library(leaflet)##January 1, 2021
#Get Data This map visualizes COVID-19 deaths in the U.S. Data is taken from:
https://coronavirus-resources.esri.com/datasets/628578697fb24d8ea4c32fa0c5ae1843_0
df <- read.csv("COVID-19_Cases_US.csv")
head(df)## ï..X Y OBJECTID Province_State Country_Region
## 1 -86.64408 32.53953 1 Alabama US
## 2 -87.72207 30.72775 2 Alabama US
## 3 -85.38713 31.86826 3 Alabama US
## 4 -87.12511 32.99642 4 Alabama US
## 5 -86.56791 33.98211 5 Alabama US
## 6 -85.71266 32.10031 6 Alabama US
## Last_Update Lat Long_ Confirmed Recovered Deaths Active
## 1 2021/01/08 14:22:38+00 32.53953 -86.64408 4705 0 50 4655
## 2 2021/01/08 14:22:38+00 30.72775 -87.72207 14845 0 171 14674
## 3 2021/01/08 14:22:38+00 31.86826 -85.38713 1614 0 35 1579
## 4 2021/01/08 14:22:38+00 32.99642 -87.12511 1981 0 48 1933
## 5 2021/01/08 14:22:38+00 33.98211 -86.56791 4957 0 72 4885
## 6 2021/01/08 14:22:38+00 32.10031 -85.71266 927 0 22 905
## Admin2 FIPS Combined_Key Incident_Rate People_Tested
## 1 Autauga 1001 Autauga, Alabama, US 8421.486 NA
## 2 Baldwin 1003 Baldwin, Alabama, US 6649.973 NA
## 3 Barbour 1005 Barbour, Alabama, US 6538.119 NA
## 4 Bibb 1007 Bibb, Alabama, US 8846.119 NA
## 5 Blount 1009 Blount, Alabama, US 8572.269 NA
## 6 Bullock 1011 Bullock, Alabama, US 9177.309 NA
## People_Hospitalized UID ISO3
## 1 NA 84001001 USA
## 2 NA 84001003 USA
## 3 NA 84001005 USA
## 4 NA 84001007 USA
## 5 NA 84001009 USA
## 6 NA 84001011 USAdf %>%
leaflet() %>%
addTiles( ) %>%
addCircleMarkers(lng = ~ Long_, lat = ~ Lat, clusterOptions = markerClusterOptions(), color = ~Province_State)## Warning in validateCoords(lng, lat, funcName): Data contains 35 rows with either
## missing or invalid lat/lon values and will be ignored