task 2:
nyczipcodes_sf <- st_read("./R-Spatial_I_Lab/ZIP_CODE_040114/ZIP_CODE_040114.shp")
## Reading layer `ZIP_CODE_040114' from data source
## `/Users/mariyatrofymova/Desktop/Rspatial Study/R-Spatial_I_Lab/ZIP_CODE_040114/ZIP_CODE_040114.shp'
## using driver `ESRI Shapefile'
## Simple feature collection with 263 features and 12 fields
## Geometry type: POLYGON
## Dimension: XY
## Bounding box: xmin: 913129 ymin: 120020.9 xmax: 1067494 ymax: 272710.9
## Projected CRS: NAD83 / New York Long Island (ftUS)
str(nyczipcodes_sf)
## Classes 'sf' and 'data.frame': 263 obs. of 13 variables:
## $ ZIPCODE : chr "11436" "11213" "11212" "11225" ...
## $ BLDGZIP : chr "0" "0" "0" "0" ...
## $ PO_NAME : chr "Jamaica" "Brooklyn" "Brooklyn" "Brooklyn" ...
## $ POPULATION: num 18681 62426 83866 56527 72280 ...
## $ AREA : num 22699295 29631004 41972104 23698630 36868799 ...
## $ STATE : chr "NY" "NY" "NY" "NY" ...
## $ COUNTY : chr "Queens" "Kings" "Kings" "Kings" ...
## $ ST_FIPS : chr "36" "36" "36" "36" ...
## $ CTY_FIPS : chr "081" "047" "047" "047" ...
## $ URL : chr "http://www.usps.com/" "http://www.usps.com/" "http://www.usps.com/" "http://www.usps.com/" ...
## $ SHAPE_AREA: num 0 0 0 0 0 0 0 0 0 0 ...
## $ SHAPE_LEN : num 0 0 0 0 0 0 0 0 0 0 ...
## $ geometry :sfc_POLYGON of length 263; first list element: List of 1
## ..$ : num [1:159, 1:2] 1038098 1038142 1038171 1038280 1038521 ...
## ..- attr(*, "class")= chr [1:3] "XY" "POLYGON" "sfg"
## - attr(*, "sf_column")= chr "geometry"
## - attr(*, "agr")= Factor w/ 3 levels "constant","aggregate",..: NA NA NA NA NA NA NA NA NA NA ...
## ..- attr(*, "names")= chr [1:12] "ZIPCODE" "BLDGZIP" "PO_NAME" "POPULATION" ...
nyc_covid <- readr::read_csv("R-Spatial_II_Lab/tests-by-zcta_2021_04_23.csv", lazy = FALSE)
## Rows: 177 Columns: 13
## ── Column specification ────────────────────────────────────────────────────────
## Delimiter: ","
## chr (3): NEIGHBORHOOD_NAME, BOROUGH_GROUP, label
## dbl (10): MODIFIED_ZCTA, lat, lon, COVID_CASE_COUNT, COVID_CASE_RATE, POP_DE...
##
## ℹ Use `spec()` to retrieve the full column specification for this data.
## ℹ Specify the column types or set `show_col_types = FALSE` to quiet this message.
str(nyc_covid)
## spc_tbl_ [177 × 13] (S3: spec_tbl_df/tbl_df/tbl/data.frame)
## $ MODIFIED_ZCTA : num [1:177] 10001 10002 10003 10004 10005 ...
## $ NEIGHBORHOOD_NAME: chr [1:177] "Chelsea/NoMad/West Chelsea" "Chinatown/Lower East Side" "East Village/Gramercy/Greenwich Village" "Financial District" ...
## $ BOROUGH_GROUP : chr [1:177] "Manhattan" "Manhattan" "Manhattan" "Manhattan" ...
## $ label : chr [1:177] "10001, 10118" "10002" "10003" "10004" ...
## $ lat : num [1:177] 40.8 40.7 40.7 40.7 40.7 ...
## $ lon : num [1:177] -74 -74 -74 -74 -74 ...
## $ COVID_CASE_COUNT : num [1:177] 1542 5902 2803 247 413 ...
## $ COVID_CASE_RATE : num [1:177] 5584 7836 5193 8311 4716 ...
## $ POP_DENOMINATOR : num [1:177] 27613 75323 53978 2972 8757 ...
## $ COVID_DEATH_COUNT: num [1:177] 35 264 48 2 0 1 4 118 37 62 ...
## $ COVID_DEATH_RATE : num [1:177] 126.8 350.5 88.9 67.3 0 ...
## $ PERCENT_POSITIVE : num [1:177] 7.86 12.63 6.93 6.92 6.72 ...
## $ TOTAL_COVID_TESTS: num [1:177] 20158 48197 41076 3599 6102 ...
## - attr(*, "spec")=
## .. cols(
## .. MODIFIED_ZCTA = col_double(),
## .. NEIGHBORHOOD_NAME = col_character(),
## .. BOROUGH_GROUP = col_character(),
## .. label = col_character(),
## .. lat = col_double(),
## .. lon = col_double(),
## .. COVID_CASE_COUNT = col_double(),
## .. COVID_CASE_RATE = col_double(),
## .. POP_DENOMINATOR = col_double(),
## .. COVID_DEATH_COUNT = col_double(),
## .. COVID_DEATH_RATE = col_double(),
## .. PERCENT_POSITIVE = col_double(),
## .. TOTAL_COVID_TESTS = col_double()
## .. )
## - attr(*, "problems")=<externalptr>
nyc_sf_merged <- base::merge(nyczipcodes_sf, nyc_covid, by.x = "ZIPCODE", by.y = "MODIFIED_ZCTA")
names(nyc_sf_merged)
## [1] "ZIPCODE" "BLDGZIP" "PO_NAME"
## [4] "POPULATION" "AREA" "STATE"
## [7] "COUNTY" "ST_FIPS" "CTY_FIPS"
## [10] "URL" "SHAPE_AREA" "SHAPE_LEN"
## [13] "NEIGHBORHOOD_NAME" "BOROUGH_GROUP" "label"
## [16] "lat" "lon" "COVID_CASE_COUNT"
## [19] "COVID_CASE_RATE" "POP_DENOMINATOR" "COVID_DEATH_COUNT"
## [22] "COVID_DEATH_RATE" "PERCENT_POSITIVE" "TOTAL_COVID_TESTS"
## [25] "geometry"
nycfoodstores_sf <- st_read("./R-Spatial_II_Lab/nycFoodStore.shp")
## Reading layer `nycFoodStore' from data source
## `/Users/mariyatrofymova/Desktop/Rspatial Study/R-Spatial_II_Lab/nycFoodStore.shp'
## using driver `ESRI Shapefile'
## Simple feature collection with 11300 features and 16 fields
## Geometry type: POINT
## Dimension: XY
## Bounding box: xmin: -74.2484 ymin: 40.50782 xmax: -73.67061 ymax: 40.91008
## Geodetic CRS: WGS 84
str(nycfoodstores_sf)
## Classes 'sf' and 'data.frame': 11300 obs. of 17 variables:
## $ ï__Cnty : chr "Bronx" "Bronx" "Bronx" "Bronx" ...
## $ Lcns_Nm : int 734149 606221 606228 723375 724807 712943 703060 609065 722972 609621 ...
## $ Oprtn_T : chr "Store" "Store" "Store" "Store" ...
## $ Estbl_T : chr "JAC" "JAC" "JAC" "JAC" ...
## $ Entty_N : chr "7 ELEVEN FOOD STORE #37933H" "1001 SAN MIGUEL FOOD CENTER INC" "1029 FOOD PLAZA INC" "1078 DELI GROCERY CORP" ...
