load packages
require(tidyverse);## Loading required package: tidyverse## ── Attaching core tidyverse packages ──────────────────────── tidyverse 2.0.0 ──
## ✔ dplyr 1.1.4 ✔ readr 2.1.5
## ✔ forcats 1.0.0 ✔ stringr 1.5.1
## ✔ ggplot2 3.4.4 ✔ tibble 3.2.1
## ✔ lubridate 1.9.3 ✔ tidyr 1.3.1
## ✔ purrr 1.0.2
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## ✖ dplyr::filter() masks stats::filter()
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## ℹ Use the conflicted package (<http://conflicted.r-lib.org/>) to force all conflicts to become errorsrequire(sf); ## Loading required package: sf
## Linking to GEOS 3.11.0, GDAL 3.5.3, PROJ 9.1.0; sf_use_s2() is TRUErequire(mapview); ## Loading required package: mapviewrequire(magrittr); ## Loading required package: magrittr
##
## Attaching package: 'magrittr'
##
## The following object is masked from 'package:purrr':
##
## set_names
##
## The following object is masked from 'package:tidyr':
##
## extract#Read in the data
zip_sf <- st_read("Data/ZIP_CODE_040114/ZIP_CODE_040114.shp")## Reading layer `ZIP_CODE_040114' from data source
## `/Users/jamesreo/Desktop/R Independent Study/Weeks 7-9/Session 8/R-spatial/Data/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)NYC_Covid_2023 <- read_csv("Data/R-Spatial_II_Lab/tests-by-zcta_2021_04_23.csv",
show_col_types = FALSE)
str(NYC_Covid_2023)## 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>#Join by zipcode
covid_zip_sf_merged <- base::merge(zip_sf, NYC_Covid_2023, by.x = "ZIPCODE", by.y = "MODIFIED_ZCTA")
names(covid_zip_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"#Read in and examine
nyc_foodstores_sf <- st_read("./Data/R-Spatial_II_Lab/nycFoodStore.shp")## Reading layer `nycFoodStore' from data source
## `/Users/jamesreo/Desktop/R Independent Study/Weeks 7-9/Session 8/R-spatial/Data/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 84str(nyc_foodstores_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" ...#Mutate and change CRS
zip_sf %>%
mutate(tract_area = st_area(geometry)) %>%
st_transform(4326) %>%
st_join(nyc_foodstores_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...#Aggregate and mutate stores and geometry to zipcodes, plot to check.
NYC_stores_agr_sf <- zip_sf %>%
mutate(tract_area = st_area(geometry)) %>%
st_transform(4326) %>%
st_join(nyc_foodstores_sf) %>%
group_by(ZIPCODE) %>%
summarize(n_stores = n(),
tract_area = max(tract_area))
mapview(NYC_stores_agr_sf, zcol='n_stores', legend=FALSE)#Read in, filter for NYC and chosen subgroup.
nys_health_facilities <- read_csv("Data/R-Spatial_II_Lab/NYS_Health_Facility.csv",
show_col_types = FALSE)
nyc_zip_codes <- as.list(as.character(zip_sf$ZIPCODE))
nyc_health_facilities <- nys_health_facilities %>% filter(`Facility Zip Code` %in%
nyc_zip_codes,
`Short Description` %in% c("HOSP", "NH"))
str(nyc_health_facilities)## spc_tbl_ [235 × 36] (S3: spec_tbl_df/tbl_df/tbl/data.frame)
## $ Facility ID : num [1:235] 1217 1185 1469 1705 7745 ...
## $ Facility Name : chr [1:235] "St Patricks Home" "Montefiore Medical Center - Montefiore Westchester Square" "Mount Sinai Morningside" "Dry Harbor Nursing Home" ...
## $ Short Description : chr [1:235] "NH" "HOSP" "HOSP" "NH" ...
## $ Description : chr [1:235] "Residential Health Care Facility - SNF" "Hospital" "Hospital" "Residential Health Care Facility - SNF" ...
## $ Facility Open Date : chr [1:235] "01/01/1901" "08/01/1979" "01/01/1901" "06/01/1987" ...
## $ Facility Address 1 : chr [1:235] "66 Van Cortlandt Park South" "2475 St. Raymond Avenue" "1111 Amsterdam Avenue" "61-35 Dry Harbor Road" ...
## $ Facility Address 2 : chr [1:235] NA NA NA NA ...
## $ Facility City : chr [1:235] "Bronx" "Bronx" "New York" "Middle Village" ...
## $ Facility State : chr [1:235] "New York" "New York" "New York" "New York" ...
## $ Facility Zip Code : chr [1:235] "10463" "10461" "10025" "11379" ...
## $ Facility Phone Number : num [1:235] 7.19e+09 7.18e+09 2.13e+09 7.19e+09 7.18e+09 ...
## $ Facility Fax Number : num [1:235] NA NA NA NA NA ...
## $ Facility Website : chr [1:235] NA NA NA NA ...
## $ Facility County Code : num [1:235] 7094 7094 7093 7096 7096 ...
## $ Facility County : chr [1:235] "Bronx" "Bronx" "New York" "Queens" ...
## $ Regional Office ID : num [1:235] 5 5 5 5 5 5 5 5 5 5 ...
## $ Regional Office : chr [1:235] "Metropolitan Area Regional Office - New York City" "Metropolitan Area Regional Office - New York City" "Metropolitan Area Regional Office - New York City" "Metropolitan Area Regional Office - New York City" ...
