UK Mobility

library(tidyverse)

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library(lubridate)

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library(COVID19)
library(sf)

## Linking to GEOS 3.5.1, GDAL 2.1.2, PROJ 4.9.3

library(mapview)
#gmr <- "https://www.gstatic.com/covid19/mobility/Global_Mobility_Report.csv"
#d  <- covid19(country="GBR",gmr = gmr, level=3)
#save(d,file=sprintf("UK_data%s_l3.rda",Sys.Date()))
load(sprintf("UK_data%s_l3.rda",Sys.Date()))
shp<-st_read("england_ct_2011.shp")

## Reading layer `england_ct_2011' from data source `/home/rstudio/webpages/epidemiology/UK_mobility/england_ct_2011.shp' using driver `ESRI Shapefile'
## Simple feature collection with 152 features and 3 fields
## geometry type:  MULTIPOLYGON
## dimension:      XY
## bbox:           xmin: 82643.6 ymin: 5333.602 xmax: 655989 ymax: 657599.5
## epsg (SRID):    NA
## proj4string:    +proj=tmerc +lat_0=49 +lon_0=-2 +k=0.9996012717 +x_0=400000 +y_0=-100000 +datum=OSGB36 +units=m +no_defs

shp$code<-aqm::clean(shp$code)

dd<-(data.frame(name=d$administrative_area_level_3,date=d$date,code=as.character(d$key),work=d$workplaces_percent_change_from_baseline))

library(plotly)

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ggplot(dd,aes(x=date,y=work,group=name)) +geom_point() ->g1

# dd %>% filter(date==(max(date)-14)) ->dd
# dim(dd)
# dd<-merge(shp,dd)
# dim(dd)
# mapview(dd)
aqm::dt(dd)

## Warning in instance$preRenderHook(instance): It seems your data is too
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