## $ DBA_Nam : chr NA "1001 SAN MIGUEL FD CNTR" "1029 FOOD PLAZA" "1078 DELI GROCERY" ...
## $ Strt_Nmb: chr "500" "1001" "122" "1078" ...
## $ Stret_Nm: chr "BAYCHESTER AVE" "SHERIDAN AVE" "E 181ST ST" "EAST 165TH STREET" ...
## $ Add_L_2 : int NA NA NA NA NA NA NA NA NA NA ...
## $ Add_L_3 : int NA NA NA NA NA NA NA NA NA NA ...
## $ City : chr "BRONX" "BRONX" "BRONX" "BRONX" ...
## $ State : chr "NY" "NY" "NY" "NY" ...
## $ Zip_Cod : int 10475 10456 10453 10459 10456 10453 10467 10456 10456 10472 ...
## $ Sqr_Ftg : chr "0" "1,100" "2,000" "1,200" ...
## $ Locatin : chr "500 BAYCHESTER AVE\nBRONX, NY 10475\n(40.869156, -73.831875)" "1001 SHERIDAN AVE\nBRONX, NY 10456\n(40.829061, -73.919613)" "122 E 181ST ST\nBRONX, NY 10453\n(40.854755, -73.902853)" "1078 EAST 165TH STREET\nBRONX, NY 10459\n(40.825105, -73.890589)" ...
## $ Coords : chr "40.869156, -73.831875" "40.829061, -73.919613" "40.854755, -73.902853" "40.825105, -73.890589" ...
## $ geometry:sfc_POINT of length 11300; first list element: 'XY' num -73.8 40.9
## - attr(*, "sf_column")= chr "geometry"
## - attr(*, "agr")= Factor w/ 3 levels "constant","aggregate",..: NA NA NA NA NA NA NA NA NA NA ...
## ..- attr(*, "names")= chr [1:16] "ï__Cnty" "Lcns_Nm" "Oprtn_T" "Estbl_T" ...
nyczipcodes_sf %>%
mutate(tract_area = st_area(geometry)) %>%
st_transform(4326) %>%
st_join(nycfoodstores_sf) %>%
filter(Estbl_T == 'A') %>%
head()
## Simple feature collection with 6 features and 29 fields
## Geometry type: POLYGON
## Dimension: XY
## Bounding box: xmin: -73.94807 ymin: 40.66319 xmax: -73.925 ymax: 40.67994
## Geodetic CRS: WGS 84
## ZIPCODE BLDGZIP PO_NAME POPULATION AREA STATE COUNTY ST_FIPS CTY_FIPS
## 2.7 11213 0 Brooklyn 62426 29631004 NY Kings 36 047
## 2.8 11213 0 Brooklyn 62426 29631004 NY Kings 36 047
## 2.21 11213 0 Brooklyn 62426 29631004 NY Kings 36 047
## 2.40 11213 0 Brooklyn 62426 29631004 NY Kings 36 047
## 2.41 11213 0 Brooklyn 62426 29631004 NY Kings 36 047
## 2.46 11213 0 Brooklyn 62426 29631004 NY Kings 36 047
## URL SHAPE_AREA SHAPE_LEN tract_area
## 2.7 http://www.usps.com/ 0 0 29631004 [US_survey_foot^2]
## 2.8 http://www.usps.com/ 0 0 29631004 [US_survey_foot^2]
## 2.21 http://www.usps.com/ 0 0 29631004 [US_survey_foot^2]
## 2.40 http://www.usps.com/ 0 0 29631004 [US_survey_foot^2]
## 2.41 http://www.usps.com/ 0 0 29631004 [US_survey_foot^2]
## 2.46 http://www.usps.com/ 0 0 29631004 [US_survey_foot^2]
## ï__Cnty Lcns_Nm Oprtn_T Estbl_T Entty_N
## 2.7 Kings 734705 Store A J & Y DISCOUNT INC
## 2.8 Kings 618090 Store A ACTION BEVERAGE CORP
## 2.21 Kings 714880 Store A ELBERATI BASEL A
## 2.40 Kings 719258 Store A DOLLAR TREE STORES INC
## 2.41 Kings 712253 Store A DOLLAR TREE STORES INC
## 2.46 Kings 618099 Store A FAMILY DOLLAR STORES OF NY INC
## DBA_Nam Strt_Nmb Stret_Nm Add_L_2 Add_L_3 City
## 2.7 99 CENTS DREAM 1376 ST JOHNS PLACE NA NA BROOKLYN
## 2.8 ACTION BEVERAGE 65 TROY AVE NA NA BROOKLYN
## 2.21 BROOKLYN WAY CANDY&GROC 142 UTICA AVE NA NA BROOKLYN
## 2.40 DOLLAR TREE # 06153 1720 ATLANTIC AVE NA NA BROOKLYN
## 2.41 DOLLAR TREE #5067 250 UTICA AVE NA NA BROOKLYN
## 2.46 FAMILY DOLLAR #6690 1679-1683 PACIFIC ST NA NA BROOKLYN
## State Zip_Cod Sqr_Ftg
## 2.7 NY 11213 2,500
## 2.8 NY 11213 2,500
## 2.21 NY 11213 800
## 2.40 NY 11213 0
## 2.41 NY 11213 5,000
## 2.46 NY 11213 1,000
## Locatin
## 2.7 1376 ST JOHNS PLACE\nBROOKLYN, NY 11213\n(40.670677, -73.932705)
## 2.8 65 TROY AVE\nBROOKLYN, NY 11213\n(40.677191, -73.935902)
## 2.21 142 UTICA AVE\nBROOKLYN, NY 11213\n(40.674019, -73.930632)
## 2.40 1720 ATLANTIC AVE\nBROOKLYN, NY 11213\n(40.677498, -73.933573)
## 2.41 250 UTICA AVE\nBROOKLYN, NY 11213\n(40.669954, -73.931014)
## 2.46 1679 1683 PACIFIC ST\nBROOKLYN, NY 11213\n(40.676826, -73.934715)
## Coords geometry
## 2.7 40.670677, -73.932705 POLYGON ((-73.9374 40.67973...
## 2.8 40.677191, -73.935902 POLYGON ((-73.9374 40.67973...
## 2.21 40.674019, -73.930632 POLYGON ((-73.9374 40.67973...
## 2.40 40.677498, -73.933573 POLYGON ((-73.9374 40.67973...
## 2.41 40.669954, -73.931014 POLYGON ((-73.9374 40.67973...
## 2.46 40.676826, -73.934715 POLYGON ((-73.9374 40.67973...
store_count_sf <- nyczipcodes_sf %>%
mutate(tract_area = st_area(geometry)) %>%
st_transform(4326) %>%
st_join(nycfoodstores_sf) %>%
group_by(ZIPCODE) %>%
summarize(n_stores = n(),
tract_area = max(tract_area))
mapview(store_count_sf, zcol='n_stores', legend=FALSE)
nyc_healthfacilities <- readr::read_csv("R-Spatial_II_Lab/NYS_Health_Facility.csv", lazy = FALSE)
## Rows: 3990 Columns: 36
## ── Column specification ────────────────────────────────────────────────────────
## Delimiter: ","
## chr (28): Facility Name, Short Description, Description, Facility Open Date,...
## dbl (8): Facility ID, Facility Phone Number, Facility Fax Number, Facility ...
##
## ℹ Use `spec()` to retrieve the full column specification for this data.
## ℹ Specify the column types or set `show_col_types = FALSE` to quiet this message.
str(nyc_healthfacilities)
## spc_tbl_ [3,990 × 36] (S3: spec_tbl_df/tbl_df/tbl/data.frame)
## $ Facility ID : num [1:3990] 204 620 654 1156 2589 ...
## $ Facility Name : chr [1:3990] "Hospice at Lourdes" "Charles T Sitrin Health Care Center Inc" "Central Park Rehabilitation and Nursing Center" "East Side Nursing Home" ...