## $ Main Site Name : chr [1:235] NA "Montefiore Medical Center - Henry & Lucy Moses Div" "Mount Sinai West" NA ...
## $ Main Site Facility ID : num [1:235] NA 1169 1466 NA NA ...
## $ Operating Certificate Number: chr [1:235] "7000307N" "7000006H" "7002032H" "7003359N" ...
## $ Operator Name : chr [1:235] "St Patricks Home for the Aged & Infirm" "Montefiore Medical Center" "St Lukes Roosevelt Hospital Center Inc" "Dry Harbor HRF Inc" ...
## $ Operator Address 1 : chr [1:235] "Box 218 Rd 1" "111 East 210th Street" "Amsterdam Avenue At 114th Street" "61-35 Dry Harbor Road" ...
## $ Operator Address 2 : chr [1:235] NA NA NA NA ...
## $ Operator City : chr [1:235] "Germantown" "Bronx" "New York" "Middle Village" ...
## $ Operator State : chr [1:235] "New York" "New York" "New York" "New York" ...
## $ Operator Zip Code : chr [1:235] "12526" "10467" "10025" "11379" ...
## $ Cooperator Name : chr [1:235] NA "Montefiore Health System, Inc" "Mount Sinai Hospitals Group, Inc." NA ...
## $ Cooperator Address : chr [1:235] NA "111 East 210th Street" "One Gustave L. Levy Place" NA ...
## $ Cooperator Address 2 : chr [1:235] NA NA NA NA ...
## $ Cooperator City : chr [1:235] NA "Bronx" "New York" NA ...
## $ Cooperator State : chr [1:235] "New York" "New York" "New York" "New York" ...
## $ Cooperator Zip Code : chr [1:235] NA "10467" "10029" NA ...
## $ Ownership Type : chr [1:235] "Not for Profit Corporation" "Not for Profit Corporation" "Not for Profit Corporation" "Business Corporation" ...
## $ Facility Latitude : num [1:235] 40.9 40.8 40.8 40.7 40.8 ...
## $ Facility Longitude : num [1:235] -73.9 -73.8 -74 -73.9 -73.9 ...
## $ Facility Location : chr [1:235] "(40.884361, -73.888451)" "(40.840431, -73.848244)" "(40.805912, -73.961639)" "(40.726879, -73.871681)" ...
## - 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>#filter missing values
nyc_health_facilities_filtered <- nyc_health_facilities %>%
filter(!is.na(`Facility Longitude`) & !is.na(`Facility Latitude`))
#convert to sf
nyc_health_facilities_sf <- st_as_sf(nyc_health_facilities_filtered, coords = c("Facility Longitude", "Facility Latitude"), crs = st_crs(zip_sf))
#change CRS
nyc_health_facilities_sf <- st_transform(nyc_health_facilities_sf, 4326)
#aggregate
health_facilities_agr <- zip_sf %>%
mutate(tract_area = st_area(geometry)) %>%
st_transform(4326) %>%
st_join(nyc_health_facilities_sf) %>%
group_by(ZIPCODE) %>%
summarize(n_facilities = n(),
tract_area = max(tract_area))
mapview(health_facilities_agr, z_col='n_facilities',legend=FALSE)4.Join the Census ACS population, race, and age data to the NYC Planning Census Tract Data.
#read in data
nyc_tracts_sf <- st_read('Data/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/jamesreo/Desktop/R Independent Study/Weeks 7-9/Session 8/R-spatial/Data/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_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" ...#Read in data
acs_data <- read_csv("Data/R-Spatial_II_Lab/acs_survey_renamed.csv", show_col_types = FALSE)
str(acs_data)## spc_tbl_ [2,168 × 358] (S3: spec_tbl_df/tbl_df/tbl/data.frame)
## $ GEO_ID : chr [1:2168] "id" "1400000US36005000100" "1400000US36005000200" "1400000US36005000400" ...
## $ NAME : chr [1:2168] "Geographic Area Name" "Census Tract 1, Bronx County, New York" "Census Tract 2, Bronx County, New York" "Census Tract 4, Bronx County, New York" ...
## $ DP05_0031PM: chr [1:2168] "Percent Margin of Error!!SEX AND AGE!!Total population!!65 years and over!!Female" "50.4" "9.5" "8.8" ...
## $ DP05_0032E : chr [1:2168] "Estimate!!SEX AND AGE!!Total population!!65 years and over!!Sex ratio (males per 100 females)" "200" "95.1" "91.4" ...
## $ DP05_0032M : chr [1:2168] "Margin of Error!!SEX AND AGE!!Total population!!65 years and over!!Sex ratio (males per 100 females)" "1316" "37.2" "32.7" ...
## $ DP05_0032PE: chr [1:2168] "Percent Estimate!!SEX AND AGE!!Total population!!65 years and over!!Sex ratio (males per 100 females)" "(X)" "(X)" "(X)" ...
