Lab III

R Spatial Assignment 3: COVID-19 Cases & Black Population in New York City

# Read in the COVID ACS shapefile
sf::st_read("./acsPopByZip.shp", quiet = TRUE) -> acscovid

# Use the color brewer to create a color palette, 8 colors from blue to green
# for the 8 breaks
RColorBrewer::brewer.pal(8, "BuGn") -> colorpal

Plot using plot.sf method

# Apply the new palette and also use a log transformation to the field
plot(acscovid["Positiv"],
     main = "Number of Positive COVID-19 Cases in NYC",
     nbreaks = 8,
     breaks = "jenks",
     pal = colorpal,
     border = NA,
     graticule = st_crs(4326),
     axes = TRUE,
     logz = TRUE)

# Use the color brewer to create a color palette, 8 colors from orange to red
# for the 8 breaks
RColorBrewer::brewer.pal(8, "OrRd") -> colorpalette

# Remove missing values from blackPp column
acscovid[!is.na(acscovid$blackPp),] -> acscovid

# Apply the new palette and also use a log transformation to the field
plot(acscovid["blackPp"],
     main = "Black Population in NYC",
     nbreaks = 8,
     breaks = "jenks",
     pal = colorpalette,
     border = NA,
     graticule = st_crs(4326),
     axes = TRUE,
     logz = TRUE)

## Warning in classInt::classIntervals(v0, min(nbreaks, n.unq), breaks, warnSmallN
## = FALSE): var has infinite values, omitted in finding classes

acscovid %>% sf::st_centroid() %>%
  dplyr::filter(Positiv > 1800) %>%
  sf::st_coordinates() -> labelCoordsCovid

## Warning in st_centroid.sf(.): st_centroid assumes attributes are constant over
## geometries of x

acscovid %>% sf::st_centroid() %>%
  dplyr::filter(Positiv > 1800) %>%
  dplyr::mutate(x = labelCoordsCovid[,1], y = labelCoordsCovid[,2]) -> labelDataCovid

## Warning in st_centroid.sf(.): st_centroid assumes attributes are constant over
## geometries of x

Using ggplot

ggplot(acscovid) +
  geom_sf(aes(fill = Positiv)) +
  geom_sf_label(data = labelDataCovid,
                aes(x = x, y = y, label = PO_NAME %>% as.character()),
                label.size = .09,
                size = 3,
                segment.color = rgb(0.8,0.8,0.9),
                segment.size = 0.8) +
  scale_fill_continuous(type = 'viridis') +
  labs(x = 'Longitude', y = 'Latitude',
       title = 'COVID-19 Cases in NYC',
       caption = 'Data Source: New York City Department of Health') -> COVIDCases

## Warning: Ignoring unknown parameters: segment.colour, segment.size

COVIDCases

acscovid %>% sf::st_centroid() %>%
  dplyr::filter(blackPp > 45644) %>%
  sf::st_coordinates() -> labelCoordsBlack

## Warning in st_centroid.sf(.): st_centroid assumes attributes are constant over
## geometries of x

acscovid %>% sf::st_centroid() %>%
  dplyr::filter(blackPp > 45644) %>%
  dplyr::mutate(x = labelCoordsBlack[,1], y = labelCoordsBlack[,2]) -> labelDataBlack

## Warning in st_centroid.sf(.): st_centroid assumes attributes are constant over
## geometries of x

ggplot(acscovid) +
  geom_sf(aes(fill = blackPp)) +
  geom_sf_label(data = labelDataBlack,
                aes(x = x, y = y, label = PO_NAME %>% as.character()),
                label.size = .09,
                size = 3,
                segment.color = rgb(0.8,0.8,0.9),
                segment.size = 0.8) +
  scale_fill_continuous(type = 'viridis') +
  labs(x = 'Longitude', y = 'Latitude',
       title = 'Black Population in NYC',
       caption = 'Data Source: New York City Department of Health') -> BlackPop

## Warning: Ignoring unknown parameters: segment.colour, segment.size

BlackPop

grid.arrange(COVIDCases, BlackPop, ncol=2)

st_transform(acscovid, 4326) -> NewYork_WGS84

leaflet(NewYork_WGS84) %>%
  addPolygons()

paste0("Zip Code:", NewYork_WGS84$ZIPCODE) -> p_tip
paste0("<strong> Zip Code </strong>",
       NewYork_WGS84$ZIPCODE,
       " <br/>",
       "<strong> Black Population: </strong>",
       NewYork_WGS84$blackPp,
       sep="") -> p_popup
paste0("<strong> Zip Code </strong>",
       NewYork_WGS84$ZIPCODE,
       " <br/>",
       "<strong> COVID-19 Cases: </strong>",
       NewYork_WGS84$Positiv,
       sep="") -> covid_popup

classIntervals(acscovid$blackPp, n = 7, style = "quantile") -> breaks_qt_black
classIntervals(acscovid$Positiv, n = 7, style = "quantile") -> breaks_qt_covid

leaflet::highlightOptions(opacity = 1.0, fillColor = 'black') -> polyHighlightOption
leaflet::labelOptions(opacity = 0.6) -> polyLabelOption

leaflet(NewYork_WGS84) %>%
  addPolygons(
    stroke = FALSE, # remove polygon borders
    fillColor = ~color_pal(blackPp), # set fill color with function from above and value
    fillOpacity = 0.8, smoothFactor = 0.5, # make it nicer
    popup = p_popup,
    group = "New York City",
    label = p_tip,
    highlightOptions = polyHighlightOption,
    labelOptions = polyLabelOption) %>% # add popup
  addTiles(group = "OSM") %>%
  addProviderTiles(providers$CartoDB.Positron) %>%
  addLegend("bottomright",  # location
            colors = brewer.pal(7, "BuGn"), 
            labels = paste0("up to ", format(breaks_qt_black$brks[-1], digits = 2)),
          title = 'Black Population in New York City by Neighborhood') %>% # legend title
  addLayersControl(baseGroups = c("OSM", "Carto"), 
                   overlayGroups = c("New York City"))

leaflet(NewYork_WGS84) %>%
  addPolygons(
    stroke = FALSE, # remove polygon borders
    fillColor = ~color_pal(Positiv), # set fill color with function from above and value
    fillOpacity = 0.8, smoothFactor = 0.5, # make it nicer
    popup = covid_popup, # add popup
    group = "New York City",
    label = p_tip,
    highlightOptions = polyHighlightOption,
    labelOptions = polyLabelOption) %>% # add popup
  addTiles(group = "OSM") %>%
  addProviderTiles(providers$CartoDB.Positron) %>%
  addLegend("bottomright",  # location
            colors = brewer.pal(7, "YlOrRd"), 
            labels = paste0("up to ", format(breaks_qt_covid$brks[-1], digits = 2)),
            title = 'COVID-19 Cases in New York City by Neighborhood') %>% # legend title
  addLayersControl(baseGroups = c("OSM", "Carto"), 
                   overlayGroups = c("New York City")) -> htmlMap

htmlMap