## $ Short Description : chr [1:3990] "HSPC" "NH" "NH" "NH" ...
## $ Description : chr [1:3990] "Hospice" "Residential Health Care Facility - SNF" "Residential Health Care Facility - SNF" "Residential Health Care Facility - SNF" ...
## $ Facility Open Date : chr [1:3990] "06/01/1985" "02/01/1989" "02/01/1989" "08/01/1979" ...
## $ Facility Address 1 : chr [1:3990] "4102 Old Vestal Road" "2050 Tilden Avenue" "116 Martin Luther King East" "62 Prospect St" ...
## $ Facility Address 2 : chr [1:3990] NA NA NA NA ...
## $ Facility City : chr [1:3990] "Vestal" "New Hartford" "Syracuse" "Warsaw" ...
## $ Facility State : chr [1:3990] "New York" "New York" "New York" "New York" ...
## $ Facility Zip Code : chr [1:3990] "13850" "13413" "13205" "14569" ...
## $ Facility Phone Number : num [1:3990] 6.08e+09 3.16e+09 3.15e+09 5.86e+09 5.86e+09 ...
## $ Facility Fax Number : num [1:3990] NA NA NA NA NA ...
## $ Facility Website : chr [1:3990] NA NA NA NA ...
## $ Facility County Code : num [1:3990] 3 32 33 60 2 ...
## $ Facility County : chr [1:3990] "Broome" "Oneida" "Onondaga" "Wyoming" ...
## $ Regional Office ID : num [1:3990] 3 3 3 1 1 1 7 1 7 5 ...
## $ Regional Office : chr [1:3990] "Central New York Regional Office" "Central New York Regional Office" "Central New York Regional Office" "Western Regional Office - Buffalo" ...
## $ Main Site Name : chr [1:3990] NA NA NA NA ...
## $ Main Site Facility ID : num [1:3990] NA NA NA NA NA ...
## $ Operating Certificate Number: chr [1:3990] "0301501F" "3227304N" "3301326N" "6027303N" ...
## $ Operator Name : chr [1:3990] "Our Lady of Lourdes Memorial Hospital Inc" "Charles T Sitrin Health Care Center, Inc" "CPRNC, LLC" "East Side Nursing Home Inc" ...
## $ Operator Address 1 : chr [1:3990] "169 Riverside Drive" "Box 1000 Tilden Avenue" "116 Martin Luther King East" "62 Prospect Street" ...
## $ Operator Address 2 : chr [1:3990] NA NA NA NA ...
## $ Operator City : chr [1:3990] "Binghamton" "New Hartford" "Syracuse" "Warsaw" ...
## $ Operator State : chr [1:3990] "New York" "New York" "New York" "New York" ...
## $ Operator Zip Code : chr [1:3990] "13905" "13413" "13205" "14569" ...
## $ Cooperator Name : chr [1:3990] NA NA NA NA ...
## $ Cooperator Address : chr [1:3990] NA NA NA NA ...
## $ Cooperator Address 2 : chr [1:3990] NA NA NA NA ...
## $ Cooperator City : chr [1:3990] NA NA NA NA ...
## $ Cooperator State : chr [1:3990] "New York" "New York" "New York" "New York" ...
## $ Cooperator Zip Code : chr [1:3990] NA NA NA NA ...
## $ Ownership Type : chr [1:3990] "Not for Profit Corporation" "Not for Profit Corporation" "LLC" "Business Corporation" ...
## $ Facility Latitude : num [1:3990] 42.1 43.1 NA 42.7 42.1 ...
## $ Facility Longitude : num [1:3990] -76 -75.2 NA -78.1 -78 ...
## $ Facility Location : chr [1:3990] "(42.097095, -75.975243)" "(43.05497, -75.228828)" NA "(42.738979, -78.12867)" ...
## - attr(*, "spec")=
## .. cols(
## .. `Facility ID` = col_double(),
## .. `Facility Name` = col_character(),
## .. `Short Description` = col_character(),
## .. Description = col_character(),
## .. `Facility Open Date` = col_character(),
## .. `Facility Address 1` = col_character(),
## .. `Facility Address 2` = col_character(),
## .. `Facility City` = col_character(),
## .. `Facility State` = col_character(),
## .. `Facility Zip Code` = col_character(),
## .. `Facility Phone Number` = col_double(),
## .. `Facility Fax Number` = col_double(),
## .. `Facility Website` = col_character(),
## .. `Facility County Code` = col_double(),
## .. `Facility County` = col_character(),
## .. `Regional Office ID` = col_double(),
## .. `Regional Office` = col_character(),
## .. `Main Site Name` = col_character(),
## .. `Main Site Facility ID` = col_double(),
## .. `Operating Certificate Number` = col_character(),
## .. `Operator Name` = col_character(),
## .. `Operator Address 1` = col_character(),
## .. `Operator Address 2` = col_character(),
## .. `Operator City` = col_character(),
## .. `Operator State` = col_character(),
## .. `Operator Zip Code` = col_character(),
## .. `Cooperator Name` = col_character(),
## .. `Cooperator Address` = col_character(),
## .. `Cooperator Address 2` = col_character(),
## .. `Cooperator City` = col_character(),
## .. `Cooperator State` = col_character(),
## .. `Cooperator Zip Code` = col_character(),
## .. `Ownership Type` = col_character(),
## .. `Facility Latitude` = col_double(),
## .. `Facility Longitude` = col_double(),
## .. `Facility Location` = col_character()
## .. )
## - attr(*, "problems")=<externalptr>
filtered_healthfacilities <- nyc_healthfacilities %>%
filter(`Short Description` %in% c('NH', 'DTC', 'HOSP'))
filtered_healthfacilities_clean <- filtered_healthfacilities %>%
filter(!is.na(`Facility Longitude`) & !is.na(`Facility Latitude`))
filtered_healthfacilities_sf <- st_as_sf(filtered_healthfacilities_clean,
coords = c("Facility Longitude", "Facility Latitude"),
crs = 4326,
agr = "constant")
healthfacility_count_sf <- nyczipcodes_sf %>%
mutate(tract_area = st_area(geometry)) %>%
st_transform(4326) %>%
st_join(filtered_healthfacilities_sf) %>%
group_by(ZIPCODE) %>%
summarize(n_facilities = n(),
tract_area = max(tract_area))
mapview(healthfacility_count_sf, zcol='n_facilities', legend=FALSE)
nyc_census_tracts_sf <- st_read('R-Spatial_II_Lab/2010 Census Tracts/geo_export_1dc7b645-647b-4806-b9a0-7b79660f120a.shp')
## Reading layer `geo_export_1dc7b645-647b-4806-b9a0-7b79660f120a' from data source `/Users/mariyatrofymova/Desktop/Rspatial Study/R-Spatial_II_Lab/2010 Census Tracts/geo_export_1dc7b645-647b-4806-b9a0-7b79660f120a.shp'
## using driver `ESRI Shapefile'
## Simple feature collection with 2165 features and 11 fields
## Geometry type: MULTIPOLYGON
## Dimension: XY
## Bounding box: xmin: -74.25559 ymin: 40.49612 xmax: -73.70001 ymax: 40.91553
## Geodetic CRS: WGS84(DD)
str(nyc_census_tracts_sf)
## Classes 'sf' and 'data.frame': 2165 obs. of 12 variables:
## $ boro_code : chr "5" "1" "1" "1" ...
## $ boro_ct201: chr "5000900" "1009800" "1010000" "1010200" ...
## $ boro_name : chr "Staten Island" "Manhattan" "Manhattan" "Manhattan" ...
## $ cdeligibil: chr "E" "I" "I" "I" ...
## $ ct2010 : chr "000900" "009800" "010000" "010200" ...
## $ ctlabel : chr "9" "98" "100" "102" ...
## $ ntacode : chr "SI22" "MN19" "MN19" "MN17" ...
## $ ntaname : chr "West New Brighton-New Brighton-St. George" "Turtle Bay-East Midtown" "Turtle Bay-East Midtown" "Midtown-Midtown South" ...