## $ DP05_0032PM: chr [1:2168] "Percent Margin of Error!!SEX AND AGE!!Total population!!65 years and over!!Sex ratio (males per 100 females)" "(X)" "(X)" "(X)" ...
## $ DP05_0033E : chr [1:2168] "Estimate!!RACE!!Total population" "7080" "4542" "5634" ...
## $ DP05_0033M : chr [1:2168] "Margin of Error!!RACE!!Total population" "290" "574" "517" ...
## $ DP05_0033PE: chr [1:2168] "Percent Estimate!!RACE!!Total population" "7080" "4542" "5634" ...
## $ DP05_0033PM: chr [1:2168] "Percent Margin of Error!!RACE!!Total population" "(X)" "(X)" "(X)" ...
## $ DP05_0034E : chr [1:2168] "Estimate!!RACE!!Total population!!One race" "7012" "4349" "5425" ...
## $ DP05_0034M : chr [1:2168] "Margin of Error!!RACE!!Total population!!One race" "289" "557" "532" ...
## $ DP05_0034PE: chr [1:2168] "Percent Estimate!!RACE!!Total population!!One race" "99" "95.8" "96.3" ...
## $ DP05_0034PM: chr [1:2168] "Percent Margin of Error!!RACE!!Total population!!One race" "0.6" "3.4" "2.1" ...
## $ DP05_0035E : chr [1:2168] "Estimate!!RACE!!Total population!!Two or more races" "68" "193" "209" ...
## $ DP05_0035M : chr [1:2168] "Margin of Error!!RACE!!Total population!!Two or more races" "42" "155" "117" ...
## $ DP05_0035PE: chr [1:2168] "Percent Estimate!!RACE!!Total population!!Two or more races" "1" "4.2" "3.7" ...
## $ DP05_0035PM: chr [1:2168] "Percent Margin of Error!!RACE!!Total population!!Two or more races" "0.6" "3.4" "2.1" ...
## $ DP05_0036E : chr [1:2168] "Estimate!!RACE!!Total population!!One race" "7012" "4349" "5425" ...
## $ DP05_0036M : chr [1:2168] "Margin of Error!!RACE!!Total population!!One race" "289" "557" "532" ...
## $ DP05_0036PE: chr [1:2168] "Percent Estimate!!RACE!!Total population!!One race" "99" "95.8" "96.3" ...
## $ DP05_0036PM: chr [1:2168] "Percent Margin of Error!!RACE!!Total population!!One race" "0.6" "3.4" "2.1" ...
## $ DP05_0037E : chr [1:2168] "Estimate!!RACE!!Total population!!One race!!White" "1773" "2165" "2623" ...
## $ DP05_0037M : chr [1:2168] "Margin of Error!!RACE!!Total population!!One race!!White" "248" "547" "427" ...
## $ DP05_0037PE: chr [1:2168] "Percent Estimate!!RACE!!Total population!!One race!!White" "25" "47.7" "46.6" ...
## $ DP05_0037PM: chr [1:2168] "Percent Margin of Error!!RACE!!Total population!!One race!!White" "3.2" "11.1" "7.8" ...
## $ DP05_0038E : chr [1:2168] "Estimate!!RACE!!Total population!!One race!!Black or African American" "4239" "1279" "1699" ...
## $ DP05_0038M : chr [1:2168] "Margin of Error!!RACE!!Total population!!One race!!Black or African American" "286" "472" "432" ...
## $ DP05_0038PE: chr [1:2168] "Percent Estimate!!RACE!!Total population!!One race!!Black or African American" "59.9" "28.2" "30.2" ...
## $ DP05_0038PM: chr [1:2168] "Percent Margin of Error!!RACE!!Total population!!One race!!Black or African American" "3.5" "10" "6.4" ...
## $ DP05_0039E : chr [1:2168] "Estimate!!RACE!!Total population!!One race!!American Indian and Alaska Native" "25" "0" "30" ...
## $ DP05_0039M : chr [1:2168] "Margin of Error!!RACE!!Total population!!One race!!American Indian and Alaska Native" "24" "12" "33" ...
## $ DP05_0039PE: chr [1:2168] "Percent Estimate!!RACE!!Total population!!One race!!American Indian and Alaska Native" "0.4" "0" "0.5" ...
## $ DP05_0039PM: chr [1:2168] "Percent Margin of Error!!RACE!!Total population!!One race!!American Indian and Alaska Native" "0.3" "0.7" "0.6" ...
## $ DP05_0040E : chr [1:2168] "Estimate!!RACE!!Total population!!One race!!American Indian and Alaska Native!!Cherokee tribal grouping" "0" "0" "0" ...
## $ DP05_0040M : chr [1:2168] "Margin of Error!!RACE!!Total population!!One race!!American Indian and Alaska Native!!Cherokee tribal grouping" "17" "12" "17" ...
## $ DP05_0040PE: chr [1:2168] "Percent Estimate!!RACE!!Total population!!One race!!American Indian and Alaska Native!!Cherokee tribal grouping" "0" "0" "0" ...
## $ DP05_0040PM: chr [1:2168] "Percent Margin of Error!!RACE!!Total population!!One race!!American Indian and Alaska Native!!Cherokee tribal grouping" "0.5" "0.7" "0.6" ...
