leaflet - Using R and leafleft for a map that changes over time -


i have data base organized neighborhoods city. data contains economic information month month several years. database looks (for reproducible example, 3 years)

> head(data , 4) neigh_id_shape  m1_y1  m2_y1 ....  m11_y3  m12_y3            id 1      7      6          -1       -3                       id 2      3     -1          -5        3                       id 3     -1      6           0       17                       id 4      0      3           1        2

more this, have shapefile object of city , neighboords. "neigh_id_shape" variable in data match variable. shapefile, can plot customized map using leafleft

> n_shape <- readshapespatial("path\\my_shape.shp")   leaflet()  %>% addtiles() %>% setview(lng = center_city_long , lat= center_city_lat ,zoom=11) %>% addpolygons( data= n_shape , weight= 1  )

so, dynamic map (with play button) visualises change on time (along months variables). furthermore, construct 2 scales of colors values of months: red scale , blue scale negative , positive values, respectively.

new

according 1 comemnt, tryed this... not works (see picture after script)

    library(htmlwidgets)     library(htmltools)     library(leaflet)     #install.packages("geojsonio")     library(geojsonio)      llat<- c(-22.973897, -22.972892,-22.971588, 22.972270,-22.974700,-22.969869,-22.970847,-22.968832,-22.974660,-22.975243)      llong<- c( -43.185296,-43.187338,-43.185675,-43.185869,-43.190858,-43.186791, -43.188980,-43.187092,-43.193239,-43.193486)       #build data.frame 10 obs + 3 cols power <- data.frame(   "latitude" = llat,#c(33.515556, 38.060556, 47.903056, 49.71, 49.041667, 31.934167, 54.140586, 54.140586, 48.494444, 48.494444),   "longitude" = llong,#c(129.837222, -77.789444, 7.563056, 8.415278, 9.175, -82.343889, 13.664422, 13.664422, 17.681944, 17.681944),   "start" = do.call(     "as.date",     list(       x = c("1jan1960", "2jan1960", "31mar1960", "30jul1960", "1jan1961", "2jan1961", "31mar1961", "30jul1961" , "1jan1962", "2jan1962" ),       format = "%d%b%y"     )   ) )  # set start same end #  adjust power$end <- power$start + 30   # use geojsonio convert our data.frame #  geojson timeline expects power_geo <- geojson_json(power[,c(1,2)],lat="latitude",lon="longitude", pretty = t)  # create leaflet map on build leaf <- leaflet() %>%   addtiles()  # add leaflet-timeline dependency #  js , css leaf$dependencies[[length(leaf$dependencies)+1]] <- htmldependency(   name = "leaflet-timeline",   version = "1.0.0",   src = c("href" = "http://skeate.github.io/leaflet.timeline/"),   script = "javascripts/leaflet.timeline.js",   stylesheet = "stylesheets/leaflet.timeline.css" )  # use new onrender in htmlwidgets run #  code once our leaflet map rendered #  did not spend time perfecting leaflet-timeline #  options leaf %>%   setview(lng = -43.187574 , lat= -22.971875,zoom=14) %>%   onrender(sprintf(     '     function(el,x){     var power_data = %s;      var timelinecontrol = l.timelineslidercontrol({     formatoutput: function(date) {     return new date(date).tostring();     }     });      var timeline = l.timeline(power_data, {     pointtolayer: function(data, latlng){     var hue_min = 120;     var hue_max = 0;     var hue = hue_min;     return l.circlemarker(latlng, {     radius: 10,     color: "hsl("+hue+", 100%%, 50%%)",     fillcolor: "hsl("+hue+", 100%%, 50%%)"     });     },     steps: 1000,     duration: 10000,     showticks: true     });     timelinecontrol.addto(htmlwidgets.find(".leaflet").getmap());     timelinecontrol.addtimelines(timeline);     timeline.addto(htmlwidgets.find(".leaflet").getmap());     }     ',         power_geo     ))

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