## $ puma : chr "3903" "3808" "3808" "3807" ...
## $ shape_area: num 2497010 1906016 1860938 1860993 1864600 ...
## $ shape_leng: num 7729 5534 5692 5688 5693 ...
## $ geometry :sfc_MULTIPOLYGON of length 2165; first list element: List of 1
## ..$ :List of 1
## .. ..$ : num [1:28, 1:2] -74.1 -74.1 -74.1 -74.1 -74.1 ...
## ..- attr(*, "class")= chr [1:3] "XY" "MULTIPOLYGON" "sfg"
## - attr(*, "sf_column")= chr "geometry"
## - attr(*, "agr")= Factor w/ 3 levels "constant","aggregate",..: NA NA NA NA NA NA NA NA NA NA ...
## ..- attr(*, "names")= chr [1:11] "boro_code" "boro_ct201" "boro_name" "cdeligibil" ...
acs_data <- readr::read_csv("R-Spatial_II_Lab/acssurvey.csv", lazy = FALSE)
## Rows: 2167 Columns: 359
## ── Column specification ────────────────────────────────────────────────────────
## Delimiter: ","
## chr (181): GEO_ID, NAME, DP05_0031PM, DP05_0032E, DP05_0032M, DP05_0032PE, D...
## dbl (178): boro_ct201, DP05_0033E, DP05_0033M, DP05_0033PE, DP05_0034E, DP05...
##
## ℹ Use `spec()` to retrieve the full column specification for this data.
## ℹ Specify the column types or set `show_col_types = FALSE` to quiet this message.
str(acs_data)
## spc_tbl_ [2,167 × 359] (S3: spec_tbl_df/tbl_df/tbl/data.frame)
## $ boro_ct201 : num [1:2167] 5e+06 5e+06 5e+06 5e+06 5e+06 ...
## $ GEO_ID : chr [1:2167] "1400000US36005000100" "1400000US36005000200" "1400000US36005000400" "1400000US36005001600" ...
## $ NAME : chr [1:2167] "Census Tract 1, Bronx County, New York" "Census Tract 2, Bronx County, New York" "Census Tract 4, Bronx County, New York" "Census Tract 16, Bronx County, New York" ...