## $ DP05_0041E : chr [1:2168] "Estimate!!RACE!!Total population!!One race!!American Indian and Alaska Native!!Chippewa tribal grouping" "0" "0" "0" ...
## $ DP05_0041M : chr [1:2168] "Margin of Error!!RACE!!Total population!!One race!!American Indian and Alaska Native!!Chippewa tribal grouping" "17" "12" "17" ...
## $ DP05_0041PE: chr [1:2168] "Percent Estimate!!RACE!!Total population!!One race!!American Indian and Alaska Native!!Chippewa tribal grouping" "0" "0" "0" ...
## $ DP05_0041PM: chr [1:2168] "Percent Margin of Error!!RACE!!Total population!!One race!!American Indian and Alaska Native!!Chippewa tribal grouping" "0.5" "0.7" "0.6" ...
## $ DP05_0042E : chr [1:2168] "Estimate!!RACE!!Total population!!One race!!American Indian and Alaska Native!!Navajo tribal grouping" "0" "0" "0" ...
## $ DP05_0042M : chr [1:2168] "Margin of Error!!RACE!!Total population!!One race!!American Indian and Alaska Native!!Navajo tribal grouping" "17" "12" "17" ...
## $ DP05_0042PE: chr [1:2168] "Percent Estimate!!RACE!!Total population!!One race!!American Indian and Alaska Native!!Navajo tribal grouping" "0" "0" "0" ...
## $ DP05_0042PM: chr [1:2168] "Percent Margin of Error!!RACE!!Total population!!One race!!American Indian and Alaska Native!!Navajo tribal grouping" "0.5" "0.7" "0.6" ...
## $ DP05_0043E : chr [1:2168] "Estimate!!RACE!!Total population!!One race!!American Indian and Alaska Native!!Sioux tribal grouping" "0" "0" "0" ...
## $ DP05_0043M : chr [1:2168] "Margin of Error!!RACE!!Total population!!One race!!American Indian and Alaska Native!!Sioux tribal grouping" "17" "12" "17" ...
## $ DP05_0043PE: chr [1:2168] "Percent Estimate!!RACE!!Total population!!One race!!American Indian and Alaska Native!!Sioux tribal grouping" "0" "0" "0" ...
## $ DP05_0043PM: chr [1:2168] "Percent Margin of Error!!RACE!!Total population!!One race!!American Indian and Alaska Native!!Sioux tribal grouping" "0.5" "0.7" "0.6" ...
## $ DP05_0044E : chr [1:2168] "Estimate!!RACE!!Total population!!One race!!Asian" "125" "104" "226" ...
## $ DP05_0044M : chr [1:2168] "Margin of Error!!RACE!!Total population!!One race!!Asian" "51" "87" "155" ...
## $ DP05_0044PE: chr [1:2168] "Percent Estimate!!RACE!!Total population!!One race!!Asian" "1.8" "2.3" "4" ...
## $ DP05_0044PM: chr [1:2168] "Percent Margin of Error!!RACE!!Total population!!One race!!Asian" "0.7" "2" "2.7" ...
## $ DP05_0045E : chr [1:2168] "Estimate!!RACE!!Total population!!One race!!Asian!!Asian Indian" "35" "40" "20" ...
## $ DP05_0045M : chr [1:2168] "Margin of Error!!RACE!!Total population!!One race!!Asian!!Asian Indian" "31" "64" "31" ...
## $ DP05_0045PE: chr [1:2168] "Percent Estimate!!RACE!!Total population!!One race!!Asian!!Asian Indian" "0.5" "0.9" "0.4" ...
## $ DP05_0045PM: chr [1:2168] "Percent Margin of Error!!RACE!!Total population!!One race!!Asian!!Asian Indian" "0.4" "1.4" "0.5" ...
## $ DP05_0046E : chr [1:2168] "Estimate!!RACE!!Total population!!One race!!Asian!!Chinese" "54" "0" "171" ...
## $ DP05_0046M : chr [1:2168] "Margin of Error!!RACE!!Total population!!One race!!Asian!!Chinese" "46" "12" "142" ...
## $ DP05_0046PE: chr [1:2168] "Percent Estimate!!RACE!!Total population!!One race!!Asian!!Chinese" "0.8" "0" "3" ...
## $ DP05_0046PM: chr [1:2168] "Percent Margin of Error!!RACE!!Total population!!One race!!Asian!!Chinese" "0.6" "0.7" "2.5" ...
## $ DP05_0047E : chr [1:2168] "Estimate!!RACE!!Total population!!One race!!Asian!!Filipino" "0" "0" "23" ...
## $ DP05_0047M : chr [1:2168] "Margin of Error!!RACE!!Total population!!One race!!Asian!!Filipino" "17" "12" "36" ...
## $ DP05_0047PE: chr [1:2168] "Percent Estimate!!RACE!!Total population!!One race!!Asian!!Filipino" "0" "0" "0.4" ...
## $ DP05_0047PM: chr [1:2168] "Percent Margin of Error!!RACE!!Total population!!One race!!Asian!!Filipino" "0.5" "0.7" "0.6" ...
