Given the following example data
mydata <- data.frame(
lat = c(21.05939, 21.04305, 21.05977, 21.04336, 21.04434),
lng = c(92.22692 ,92.23357 ,92.22733 ,92.23361 ,92.23478),
X1 = c("sometimes", "always", "never", "often", "rarely")
)
And the following Leaflet plot:
pal1 <- c("#003366","#00ced1", "#ffd700","#ffa500","#ff1a1a")
color <- colorFactor(pal1, domain = mydata$X1)
leaflet(data = mydata) %>%
addTiles() %>%
addCircleMarkers(lng = mydata$lng,
lat = mydata$lat,
color = ~color(mydata$X1)) %>%
addLegend("topright",
pal=color,
values=mydata$X1,
opacity = 1)
How can I manipulate the order of labels in the legend so that they are:
always,
often,
sometimes,
rarely,
never
I have attempted to specify the levels argument in colorFactor() and have also attempted the same with the values argument in addLegend However, the legend still resorts to alphabetical order of the items.
NVM I think I figured it out.
I first specified a sort order by:
sort_val = factor(mydata$X1, levels = c('always',
'often',
'sometimes',
'rarely',
'never'))
I then passed sort_val to the values argument in addlegend()
addLegend("topright",
pal=color,
values=sort_val,
opacity = 1)
I think this is correct unless anyone can suggest an alternative?
Related
I have a shapefile with polylines of routes in different years. Here is an example data shapefile with routes in the year 2000 and year 2013. I would like the map to show the older routes at the top and more recent routes at the bottom. I've had a look at the addMapPane function but not sure how to apply it for a vector in the same file. Here is my code so far:
sample_palette <- leaflet::colorFactor(palette = rainbow(2),
domain = data_sample$Year)
sample_plot <- leaflet(data_sample) %>%
addProviderTiles("CartoDB.Positron") %>%
addPolylines(color = ~sample_palette(Year),
opacity = 1) %>%
leaflet::addLegend(values = ~Year,
opacity = 1,
pal = sample_palette,
title = "Routes")
sample_plot
I am using leaflet and R.
Please find one possible solution to get the older routes on top of recent routes: just need to change the order of rows in data_sample
Code
library(sf)
library(leaflet)
data_sample <- st_read("ADD YOUR PATH HERE")
# Order 'data_sample' rows in decreasing order of 'Year'
data_sample <- data_sample %>%
arrange(., desc(Year))
# Choose colors
sample_palette <- leaflet::colorFactor(palette = rainbow(2),
domain = data_sample$Year)
# Build the map
sample_plot <- leaflet(data_sample) %>%
addProviderTiles("CartoDB.Positron") %>%
addPolylines(color = ~sample_palette(Year),
opacity = 1) %>%
leaflet::addLegend(values = ~Year,
opacity = 1,
pal = sample_palette,
title = "Routes")
Visualization
sample_plot
I'm trying to add separate images to popups so that as you click on each location, an image specific to that place/popup appears. I've figured out how to get one image in, but it applies to all of the popups on the map instead of just one. I have been trying to use the package leafpop for this, but I can't really figure out how to make it work. Even if I just use one image, nothing appears on the map.
This is what my code looks like for it:
library(leaflet)
library(leafpop)
img = system.file("file/image_name.jpg", package = "jpg")
leaflet(map) %>%
addTiles() %>%
addCircleMarkers(label = map#data$name,
weight = 2,
color = "grey",
fillColor = "red",
fillOpacity = 0.7)%>%
addPopupImages(img, group = "map")
I know there's some bits in there that I'm not quite doing right. At this point, I just want to know if it's even possible to do this the way I'm envisioning. Any help is appreciated.
The images need to be in a vector of the same length as the points passed to leaflet. Here is a reproducible example you can copy paste that will get you started:
library(tidyverse)
library(sf)
library(leaflet)
library(leafpop)
pts <- tibble(x = runif(10, 175, 176),
y = runif(10, -38, -37)) %>%
st_as_sf(coords = c("x", "y"), crs = 4326)
img <- glue::glue("https://github.com/IQAndreas/sample-images/blob/gh-pages/100-100-color/{11:20}.jpg?raw=true")
pts$img <- img
leaflet() %>%
addTiles() %>%
addCircleMarkers(data = pts, group = "pts") %>%
addPopupImages(pts$img, group = "pts")
Figured it out, with the help of Rich Pauloo! This is the code I ended up using the get local image files. It's a little clunky, but it worked out for me:
data_name <- readOGR("data/map_file.kml")
data_name2 <- data.frame(data_name)
pts <- st_as_sf(data.frame(data_name2),
coords = c("coords.x1", "coords.x2"), crs = 4326)
img <- c("images/picture_name.jpg") ##did this for every image I wanted to use, in the order
##that matched up with the data points I wanted them associated with.
pts$img <- img
leaflet() %>%
addTiles() %>%
addCircleMarkers(data = pts, group = "pts") %>%
addPopupImages(pts$img, group = "pts", width = 300)
Sorry if my conventions for writing out code are not quite right for the website. I just wanted to keep things generic and not include any of my file names or anything.