## $ DP05_0031PM: chr [1:2167] "50.4" "9.5" "8.8" "8.9" ...
## $ DP05_0032E : chr [1:2167] "200" "95.1" "91.4" "42.5" ...
## $ DP05_0032M : chr [1:2167] "1316" "37.2" "32.7" "18.4" ...
## $ DP05_0032PE: chr [1:2167] "(X)" "(X)" "(X)" "(X)" ...
## $ DP05_0032PM: chr [1:2167] "(X)" "(X)" "(X)" "(X)" ...
## $ DP05_0033E : num [1:2167] 7080 4542 5634 5917 2765 ...
## $ DP05_0033M : num [1:2167] 290 574 517 461 307 ...
## $ DP05_0033PE: num [1:2167] 7080 4542 5634 5917 2765 ...
## $ DP05_0033PM: chr [1:2167] "(X)" "(X)" "(X)" "(X)" ...
## $ DP05_0034E : num [1:2167] 7012 4349 5425 5760 2595 ...
## $ DP05_0034M : num [1:2167] 289 557 532 454 297 ...
## $ DP05_0034PE: chr [1:2167] "99" "95.8" "96.3" "97.3" ...
## $ DP05_0034PM: chr [1:2167] "0.6" "3.4" "2.1" "1.9" ...
## $ DP05_0035E : num [1:2167] 68 193 209 157 170 309 86 14 159 35 ...
## $ DP05_0035M : num [1:2167] 42 155 117 115 93 287 61 20 113 30 ...
## $ DP05_0035PE: chr [1:2167] "1" "4.2" "3.7" "2.7" ...
## $ DP05_0035PM: chr [1:2167] "0.6" "3.4" "2.1" "1.9" ...
## $ DP05_0036E : num [1:2167] 7012 4349 5425 5760 2595 ...
## $ DP05_0036M : num [1:2167] 289 557 532 454 297 ...
## $ DP05_0036PE: chr [1:2167] "99" "95.8" "96.3" "97.3" ...
## $ DP05_0036PM: chr [1:2167] "0.6" "3.4" "2.1" "1.9" ...
## $ DP05_0037E : num [1:2167] 1773 2165 2623 2406 585 ...
## $ DP05_0037M : num [1:2167] 248 547 427 483 171 907 171 111 310 140 ...
## $ DP05_0037PE: chr [1:2167] "25" "47.7" "46.6" "40.7" ...
## $ DP05_0037PM: chr [1:2167] "3.2" "11.1" "7.8" "7.1" ...
## $ DP05_0038E : num [1:2167] 4239 1279 1699 2434 1041 ...
## $ DP05_0038M : num [1:2167] 286 472 432 451 175 ...
## $ DP05_0038PE: chr [1:2167] "59.9" "28.2" "30.2" "41.1" ...
## $ DP05_0038PM: chr [1:2167] "3.5" "10" "6.4" "7.1" ...
## $ DP05_0039E : num [1:2167] 25 0 30 0 0 182 68 0 22 0 ...
## $ DP05_0039M : num [1:2167] 24 12 33 17 12 151 57 12 35 12 ...
## $ DP05_0039PE: chr [1:2167] "0.4" "0" "0.5" "0" ...
## $ DP05_0039PM: chr [1:2167] "0.3" "0.7" "0.6" "0.5" ...
## $ DP05_0040E : num [1:2167] 0 0 0 0 0 0 0 0 0 0 ...
## $ DP05_0040M : num [1:2167] 17 12 17 17 12 17 12 12 17 12 ...
## $ DP05_0040PE: chr [1:2167] "0" "0" "0" "0" ...
## $ DP05_0040PM: chr [1:2167] "0.5" "0.7" "0.6" "0.5" ...
## $ DP05_0041E : num [1:2167] 0 0 0 0 0 0 0 0 0 0 ...
## $ DP05_0041M : num [1:2167] 17 12 17 17 12 17 12 12 17 12 ...
## $ DP05_0041PE: chr [1:2167] "0" "0" "0" "0" ...
## $ DP05_0041PM: chr [1:2167] "0.5" "0.7" "0.6" "0.5" ...
## $ DP05_0042E : num [1:2167] 0 0 0 0 0 0 0 0 0 0 ...
## $ DP05_0042M : num [1:2167] 17 12 17 17 12 17 12 12 17 12 ...
## $ DP05_0042PE: chr [1:2167] "0" "0" "0" "0" ...
## $ DP05_0042PM: chr [1:2167] "0.5" "0.7" "0.6" "0.5" ...
## $ DP05_0043E : num [1:2167] 0 0 0 0 0 0 0 0 0 0 ...
## $ DP05_0043M : num [1:2167] 17 12 17 17 12 17 12 12 17 12 ...
## $ DP05_0043PE: chr [1:2167] "0" "0" "0" "0" ...
## $ DP05_0043PM: chr [1:2167] "0.5" "0.7" "0.6" "0.5" ...
## $ DP05_0044E : num [1:2167] 125 104 226 13 93 29 0 0 50 0 ...
## $ DP05_0044M : num [1:2167] 51 87 155 19 74 45 12 12 69 12 ...
## $ DP05_0044PE: chr [1:2167] "1.8" "2.3" "4" "0.2" ...
## $ DP05_0044PM: chr [1:2167] "0.7" "2" "2.7" "0.3" ...
## $ DP05_0045E : num [1:2167] 35 40 20 0 69 29 0 0 43 0 ...
## $ DP05_0045M : num [1:2167] 31 64 31 17 70 45 12 12 68 12 ...
## $ DP05_0045PE: chr [1:2167] "0.5" "0.9" "0.4" "0" ...
## $ DP05_0045PM: chr [1:2167] "0.4" "1.4" "0.5" "0.5" ...
## $ DP05_0046E : num [1:2167] 54 0 171 0 9 0 0 0 0 0 ...
## $ DP05_0046M : num [1:2167] 46 12 142 17 14 17 12 12 17 12 ...
## $ DP05_0046PE: chr [1:2167] "0.8" "0" "3" "0" ...
## $ DP05_0046PM: chr [1:2167] "0.6" "0.7" "2.5" "0.5" ...
## $ DP05_0047E : num [1:2167] 0 0 23 0 4 0 0 0 0 0 ...
## $ DP05_0047M : num [1:2167] 17 12 36 17 6 17 12 12 17 12 ...
## $ DP05_0047PE: chr [1:2167] "0" "0" "0.4" "0" ...
## $ DP05_0047PM: chr [1:2167] "0.5" "0.7" "0.6" "0.5" ...
## $ DP05_0048E : num [1:2167] 0 40 0 0 0 0 0 0 0 0 ...
## $ DP05_0048M : num [1:2167] 17 55 17 17 12 17 12 12 17 12 ...
## $ DP05_0048PE: chr [1:2167] "0" "0.9" "0" "0" ...
## $ DP05_0048PM: chr [1:2167] "0.5" "1.2" "0.6" "0.5" ...
## $ DP05_0049E : num [1:2167] 4 0 0 0 11 0 0 0 7 0 ...
## $ DP05_0049M : num [1:2167] 7 12 17 17 18 17 12 12 11 12 ...
## $ DP05_0049PE: chr [1:2167] "0.1" "0" "0" "0" ...
## $ DP05_0049PM: chr [1:2167] "0.1" "0.7" "0.6" "0.5" ...
## $ DP05_0050E : num [1:2167] 0 0 12 0 0 0 0 0 0 0 ...
## $ DP05_0050M : num [1:2167] 17 12 19 17 12 17 12 12 17 12 ...
## $ DP05_0050PE: chr [1:2167] "0" "0" "0.2" "0" ...
## $ DP05_0050PM: chr [1:2167] "0.5" "0.7" "0.3" "0.5" ...
## $ DP05_0051E : num [1:2167] 32 24 0 13 0 0 0 0 0 0 ...
## $ DP05_0051M : num [1:2167] 30 45 17 19 12 17 12 12 17 12 ...
## $ DP05_0051PE: chr [1:2167] "0.5" "0.5" "0" "0.2" ...
## $ DP05_0051PM: chr [1:2167] "0.4" "1" "0.6" "0.3" ...
## $ DP05_0052E : num [1:2167] 0 0 0 0 0 0 0 0 20 0 ...
## $ DP05_0052M : num [1:2167] 17 12 17 17 12 17 12 12 35 12 ...
## $ DP05_0052PE: chr [1:2167] "0" "0" "0" "0" ...
## $ DP05_0052PM: chr [1:2167] "0.5" "0.7" "0.6" "0.5" ...
## $ DP05_0053E : num [1:2167] 0 0 0 0 0 0 0 0 0 0 ...
## $ DP05_0053M : num [1:2167] 17 12 17 17 12 17 12 12 17 12 ...
## $ DP05_0053PE: chr [1:2167] "0" "0" "0" "0" ...
## $ DP05_0053PM: chr [1:2167] "0.5" "0.7" "0.6" "0.5" ...
## $ DP05_0054E : num [1:2167] 0 0 0 0 0 0 0 0 0 0 ...
## $ DP05_0054M : num [1:2167] 17 12 17 17 12 17 12 12 17 12 ...
## $ DP05_0054PE: chr [1:2167] "0" "0" "0" "0" ...
## $ DP05_0054PM: chr [1:2167] "0.5" "0.7" "0.6" "0.5" ...
## $ DP05_0055E : num [1:2167] 0 0 0 0 0 0 0 0 0 0 ...
## $ DP05_0055M : num [1:2167] 17 12 17 17 12 17 12 12 17 12 ...
## $ DP05_0055PE: chr [1:2167] "0" "0" "0" "0" ...
