop * 100,
`Non-responder %` = nr_prop * 100,
Month = factor(x = Month,
levels = month.abb))
})
output$performance <- renderPlotly({
z <- x() %>%
ggplot(mapping = aes(x = Month, group = Year)) +
geom_line(mapping = aes(y = `Cured %`, colour = "Cured",
text = paste("Cured: ",
round(`Cured %`, digits = 1),
"%\n", Month, " ", Year, sep = "")),
size = 1) +
geom_line(mapping = aes(y = `Dead %`, colour = "Dead",
text = paste("Dead: ",
round(`Dead %`, digits = 1),
"%\n", Month, " ", Year, sep = "")),
size = 1) +
geom_line(mapping = aes(y = `Defaulted %`, colour = "Defaulted",
text = paste("Defaulted: ",
round(`Defaulted %`, digits = 1),
"%\n", Month, " ", Year, sep = "")),
size = 1) +
geom_line(mapping = aes(y = `Non-responder %`, colour = "Non-responder",
text = paste("Non-responder: ",
round(`Non-responder %`, digits = 1),
"%\n", Month, " ", Year, sep = "")),
alpha = 0.5, size = 1) +
scale_colour_manual(name = "",
values = c("Cured" = "darkgreen",
"Dead" = "black",
"Defaulted" = "red",
"Non-responder" = "gray50")) +
scale_y_continuous(limits = c(0, 100),
breaks = seq(from = 0, to = 100, by = 10)) +
labs(title = paste("Performance over time - Year ", input$chosen_year, sep = ""),
y = "%", x = "")
sphere_cure <- geom_hline(yintercept = 75,
colour = "darkgreen",
linetype = 2, size = 0.25)
sphere_default <- geom_hline(yintercept = 15,
colour = "red",
linetype = 2, size = 0.25)
sphere_dead <- geom_hline(yintercept = 10,
colour = "black",
linetype = 2, size = 0.25)
## Assemble plot
if (input$standards) {
z <- z + sphere_cure + sphere_default + sphere_dead + unicef_theme
} else {
z <- z + unicef_theme
}
ggplotly(p = z, tooltip = "text") %>%
layout(legend = list(orientation = "h", y = 1.035))
})
plotlyOutput(outputId = "performance")
```
### State
```{r}
xstate <- reactive({
aggregate(cbind(Cured, Death, Default, `Non-Responder`) ~ State + Month + Year,
data = monitoring, FUN = sum) %>%
calculate_performance() %>%
filter(Year == input$chosen_year) %>%
mutate(`Cured %` = cured_prop * 100,
`Defaulted %` = defaulter_prop * 100,
`Dead %` = dead_prop * 100,
`Non-responder %` = nr_prop * 100,
Month = factor(x = Month,
levels = month.abb))
})
output$state_performance <- renderPlotly({
z <- xstate() %>%
ggplot(mapping = aes(x = Month, group = State)) +
geom_line(mapping = aes(y = `Cured %`, colour = "Cured",
text = paste("Cured: ",
round(`Cured %`, digits = 1),
"%\n", Month, " ", Year, sep = "")),
size = 1) +
geom_line(mapping = aes(y = `Dead %`, colour = "Dead",
text = paste("Dead: ",
round(`Dead %`, digits = 1),
"%\n", Month, " ", Year, sep = "")),
size = 1) +
geom_line(mapping = aes(y = `Defaulted %`, colour = "Defaulted",
text = paste("Defaulted: ",
round(`Defaulted %`, digits = 1),
"%\n", Month, " ", Year, sep = "")),
size = 1) +
geom_line(mapping = aes(y = `Non-responder %`, colour = "Non-responder",
text = paste("Non-responder: ",
round(`Non-responder %`, digits = 1),
"%\n", Month, " ", Year, sep = "")),
alpha = 0.5, size = 1) +
scale_colour_manual(name = "",
values = c("Cured" = "darkgreen",
"Dead" = "black",
"Defaulted" = "red",
"Non-responder" = "gray50")) +
scale_y_continuous(limits = c(0, 100),
breaks = seq(from = 0, to = 100, by = 10)) +
labs(title = paste("Performance over time by state - Year ", input$chosen_year, sep = ""),
y = "%", x = "")
sphere_cure <- geom_hline(yintercept = 75,
colour = "darkgreen",
linetype = 2, size = 0.25)
sphere_default <- geom_hline(yintercept = 15,
colour = "red",
linetype = 2, size = 0.25)
sphere_dead <- geom_hline(yintercept = 10,
colour = "black",
linetype = 2, size = 0.25)
add_facets <- facet_wrap( ~ State, ncol = 6)
if(input$standards) {
z <- z + sphere_cure + sphere_default + sphere_dead + add_facets
} else {
z <- z + add_facets
}
z <- z + unicef_theme +
theme(axis.text.x = element_text(size = 8, angle = 90),
axis.text.y = element_text(size = 8))
ggplotly(p = z, tooltip = "text") %>%
layout(legend = list(orientation = "h", y = -0.055))
})
plotlyOutput(outputId = "state_performance")
```
### Locality
```{r}
xlocality <- reactive({
monitoring %>%
calculate_performance() %>%
filter(Year == input$chosen_year,
State == input$state_name) %>%
mutate(`Cured %` = cured_prop * 100,
`Defaulted %` = defaulter_prop * 100,
`Dead %` = dead_prop * 100,
`Non-responder %` = nr_prop * 100,
Month = factor(x = Month,
levels = month.abb))
})
output$locality_performance <- renderPlotly({
z <- xlocality() %>%
ggplot(mapping = aes(x = Month, group = Locality)) +
geom_line(mapping = aes(y = `Cured %`, colour = "Cured",
text = paste("Cured: ",
round(`Cured %`, digits = 1),
"%\n", Month, " ", Year, sep = "")),
size = 1) +
geom_line(mapping = aes(y = `Dead %`, colour = "Dead",
text = paste("Dead: ",
round(`Dead %`, digits = 1),
"%\n", Month, " ", Year, sep = "")),
size = 1) +
geom_line(mapping = aes(y = `Defaulted %`, colour = "Defaulted",
text = paste("Defaulted: ",
round(`Defaulted %`, digits = 1),
"%\n", Month, " ", Year, sep = "")),
size = 1) +
geom_line(mapping = aes(y = `Non-responder %`, colour = "Non-responder",
text = paste("Non-responder: ",
round(`Non-responder %`, digits = 1),
"%\n", Month, " ", Year, sep = "")),
alpha = 0.5, size = 1) +
scale_colour_manual(name = "",
values = c("Cured" = "darkgreen",
"Dead" = "black",
"Defaulted" = "red",
"Non-responder" = "gray50")) +
scale_y_continuous(limits = c(0, 100),
breaks = seq(from = 0, to = 100, by = 10)) +
labs(title = paste("Performance over time in ", input$state_name,
" State by locality - Year ", input$chosen_year, sep = ""),
y = "%", x = "")
sphere_cure <- geom_hline(yintercept = 75,
colour = "darkgreen",
linetype = 2, size = 0.25)
sphere_default <- geom_hline(yintercept = 15,
colour = "red",
linetype = 2, size = 0.25)
sphere_dead <- geom_hline(yintercept = 10,
colour = "black",
linetype = 2, size = 0.25)
add_facets <- facet_wrap( ~ Locality, nrow = 3)