## $ DP05_0048E : chr [1:2168] "Estimate!!RACE!!Total population!!One race!!Asian!!Japanese" "0" "40" "0" ...
## $ DP05_0048M : chr [1:2168] "Margin of Error!!RACE!!Total population!!One race!!Asian!!Japanese" "17" "55" "17" ...
## $ DP05_0048PE: chr [1:2168] "Percent Estimate!!RACE!!Total population!!One race!!Asian!!Japanese" "0" "0.9" "0" ...
## $ DP05_0048PM: chr [1:2168] "Percent Margin of Error!!RACE!!Total population!!One race!!Asian!!Japanese" "0.5" "1.2" "0.6" ...
## $ DP05_0049E : chr [1:2168] "Estimate!!RACE!!Total population!!One race!!Asian!!Korean" "4" "0" "0" ...
## $ DP05_0049M : chr [1:2168] "Margin of Error!!RACE!!Total population!!One race!!Asian!!Korean" "7" "12" "17" ...
## $ DP05_0049PE: chr [1:2168] "Percent Estimate!!RACE!!Total population!!One race!!Asian!!Korean" "0.1" "0" "0" ...
## $ DP05_0049PM: chr [1:2168] "Percent Margin of Error!!RACE!!Total population!!One race!!Asian!!Korean" "0.1" "0.7" "0.6" ...
## $ DP05_0050E : chr [1:2168] "Estimate!!RACE!!Total population!!One race!!Asian!!Vietnamese" "0" "0" "12" ...
## $ DP05_0050M : chr [1:2168] "Margin of Error!!RACE!!Total population!!One race!!Asian!!Vietnamese" "17" "12" "19" ...
## $ DP05_0050PE: chr [1:2168] "Percent Estimate!!RACE!!Total population!!One race!!Asian!!Vietnamese" "0" "0" "0.2" ...
## $ DP05_0050PM: chr [1:2168] "Percent Margin of Error!!RACE!!Total population!!One race!!Asian!!Vietnamese" "0.5" "0.7" "0.3" ...
## $ DP05_0051E : chr [1:2168] "Estimate!!RACE!!Total population!!One race!!Asian!!Other Asian" "32" "24" "0" ...
## $ DP05_0051M : chr [1:2168] "Margin of Error!!RACE!!Total population!!One race!!Asian!!Other Asian" "30" "45" "17" ...
## $ DP05_0051PE: chr [1:2168] "Percent Estimate!!RACE!!Total population!!One race!!Asian!!Other Asian" "0.5" "0.5" "0" ...
## $ DP05_0051PM: chr [1:2168] "Percent Margin of Error!!RACE!!Total population!!One race!!Asian!!Other Asian" "0.4" "1" "0.6" ...
## $ DP05_0052E : chr [1:2168] "Estimate!!RACE!!Total population!!One race!!Native Hawaiian and Other Pacific Islander" "0" "0" "0" ...
## $ DP05_0052M : chr [1:2168] "Margin of Error!!RACE!!Total population!!One race!!Native Hawaiian and Other Pacific Islander" "17" "12" "17" ...
## $ DP05_0052PE: chr [1:2168] "Percent Estimate!!RACE!!Total population!!One race!!Native Hawaiian and Other Pacific Islander" "0" "0" "0" ...
## $ DP05_0052PM: chr [1:2168] "Percent Margin of Error!!RACE!!Total population!!One race!!Native Hawaiian and Other Pacific Islander" "0.5" "0.7" "0.6" ...
## $ DP05_0053E : chr [1:2168] "Estimate!!RACE!!Total population!!One race!!Native Hawaiian and Other Pacific Islander!!Native Hawaiian" "0" "0" "0" ...
## $ DP05_0053M : chr [1:2168] "Margin of Error!!RACE!!Total population!!One race!!Native Hawaiian and Other Pacific Islander!!Native Hawaiian" "17" "12" "17" ...
## $ DP05_0053PE: chr [1:2168] "Percent Estimate!!RACE!!Total population!!One race!!Native Hawaiian and Other Pacific Islander!!Native Hawaiian" "0" "0" "0" ...
## $ DP05_0053PM: chr [1:2168] "Percent Margin of Error!!RACE!!Total population!!One race!!Native Hawaiian and Other Pacific Islander!!Native Hawaiian" "0.5" "0.7" "0.6" ...
## $ DP05_0054E : chr [1:2168] "Estimate!!RACE!!Total population!!One race!!Native Hawaiian and Other Pacific Islander!!Guamanian or Chamorro" "0" "0" "0" ...
## $ DP05_0054M : chr [1:2168] "Margin of Error!!RACE!!Total population!!One race!!Native Hawaiian and Other Pacific Islander!!Guamanian or Chamorro" "17" "12" "17" ...
## $ DP05_0054PE: chr [1:2168] "Percent Estimate!!RACE!!Total population!!One race!!Native Hawaiian and Other Pacific Islander!!Guamanian or Chamorro" "0" "0" "0" ...
## $ DP05_0054PM: chr [1:2168] "Percent Margin of Error!!RACE!!Total population!!One race!!Native Hawaiian and Other Pacific Islander!!Guamanian or Chamorro" "0.5" "0.7" "0.6" ...