## [list output truncated]
## - attr(*, "spec")=
## .. cols(
## .. boro_ct201 = col_double(),
## .. GEO_ID = col_character(),
## .. NAME = col_character(),
## .. DP05_0031PM = col_character(),
## .. DP05_0032E = col_character(),
## .. DP05_0032M = col_character(),
## .. DP05_0032PE = col_character(),
## .. DP05_0032PM = col_character(),
## .. DP05_0033E = col_double(),
## .. DP05_0033M = col_double(),
## .. DP05_0033PE = col_double(),
## .. DP05_0033PM = col_character(),
## .. DP05_0034E = col_double(),
## .. DP05_0034M = col_double(),
## .. DP05_0034PE = col_character(),
## .. DP05_0034PM = col_character(),
## .. DP05_0035E = col_double(),
## .. DP05_0035M = col_double(),
## .. DP05_0035PE = col_character(),
## .. DP05_0035PM = col_character(),
## .. DP05_0036E = col_double(),
## .. DP05_0036M = col_double(),
## .. DP05_0036PE = col_character(),
## .. DP05_0036PM = col_character(),
## .. DP05_0037E = col_double(),
## .. DP05_0037M = col_double(),
## .. DP05_0037PE = col_character(),
## .. DP05_0037PM = col_character(),
## .. DP05_0038E = col_double(),
## .. DP05_0038M = col_double(),
## .. DP05_0038PE = col_character(),
## .. DP05_0038PM = col_character(),
## .. DP05_0039E = col_double(),
## .. DP05_0039M = col_double(),
## .. DP05_0039PE = col_character(),
## .. DP05_0039PM = col_character(),
## .. DP05_0040E = col_double(),
## .. DP05_0040M = col_double(),
## .. DP05_0040PE = col_character(),
## .. DP05_0040PM = col_character(),
## .. DP05_0041E = col_double(),
## .. DP05_0041M = col_double(),
## .. DP05_0041PE = col_character(),
## .. DP05_0041PM = col_character(),
## .. DP05_0042E = col_double(),
## .. DP05_0042M = col_double(),
## .. DP05_0042PE = col_character(),
## .. DP05_0042PM = col_character(),
## .. DP05_0043E = col_double(),
## .. DP05_0043M = col_double(),
## .. DP05_0043PE = col_character(),
## .. DP05_0043PM = col_character(),
## .. DP05_0044E = col_double(),
## .. DP05_0044M = col_double(),
## .. DP05_0044PE = col_character(),
## .. DP05_0044PM = col_character(),
## .. DP05_0045E = col_double(),
## .. DP05_0045M = col_double(),
## .. DP05_0045PE = col_character(),
## .. DP05_0045PM = col_character(),
## .. DP05_0046E = col_double(),
## .. DP05_0046M = col_double(),
## .. DP05_0046PE = col_character(),
## .. DP05_0046PM = col_character(),
## .. DP05_0047E = col_double(),
## .. DP05_0047M = col_double(),
## .. DP05_0047PE = col_character(),
## .. DP05_0047PM = col_character(),
## .. DP05_0048E = col_double(),
## .. DP05_0048M = col_double(),
## .. DP05_0048PE = col_character(),
## .. DP05_0048PM = col_character(),
## .. DP05_0049E = col_double(),
## .. DP05_0049M = col_double(),
## .. DP05_0049PE = col_character(),
## .. DP05_0049PM = col_character(),
## .. DP05_0050E = col_double(),
## .. DP05_0050M = col_double(),
## .. DP05_0050PE = col_character(),
## .. DP05_0050PM = col_character(),
## .. DP05_0051E = col_double(),
## .. DP05_0051M = col_double(),
## .. DP05_0051PE = col_character(),
## .. DP05_0051PM = col_character(),
## .. DP05_0052E = col_double(),
## .. DP05_0052M = col_double(),
## .. DP05_0052PE = col_character(),
## .. DP05_0052PM = col_character(),
## .. DP05_0053E = col_double(),
## .. DP05_0053M = col_double(),
## .. DP05_0053PE = col_character(),
## .. DP05_0053PM = col_character(),
## .. DP05_0054E = col_double(),
## .. DP05_0054M = col_double(),
## .. DP05_0054PE = col_character(),
## .. DP05_0054PM = col_character(),
## .. DP05_0055E = col_double(),
## .. DP05_0055M = col_double(),
## .. DP05_0055PE = col_character(),
## .. DP05_0055PM = col_character(),
## .. DP05_0056E = col_double(),
## .. DP05_0056M = col_double(),
## .. DP05_0056PE = col_character(),
## .. DP05_0056PM = col_character(),
## .. DP05_0057E = col_double(),
## .. DP05_0057M = col_double(),
## .. DP05_0057PE = col_character(),
## .. DP05_0057PM = col_character(),
## .. DP05_0058E = col_double(),
## .. DP05_0058M = col_double(),
## .. DP05_0058PE = col_character(),
## .. DP05_0058PM = col_character(),
## .. DP05_0059E = col_double(),
## .. DP05_0059M = col_double(),
## .. DP05_0059PE = col_character(),
## .. DP05_0059PM = col_character(),
## .. DP05_0060E = col_double(),
## .. DP05_0060M = col_double(),
## .. DP05_0060PE = col_character(),
## .. DP05_0060PM = col_character(),
## .. DP05_0061E = col_double(),
## .. DP05_0061M = col_double(),
## .. DP05_0061PE = col_character(),
## .. DP05_0061PM = col_character(),
## .. DP05_0062E = col_double(),
## .. DP05_0062M = col_double(),
## .. DP05_0062PE = col_character(),
## .. DP05_0062PM = col_character(),
## .. DP05_0063E = col_double(),
## .. DP05_0063M = col_double(),
## .. DP05_0063PE = col_double(),
## .. DP05_0063PM = col_character(),
## .. DP05_0064E = col_double(),
## .. DP05_0064M = col_double(),
## .. DP05_0064PE = col_character(),
## .. DP05_0064PM = col_character(),
## .. DP05_0065E = col_double(),
## .. DP05_0065M = col_double(),
## .. DP05_0065PE = col_character(),
## .. DP05_0065PM = col_character(),
## .. DP05_0066E = col_double(),
## .. DP05_0066M = col_double(),
## .. DP05_0066PE = col_character(),
## .. DP05_0066PM = col_character(),
## .. DP05_0067E = col_double(),
## .. DP05_0067M = col_double(),
## .. DP05_0067PE = col_character(),
## .. DP05_0067PM = col_character(),
## .. DP05_0068E = col_double(),
## .. DP05_0068M = col_double(),
## .. DP05_0068PE = col_character(),
## .. DP05_0068PM = col_character(),
## .. DP05_0069E = col_double(),
## .. DP05_0069M = col_double(),
## .. DP05_0069PE = col_character(),
## .. DP05_0069PM = col_character(),
## .. DP05_0070E = col_double(),
## .. DP05_0070M = col_double(),
## .. DP05_0070PE = col_double(),
## .. DP05_0070PM = col_character(),
## .. DP05_0071E = col_double(),
## .. DP05_0071M = col_double(),
## .. DP05_0071PE = col_character(),
## .. DP05_0071PM = col_character(),
## .. DP05_0072E = col_double(),
## .. DP05_0072M = col_double(),
## .. DP05_0072PE = col_character(),
## .. DP05_0072PM = col_character(),
## .. DP05_0073E = col_double(),
## .. DP05_0073M = col_double(),
## .. DP05_0073PE = col_character(),
## .. DP05_0073PM = col_character(),
## .. DP05_0074E = col_double(),
## .. DP05_0074M = col_double(),
## .. DP05_0074PE = col_character(),
## .. DP05_0074PM = col_character(),
## .. DP05_0075E = col_double(),
## .. DP05_0075M = col_double(),
## .. DP05_0075PE = col_character(),
## .. DP05_0075PM = col_character(),
## .. DP05_0076E = col_double(),
## .. DP05_0076M = col_double(),
## .. DP05_0076PE = col_character(),
## .. DP05_0076PM = col_character(),
## .. DP05_0077E = col_double(),