Anyone created a leaflet map in Code Workbook using r-Leaflet? I have a functioning script that runs (also double checked in R) but how do I get it to visualise and then use in a Report etc. I have tried various tweaks on what may get it to run but no success - any ideas
leaflet_map <- function(map_data) {
library(leaflet)
data<-map_data
# first cut the continuous variable into bins
# these bins are now factors
data$Fill_rateLvl <- cut(data$Fill_rate,
c(0,.5,0.6,0.7,0.8,0.9,1), include.lowest = T,
labels = c('<50%', '50-60%', '60-70%', '70-80%', '80-90%','90-100%'))
# then assign a palette to this using colorFactor
# in this case it goes from red for the smaller values to yellow and green
# standard stoplight for bad, good, and best
FillCol <- colorFactor(palette = 'RdYlGn', data$Fill_rateLvl)
m<-leaflet() %>%
addTiles() %>%
addProviderTiles(providers$CartoDB.Positron)%>%
setView(lng = -0, lat = 50, zoom = 8) %>%
addCircleMarkers(data = data, lat = ~lat, lng = ~long,
color = ~FillCol(Fill_rateLvl), popup = data$Lead_employer,
radius = ~sqrt(Fill_rate*50), group = 'Fill rate') %>%
addLegend('bottomright', pal = FillCol, values = data$Fill_rateLvl,
title = 'Fill rate for next two weeks',
opacity = 1)
return(NULL)
}
I am not familiar with R in code workbook, but it sounds to me that you need to materialize your leaflet map as a dataset and then consume it in some sort of map compatible UI.
For example slate has a map widget which is backed by leaflets. You can find documentation and examples for it in https://www.palantir.com/docs/foundry/slate/widgets-map/
I am trying the create a plotly gauge graph for a flexdashboard which should change value depending on the chosen filter in crosstalk::filter_select().
I have tried and tried but cannot get the filter to work. This is an example with mtcars of what I am trying to do. I noticed that if the SharedData object has only one value, then it works, but otherwise plotly does not show any data.
mtcars_data <- tibble::rownames_to_column(mtcars, "Car")
shared_mtcars <- SharedData$new(mtcars_data)
row1 <- bscols(filter_select("Car", "Car", shared_mtcars, ~Car, multiple = F)
)
fig <- plot_ly(shared_mtcars,
domain = list(x = c(0, 1), y = c(0, 1)),
value = ~mpg,
title = list(text = "MPG"),
type = "indicator",
mode = "gauge+number")
bscols(row1, fig, widths = 12)
This code results in a graph with no data. If I subset mtcars_data to take the first row or the first two rows (which happen to have the same value for mpg) then it works. If I subset rows 1 and 3, it doesn't.
I might be missing something - in that case would really appreciate any feedback.
I am referring to the choropleth tutorial for Leaflet (https://rstudio.github.io/leaflet/choropleths.html) and modifying it for Shiny. I have different columns that I want to be able to use depending on what the user selects. The problem I encounter has to do with this part:
pal <- colorBin("YlOrRd", domain = states$density, bins = bins)
m %>% addPolygons(
fillColor = ~pal(density),
weight = 2,
opacity = 1,
color = "white",
dashArray = "3",
fillOpacity = 0.7)
Specifically, I want to be able to replace the density column be a column that I can get from a button in Shiny (assume the columns are called a and b and that I get them from the name_button object). I create the col_name function to enclose this choice:
col_name <- reactive({
name <- switch(input$name_button, "A" = "a", "B" = "b" )
name})
Then I can modify the pal <- ... line as follows (see R how use a string variable to select a data frame column using $ notation):
pal <- colorBin("YlOrRd", domain = states[[col_name()]], bins = bins)
However, I am not sure how to change the fillColor = ~pal(density), line because density is the name of a column. I have tried
fillColor = ~pal([[col_name]])
but this doesn't work. What can I do?
Also, what is the function of the tilde ~ in ~pal(...)?