## $ DP05_0055E : chr [1:2168] "Estimate!!RACE!!Total population!!One race!!Native Hawaiian and Other Pacific Islander!!Samoan" "0" "0" "0" ...
## $ DP05_0055M : chr [1:2168] "Margin of Error!!RACE!!Total population!!One race!!Native Hawaiian and Other Pacific Islander!!Samoan" "17" "12" "17" ...
## $ DP05_0055PE: chr [1:2168] "Percent Estimate!!RACE!!Total population!!One race!!Native Hawaiian and Other Pacific Islander!!Samoan" "0" "0" "0" ...
## $ DP05_0055PM: chr [1:2168] "Percent Margin of Error!!RACE!!Total population!!One race!!Native Hawaiian and Other Pacific Islander!!Samoan" "0.5" "0.7" "0.6" ...
## [list output truncated]
## - attr(*, "spec")=
## .. cols(
## .. 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_character(),
## .. DP05_0033M = col_character(),
## .. DP05_0033PE = col_character(),
## .. DP05_0033PM = col_character(),
## .. DP05_0034E = col_character(),
## .. DP05_0034M = col_character(),
## .. DP05_0034PE = col_character(),
## .. DP05_0034PM = col_character(),
## .. DP05_0035E = col_character(),
## .. DP05_0035M = col_character(),
## .. DP05_0035PE = col_character(),
## .. DP05_0035PM = col_character(),
## .. DP05_0036E = col_character(),
## .. DP05_0036M = col_character(),
## .. DP05_0036PE = col_character(),
## .. DP05_0036PM = col_character(),
## .. DP05_0037E = col_character(),
## .. DP05_0037M = col_character(),
## .. DP05_0037PE = col_character(),
## .. DP05_0037PM = col_character(),
## .. DP05_0038E = col_character(),
## .. DP05_0038M = col_character(),
## .. DP05_0038PE = col_character(),
## .. DP05_0038PM = col_character(),
## .. DP05_0039E = col_character(),
## .. DP05_0039M = col_character(),
## .. DP05_0039PE = col_character(),
## .. DP05_0039PM = col_character(),
## .. DP05_0040E = col_character(),
## .. DP05_0040M = col_character(),
## .. DP05_0040PE = col_character(),
## .. DP05_0040PM = col_character(),
## .. DP05_0041E = col_character(),
## .. DP05_0041M = col_character(),
## .. DP05_0041PE = col_character(),
## .. DP05_0041PM = col_character(),
## .. DP05_0042E = col_character(),
## .. DP05_0042M = col_character(),
## .. DP05_0042PE = col_character(),
## .. DP05_0042PM = col_character(),
## .. DP05_0043E = col_character(),
## .. DP05_0043M = col_character(),
## .. DP05_0043PE = col_character(),
## .. DP05_0043PM = col_character(),
## .. DP05_0044E = col_character(),
## .. DP05_0044M = col_character(),
## .. DP05_0044PE = col_character(),
## .. DP05_0044PM = col_character(),
## .. DP05_0045E = col_character(),
## .. DP05_0045M = col_character(),
## .. DP05_0045PE = col_character(),
## .. DP05_0045PM = col_character(),
## .. DP05_0046E = col_character(),
## .. DP05_0046M = col_character(),
## .. DP05_0046PE = col_character(),
## .. DP05_0046PM = col_character(),
## .. DP05_0047E = col_character(),
## .. DP05_0047M = col_character(),
## .. DP05_0047PE = col_character(),
## .. DP05_0047PM = col_character(),
## .. DP05_0048E = col_character(),
## .. DP05_0048M = col_character(),
## .. DP05_0048PE = col_character(),
## .. DP05_0048PM = col_character(),
## .. DP05_0049E = col_character(),
## .. DP05_0049M = col_character(),
## .. DP05_0049PE = col_character(),
## .. DP05_0049PM = col_character(),
## .. DP05_0050E = col_character(),
## .. DP05_0050M = col_character(),
## .. DP05_0050PE = col_character(),
## .. DP05_0050PM = col_character(),
## .. DP05_0051E = col_character(),
## .. DP05_0051M = col_character(),
## .. DP05_0051PE = col_character(),
## .. DP05_0051PM = col_character(),
## .. DP05_0052E = col_character(),
## .. DP05_0052M = col_character(),
## .. DP05_0052PE = col_character(),
## .. DP05_0052PM = col_character(),
## .. DP05_0053E = col_character(),
## .. DP05_0053M = col_character(),
## .. DP05_0053PE = col_character(),
## .. DP05_0053PM = col_character(),
## .. DP05_0054E = col_character(),
## .. DP05_0054M = col_character(),
## .. DP05_0054PE = col_character(),
## .. DP05_0054PM = col_character(),
## .. DP05_0055E = col_character(),
## .. DP05_0055M = col_character(),
## .. DP05_0055PE = col_character(),
## .. DP05_0055PM = col_character(),
## .. DP05_0056E = col_character(),
## .. DP05_0056M = col_character(),
## .. DP05_0056PE = col_character(),
## .. DP05_0056PM = col_character(),
## .. DP05_0057E = col_character(),
## .. DP05_0057M = col_character(),
## .. DP05_0057PE = col_character(),
## .. DP05_0057PM = col_character(),
## .. DP05_0058E = col_character(),
## .. DP05_0058M = col_character(),
## .. DP05_0058PE = col_character(),
## .. DP05_0058PM = col_character(),
## .. DP05_0059E = col_character(),
## .. DP05_0059M = col_character(),
## .. DP05_0059PE = col_character(),
## .. DP05_0059PM = col_character(),
## .. DP05_0060E = col_character(),
## .. DP05_0060M = col_character(),
## .. DP05_0060PE = col_character(),
## .. DP05_0060PM = col_character(),
## .. DP05_0061E = col_character(),
## .. DP05_0061M = col_character(),
## .. DP05_0061PE = col_character(),
## .. DP05_0061PM = col_character(),
## .. DP05_0062E = col_character(),
## .. DP05_0062M = col_character(),
## .. DP05_0062PE = col_character(),
## .. DP05_0062PM = col_character(),
## .. DP05_0063E = col_character(),
## .. DP05_0063M = col_character(),
## .. DP05_0063PE = col_character(),
## .. DP05_0063PM = col_character(),
## .. DP05_0064E = col_character(),
## .. DP05_0064M = col_character(),
## .. DP05_0064PE = col_character(),
## .. DP05_0064PM = col_character(),
## .. DP05_0065E = col_character(),
## .. DP05_0065M = col_character(),
## .. DP05_0065PE = col_character(),
## .. DP05_0065PM = col_character(),
## .. DP05_0066E = col_character(),
## .. DP05_0066M = col_character(),
## .. DP05_0066PE = col_character(),
## .. DP05_0066PM = col_character(),
## .. DP05_0067E = col_character(),
## .. DP05_0067M = col_character(),
## .. DP05_0067PE = col_character(),
## .. DP05_0067PM = col_character(),
## .. DP05_0068E = col_character(),
## .. DP05_0068M = col_character(),
## .. DP05_0068PE = col_character(),
## .. DP05_0068PM = col_character(),
## .. DP05_0069E = col_character(),
## .. DP05_0069M = col_character(),
## .. DP05_0069PE = col_character(),
## .. DP05_0069PM = col_character(),
## .. DP05_0070E = col_character(),
## .. DP05_0070M = col_character(),
## .. DP05_0070PE = col_character(),
## .. DP05_0070PM = col_character(),
## .. DP05_0071E = col_character(),
## .. DP05_0071M = col_character(),
## .. DP05_0071PE = col_character(),
## .. DP05_0071PM = col_character(),
## .. DP05_0072E = col_character(),
## .. DP05_0072M = col_character(),
## .. DP05_0072PE = col_character(),
## .. DP05_0072PM = col_character(),
## .. DP05_0073E = col_character(),
## .. DP05_0073M = col_character(),
## .. DP05_0073PE = col_character(),
## .. DP05_0073PM = col_character(),
## .. DP05_0074E = col_character(),
## .. DP05_0074M = col_character(),
## .. DP05_0074PE = col_character(),
## .. DP05_0074PM = col_character(),
## .. DP05_0075E = col_character(),
## .. DP05_0075M = col_character(),
## .. DP05_0075PE = col_character(),
## .. DP05_0075PM = col_character(),
## .. DP05_0076E = col_character(),
## .. DP05_0076M = col_character(),
## .. DP05_0076PE = col_character(),
## .. DP05_0076PM = col_character(),
## .. DP05_0077E = col_character(),
## .. DP05_0077M = col_character(),
## .. DP05_0077PE = col_character(),
## .. DP05_0077PM = col_character(),
## .. DP05_0078E = col_character(),
## .. DP05_0078M = col_character(),
## .. DP05_0078PE = col_character(),
## .. DP05_0078PM = col_character(),
## .. DP05_0079E = col_character(),
## .. DP05_0079M = col_character(),
## .. DP05_0079PE = col_character(),
## .. DP05_0079PM = col_character(),
## .. DP05_0080E = col_character(),
## .. DP05_0080M = col_character(),
## .. DP05_0080PE = col_character(),
## .. DP05_0080PM = col_character(),
## .. DP05_0081E = col_character(),
## .. DP05_0081M = col_character(),
## .. DP05_0081PE = col_character(),
## .. DP05_0081PM = col_character(),
## .. DP05_0082E = col_character(),
## .. DP05_0082M = col_character(),
## .. DP05_0082PE = col_character(),
## .. DP05_0082PM = col_character(),
## .. DP05_0083E = col_character(),
## .. DP05_0083M = col_character(),
## .. DP05_0083PE = col_character(),
## .. DP05_0083PM = col_character(),
## .. DP05_0084E = col_character(),
## .. DP05_0084M = col_character(),
## .. DP05_0084PE = col_character(),
## .. DP05_0084PM = col_character(),
## .. DP05_0085E = col_character(),
## .. DP05_0085M = col_character(),
## .. DP05_0085PE = col_character(),
## .. DP05_0085PM = col_character(),
## .. DP05_0086E = col_character(),
## .. DP05_0086M = col_character(),
## .. DP05_0086PE = col_character(),
## .. DP05_0086PM = col_character(),
## .. DP05_0087E = col_character(),
## .. DP05_0087M = col_character(),
## .. DP05_0087PE = col_character(),
## .. DP05_0087PM = col_character(),
## .. DP05_0088E = col_character(),
## .. DP05_0088M = col_character(),
## .. DP05_0088PE = col_character(),
## .. DP05_0088PM = col_character(),
## .. DP05_0089E = col_character(),
## .. DP05_0089M = col_character(),
## .. DP05_0089PE = col_character(),
## .. DP05_0089PM = col_character(),
## .. DP05_0001E = col_character(),
## .. DP05_0001M = col_character(),
## .. DP05_0001PE = col_character(),
## .. DP05_0001PM = col_character(),
## .. DP05_0002E = col_character(),
## .. DP05_0002M = col_character(),
## .. DP05_0002PE = col_character(),
## .. DP05_0002PM = col_character(),
## .. DP05_0003E = col_character(),
## .. DP05_0003M = col_character(),
## .. 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_character(),
## .. DP05_0005M = col_character(),
## .. DP05_0005PE = col_character(),
## .. DP05_0005PM = col_character(),
## .. DP05_0006E = col_character(),
## .. DP05_0006M = col_character(),
## .. DP05_0006PE = col_character(),
## .. DP05_0006PM = col_character(),
## .. DP05_0007E = col_character(),
## .. DP05_0007M = col_character(),
## .. DP05_0007PE = col_character(),
## .. DP05_0007PM = col_character(),
## .. DP05_0008E = col_character(),
## .. DP05_0008M = col_character(),
## .. DP05_0008PE = col_character(),
## .. DP05_0008PM = col_character(),
## .. DP05_0009E = col_character(),
## .. DP05_0009M = col_character(),
## .. DP05_0009PE = col_character(),
## .. DP05_0009PM = col_character(),
## .. DP05_0010E = col_character(),
## .. DP05_0010M = col_character(),
## .. DP05_0010PE = col_character(),
## .. DP05_0010PM = col_character(),
## .. DP05_0011E = col_character(),
## .. DP05_0011M = col_character(),
## .. DP05_0011PE = col_character(),
## .. DP05_0011PM = col_character(),
## .. DP05_0012E = col_character(),
## .. DP05_0012M = col_character(),
## .. DP05_0012PE = col_character(),
## .. DP05_0012PM = col_character(),
## .. DP05_0013E = col_character(),
## .. DP05_0013M = col_character(),
## .. DP05_0013PE = col_character(),
## .. DP05_0013PM = col_character(),
## .. DP05_0014E = col_character(),
## .. DP05_0014M = col_character(),
## .. DP05_0014PE = col_character(),
## .. DP05_0014PM = col_character(),
## .. DP05_0015E = col_character(),
## .. DP05_0015M = col_character(),
## .. DP05_0015PE = col_character(),
## .. DP05_0015PM = col_character(),
## .. DP05_0016E = col_character(),
## .. DP05_0016M = col_character(),
## .. DP05_0016PE = col_character(),
## .. DP05_0016PM = col_character(),
## .. DP05_0017E = col_character(),
## .. DP05_0017M = col_character(),
## .. 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_character(),
## .. DP05_0019M = col_character(),
## .. DP05_0019PE = col_character(),
## .. DP05_0019PM = col_character(),
## .. DP05_0020E = col_character(),
## .. DP05_0020M = col_character(),
## .. DP05_0020PE = col_character(),
## .. DP05_0020PM = col_character(),
## .. DP05_0021E = col_character(),
## .. DP05_0021M = col_character(),
## .. DP05_0021PE = col_character(),
## .. DP05_0021PM = col_character(),
## .. DP05_0022E = col_character(),
## .. DP05_0022M = col_character(),
## .. DP05_0022PE = col_character(),
## .. DP05_0022PM = col_character(),
## .. DP05_0023E = col_character(),
## .. DP05_0023M = col_character(),
## .. DP05_0023PE = col_character(),
## .. DP05_0023PM = col_character(),
## .. DP05_0024E = col_character(),
## .. DP05_0024M = col_character(),
## .. DP05_0024PE = col_character(),
## .. DP05_0024PM = col_character(),
## .. DP05_0025E = col_character(),
## .. DP05_0025M = col_character(),
## .. DP05_0025PE = col_character(),
## .. DP05_0025PM = col_character(),
## .. DP05_0026E = col_character(),
## .. DP05_0026M = col_character(),
## .. DP05_0026PE = col_character(),
## .. DP05_0026PM = col_character(),
## .. DP05_0027E = col_character(),
## .. DP05_0027M = col_character(),
## .. 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_character(),
## .. DP05_0029M = col_character(),
## .. DP05_0029PE = col_character(),
## .. DP05_0029PM = col_character(),
## .. DP05_0030E = col_character(),
## .. DP05_0030M = col_character(),
## .. DP05_0030PE = col_character(),
## .. DP05_0030PM = col_character(),
## .. DP05_0031E = col_character(),
## .. DP05_0031M = col_character(),
## .. DP05_0031PE = col_character()
## .. )
## - attr(*, "problems")=<externalptr>