## .. DP05_0077M = col_double(),
## .. DP05_0077PE = col_character(),
## .. DP05_0077PM = col_character(),
## .. DP05_0078E = col_double(),
## .. DP05_0078M = col_double(),
## .. DP05_0078PE = col_character(),
## .. DP05_0078PM = col_character(),
## .. DP05_0079E = col_double(),
## .. DP05_0079M = col_double(),
## .. DP05_0079PE = col_character(),
## .. DP05_0079PM = col_character(),
## .. DP05_0080E = col_double(),
## .. DP05_0080M = col_double(),
## .. DP05_0080PE = col_character(),
## .. DP05_0080PM = col_character(),
## .. DP05_0081E = col_double(),
## .. DP05_0081M = col_double(),
## .. DP05_0081PE = col_character(),
## .. DP05_0081PM = col_character(),
## .. DP05_0082E = col_double(),
## .. DP05_0082M = col_double(),
## .. DP05_0082PE = col_character(),
## .. DP05_0082PM = col_character(),
## .. DP05_0083E = col_double(),
## .. DP05_0083M = col_double(),
## .. DP05_0083PE = col_character(),
## .. DP05_0083PM = col_character(),
## .. DP05_0084E = col_double(),
## .. DP05_0084M = col_double(),
## .. DP05_0084PE = col_character(),
## .. DP05_0084PM = col_character(),
## .. DP05_0085E = col_double(),
## .. DP05_0085M = col_double(),
## .. DP05_0085PE = col_character(),
## .. DP05_0085PM = col_character(),
## .. DP05_0086E = col_double(),
## .. DP05_0086M = col_double(),
## .. DP05_0086PE = col_character(),
## .. DP05_0086PM = col_character(),
## .. DP05_0087E = col_double(),
## .. DP05_0087M = col_double(),
## .. DP05_0087PE = col_double(),
## .. DP05_0087PM = col_character(),
## .. DP05_0088E = col_double(),
## .. DP05_0088M = col_double(),
## .. DP05_0088PE = col_character(),
## .. DP05_0088PM = col_character(),
## .. DP05_0089E = col_double(),
## .. DP05_0089M = col_double(),
## .. DP05_0089PE = col_character(),
## .. DP05_0089PM = col_character(),
## .. DP05_0001E = col_double(),
## .. DP05_0001M = col_double(),
## .. DP05_0001PE = col_double(),
## .. DP05_0001PM = col_character(),
## .. DP05_0002E = col_double(),
## .. DP05_0002M = col_double(),
## .. DP05_0002PE = col_character(),
## .. DP05_0002PM = col_character(),
## .. DP05_0003E = col_double(),
## .. DP05_0003M = col_double(),
## .. DP05_0003PE = col_character(),
## .. DP05_0003PM = col_character(),
## .. DP05_0004E = col_character(),
## .. DP05_0004M = col_character(),
## .. DP05_0004PE = col_character(),
## .. DP05_0004PM = col_character(),
## .. DP05_0005E = col_double(),
## .. DP05_0005M = col_double(),
## .. DP05_0005PE = col_character(),
## .. DP05_0005PM = col_character(),
## .. DP05_0006E = col_double(),
## .. DP05_0006M = col_double(),
## .. DP05_0006PE = col_character(),
## .. DP05_0006PM = col_character(),
## .. DP05_0007E = col_double(),
## .. DP05_0007M = col_double(),
## .. DP05_0007PE = col_character(),
## .. DP05_0007PM = col_character(),
## .. DP05_0008E = col_double(),
## .. DP05_0008M = col_double(),
## .. DP05_0008PE = col_character(),
## .. DP05_0008PM = col_character(),
## .. DP05_0009E = col_double(),
## .. DP05_0009M = col_double(),
## .. DP05_0009PE = col_character(),
## .. DP05_0009PM = col_character(),
## .. DP05_0010E = col_double(),
## .. DP05_0010M = col_double(),
## .. DP05_0010PE = col_character(),
## .. DP05_0010PM = col_character(),
## .. DP05_0011E = col_double(),
## .. DP05_0011M = col_double(),
## .. DP05_0011PE = col_character(),
## .. DP05_0011PM = col_character(),
## .. DP05_0012E = col_double(),
## .. DP05_0012M = col_double(),
## .. DP05_0012PE = col_character(),
## .. DP05_0012PM = col_character(),
## .. DP05_0013E = col_double(),
## .. DP05_0013M = col_double(),
## .. DP05_0013PE = col_character(),
## .. DP05_0013PM = col_character(),
## .. DP05_0014E = col_double(),
## .. DP05_0014M = col_double(),
## .. DP05_0014PE = col_character(),
## .. DP05_0014PM = col_character(),
## .. DP05_0015E = col_double(),
## .. DP05_0015M = col_double(),
## .. DP05_0015PE = col_character(),
## .. DP05_0015PM = col_character(),
## .. DP05_0016E = col_double(),
## .. DP05_0016M = col_double(),
## .. DP05_0016PE = col_character(),
## .. DP05_0016PM = col_character(),
## .. DP05_0017E = col_double(),
## .. DP05_0017M = col_double(),
## .. DP05_0017PE = col_character(),
## .. DP05_0017PM = col_character(),
## .. DP05_0018E = col_character(),
## .. DP05_0018M = col_character(),
## .. DP05_0018PE = col_character(),
## .. DP05_0018PM = col_character(),
## .. DP05_0019E = col_double(),
## .. DP05_0019M = col_double(),
## .. DP05_0019PE = col_character(),
## .. DP05_0019PM = col_character(),
## .. DP05_0020E = col_double(),
## .. DP05_0020M = col_double(),
## .. DP05_0020PE = col_character(),
## .. DP05_0020PM = col_character(),
## .. DP05_0021E = col_double(),
## .. DP05_0021M = col_double(),
## .. DP05_0021PE = col_character(),
## .. DP05_0021PM = col_character(),
## .. DP05_0022E = col_double(),
## .. DP05_0022M = col_double(),
## .. DP05_0022PE = col_character(),
## .. DP05_0022PM = col_character(),
## .. DP05_0023E = col_double(),
## .. DP05_0023M = col_double(),
## .. DP05_0023PE = col_character(),
## .. DP05_0023PM = col_character(),
## .. DP05_0024E = col_double(),
## .. DP05_0024M = col_double(),
## .. DP05_0024PE = col_character(),
## .. DP05_0024PM = col_character(),
## .. DP05_0025E = col_double(),
## .. DP05_0025M = col_double(),
## .. DP05_0025PE = col_double(),
## .. DP05_0025PM = col_character(),
## .. DP05_0026E = col_double(),
## .. DP05_0026M = col_double(),
## .. DP05_0026PE = col_character(),
## .. DP05_0026PM = col_character(),
## .. DP05_0027E = col_double(),
## .. DP05_0027M = col_double(),
## .. DP05_0027PE = col_character(),
## .. DP05_0027PM = col_character(),
## .. DP05_0028E = col_character(),
## .. DP05_0028M = col_character(),
## .. DP05_0028PE = col_character(),
## .. DP05_0028PM = col_character(),
## .. DP05_0029E = col_double(),
## .. DP05_0029M = col_double(),
## .. DP05_0029PE = col_double(),
## .. DP05_0029PM = col_character(),
## .. DP05_0030E = col_double(),
## .. DP05_0030M = col_double(),
## .. DP05_0030PE = col_character(),
## .. DP05_0030PM = col_character(),
## .. DP05_0031E = col_double(),
## .. DP05_0031M = col_double(),
## .. DP05_0031PE = col_character()
## .. )
## - attr(*, "problems")=<externalptr>
acs_sf_merged <- base::merge(nyc_census_tracts_sf, acs_data, by.x = "boro_ct201", by.y = "boro_ct201")
names(acs_sf_merged)
## [1] "boro_ct201" "boro_code" "boro_name" "cdeligibil" "ct2010"
## [6] "ctlabel" "ntacode" "ntaname" "puma" "shape_area"
## [11] "shape_leng" "GEO_ID" "NAME" "DP05_0031PM" "DP05_0032E"
## [16] "DP05_0032M" "DP05_0032PE" "DP05_0032PM" "DP05_0033E" "DP05_0033M"
## [21] "DP05_0033PE" "DP05_0033PM" "DP05_0034E" "DP05_0034M" "DP05_0034PE"
## [26] "DP05_0034PM" "DP05_0035E" "DP05_0035M" "DP05_0035PE" "DP05_0035PM"
## [31] "DP05_0036E" "DP05_0036M" "DP05_0036PE" "DP05_0036PM" "DP05_0037E"
## [36] "DP05_0037M" "DP05_0037PE" "DP05_0037PM" "DP05_0038E" "DP05_0038M"
## [41] "DP05_0038PE" "DP05_0038PM" "DP05_0039E" "DP05_0039M" "DP05_0039PE"
## [46] "DP05_0039PM" "DP05_0040E" "DP05_0040M" "DP05_0040PE" "DP05_0040PM"
## [51] "DP05_0041E" "DP05_0041M" "DP05_0041PE" "DP05_0041PM" "DP05_0042E"
## [56] "DP05_0042M" "DP05_0042PE" "DP05_0042PM" "DP05_0043E" "DP05_0043M"
## [61] "DP05_0043PE" "DP05_0043PM" "DP05_0044E" "DP05_0044M" "DP05_0044PE"
## [66] "DP05_0044PM" "DP05_0045E" "DP05_0045M" "DP05_0045PE" "DP05_0045PM"
## [71] "DP05_0046E" "DP05_0046M" "DP05_0046PE" "DP05_0046PM" "DP05_0047E"
## [76] "DP05_0047M" "DP05_0047PE" "DP05_0047PM" "DP05_0048E" "DP05_0048M"
## [81] "DP05_0048PE" "DP05_0048PM" "DP05_0049E" "DP05_0049M" "DP05_0049PE"
## [86] "DP05_0049PM" "DP05_0050E" "DP05_0050M" "DP05_0050PE" "DP05_0050PM"
## [91] "DP05_0051E" "DP05_0051M" "DP05_0051PE" "DP05_0051PM" "DP05_0052E"
## [96] "DP05_0052M" "DP05_0052PE" "DP05_0052PM" "DP05_0053E" "DP05_0053M"
## [101] "DP05_0053PE" "DP05_0053PM" "DP05_0054E" "DP05_0054M" "DP05_0054PE"
## [106] "DP05_0054PM" "DP05_0055E" "DP05_0055M" "DP05_0055PE" "DP05_0055PM"
## [111] "DP05_0056E" "DP05_0056M" "DP05_0056PE" "DP05_0056PM" "DP05_0057E"
## [116] "DP05_0057M" "DP05_0057PE" "DP05_0057PM" "DP05_0058E" "DP05_0058M"
## [121] "DP05_0058PE" "DP05_0058PM" "DP05_0059E" "DP05_0059M" "DP05_0059PE"
## [126] "DP05_0059PM" "DP05_0060E" "DP05_0060M" "DP05_0060PE" "DP05_0060PM"
## [131] "DP05_0061E" "DP05_0061M" "DP05_0061PE" "DP05_0061PM" "DP05_0062E"
## [136] "DP05_0062M" "DP05_0062PE" "DP05_0062PM" "DP05_0063E" "DP05_0063M"
## [141] "DP05_0063PE" "DP05_0063PM" "DP05_0064E" "DP05_0064M" "DP05_0064PE"
## [146] "DP05_0064PM" "DP05_0065E" "DP05_0065M" "DP05_0065PE" "DP05_0065PM"
## [151] "DP05_0066E" "DP05_0066M" "DP05_0066PE" "DP05_0066PM" "DP05_0067E"
## [156] "DP05_0067M" "DP05_0067PE" "DP05_0067PM" "DP05_0068E" "DP05_0068M"
## [161] "DP05_0068PE" "DP05_0068PM" "DP05_0069E" "DP05_0069M" "DP05_0069PE"
## [166] "DP05_0069PM" "DP05_0070E" "DP05_0070M" "DP05_0070PE" "DP05_0070PM"
## [171] "DP05_0071E" "DP05_0071M" "DP05_0071PE" "DP05_0071PM" "DP05_0072E"
## [176] "DP05_0072M" "DP05_0072PE" "DP05_0072PM" "DP05_0073E" "DP05_0073M"
## [181] "DP05_0073PE" "DP05_0073PM" "DP05_0074E" "DP05_0074M" "DP05_0074PE"
## [186] "DP05_0074PM" "DP05_0075E" "DP05_0075M" "DP05_0075PE" "DP05_0075PM"
## [191] "DP05_0076E" "DP05_0076M" "DP05_0076PE" "DP05_0076PM" "DP05_0077E"
## [196] "DP05_0077M" "DP05_0077PE" "DP05_0077PM" "DP05_0078E" "DP05_0078M"
## [201] "DP05_0078PE" "DP05_0078PM" "DP05_0079E" "DP05_0079M" "DP05_0079PE"
## [206] "DP05_0079PM" "DP05_0080E" "DP05_0080M" "DP05_0080PE" "DP05_0080PM"
## [211] "DP05_0081E" "DP05_0081M" "DP05_0081PE" "DP05_0081PM" "DP05_0082E"
## [216] "DP05_0082M" "DP05_0082PE" "DP05_0082PM" "DP05_0083E" "DP05_0083M"
## [221] "DP05_0083PE" "DP05_0083PM" "DP05_0084E" "DP05_0084M" "DP05_0084PE"
## [226] "DP05_0084PM" "DP05_0085E" "DP05_0085M" "DP05_0085PE" "DP05_0085PM"
## [231] "DP05_0086E" "DP05_0086M" "DP05_0086PE" "DP05_0086PM" "DP05_0087E"
## [236] "DP05_0087M" "DP05_0087PE" "DP05_0087PM" "DP05_0088E" "DP05_0088M"
## [241] "DP05_0088PE" "DP05_0088PM" "DP05_0089E" "DP05_0089M" "DP05_0089PE"
## [246] "DP05_0089PM" "DP05_0001E" "DP05_0001M" "DP05_0001PE" "DP05_0001PM"
## [251] "DP05_0002E" "DP05_0002M" "DP05_0002PE" "DP05_0002PM" "DP05_0003E"
## [256] "DP05_0003M" "DP05_0003PE" "DP05_0003PM" "DP05_0004E" "DP05_0004M"
## [261] "DP05_0004PE" "DP05_0004PM" "DP05_0005E" "DP05_0005M" "DP05_0005PE"
## [266] "DP05_0005PM" "DP05_0006E" "DP05_0006M" "DP05_0006PE" "DP05_0006PM"
## [271] "DP05_0007E" "DP05_0007M" "DP05_0007PE" "DP05_0007PM" "DP05_0008E"
## [276] "DP05_0008M" "DP05_0008PE" "DP05_0008PM" "DP05_0009E" "DP05_0009M"
## [281] "DP05_0009PE" "DP05_0009PM" "DP05_0010E" "DP05_0010M" "DP05_0010PE"
## [286] "DP05_0010PM" "DP05_0011E" "DP05_0011M" "DP05_0011PE" "DP05_0011PM"
## [291] "DP05_0012E" "DP05_0012M" "DP05_0012PE" "DP05_0012PM" "DP05_0013E"
## [296] "DP05_0013M" "DP05_0013PE" "DP05_0013PM" "DP05_0014E" "DP05_0014M"
## [301] "DP05_0014PE" "DP05_0014PM" "DP05_0015E" "DP05_0015M" "DP05_0015PE"
## [306] "DP05_0015PM" "DP05_0016E" "DP05_0016M" "DP05_0016PE" "DP05_0016PM"
## [311] "DP05_0017E" "DP05_0017M" "DP05_0017PE" "DP05_0017PM" "DP05_0018E"
## [316] "DP05_0018M" "DP05_0018PE" "DP05_0018PM" "DP05_0019E" "DP05_0019M"
## [321] "DP05_0019PE" "DP05_0019PM" "DP05_0020E" "DP05_0020M" "DP05_0020PE"
## [326] "DP05_0020PM" "DP05_0021E" "DP05_0021M" "DP05_0021PE" "DP05_0021PM"
## [331] "DP05_0022E" "DP05_0022M" "DP05_0022PE" "DP05_0022PM" "DP05_0023E"
## [336] "DP05_0023M" "DP05_0023PE" "DP05_0023PM" "DP05_0024E" "DP05_0024M"
## [341] "DP05_0024PE" "DP05_0024PM" "DP05_0025E" "DP05_0025M" "DP05_0025PE"
## [346] "DP05_0025PM" "DP05_0026E" "DP05_0026M" "DP05_0026PE" "DP05_0026PM"
## [351] "DP05_0027E" "DP05_0027M" "DP05_0027PE" "DP05_0027PM" "DP05_0028E"
## [356] "DP05_0028M" "DP05_0028PE" "DP05_0028PM" "DP05_0029E" "DP05_0029M"
## [361] "DP05_0029PE" "DP05_0029PM" "DP05_0030E" "DP05_0030M" "DP05_0030PE"
## [366] "DP05_0030PM" "DP05_0031E" "DP05_0031M" "DP05_0031PE" "geometry"
acs_sf_merged <- st_transform(acs_sf_merged, st_crs(nyczipcodes_sf))
tracts_with_zip <- st_join(acs_sf_merged, nyczipcodes_sf, join = st_within)
zip_code_aggregates <- tracts_with_zip %>%
group_by(ZIPCODE) %>%
summarize(total_population = sum(POPULATION, na.rm = TRUE))
mapview(zip_code_aggregates, zcol = 'total_population')