Objectives

Using the spatial visualization techniques, explore this data set on Pennsylvania hospitals (http://www.arcgis.com/home/item.html?id=eccee5dfe01e4c4283c9be0cfc596882). Create a series of 5 maps that highlight spatial differences in hospital service coverage for the state of PA.

To help you in getting the data imported into R, I have included the code below:

To import the data I use the foreign package, if you do not have it than be sure to install it prior to testing the code.

library(foreign)
library(ggplot2)
## Warning: package 'ggplot2' was built under R version 3.6.3
library(ggmap)
## Warning: package 'ggmap' was built under R version 3.6.3
## Google's Terms of Service: https://cloud.google.com/maps-platform/terms/.
## Please cite ggmap if you use it! See citation("ggmap") for details.
dat <- read.dbf("C:/Users/mruga/Desktop/pennsylv.dbf")  # change this to connect to your version

The dataset contains a number of variables about each hospital, many of them are clear and straight forward.

names(dat)
##   [1] "acc_trauma" "air_amb"    "als"        "arc_street" "arc_zone"  
##   [6] "bas_ls"     "bassinets"  "bb_id"      "bc_beds"    "bc_sus_bed"
##  [11] "beds_sus"   "birthing_r" "bone_marro" "burn_car"   "burn_care" 
##  [16] "card_beds"  "card_surge" "card_sus_b" "cardiac"    "cardiac_ca"
##  [21] "cardio_reh" "chemo"      "city"       "clin_lab"   "clin_psych"
##  [26] "county"     "countyname" "ct_scan"    "cty_key"    "cystoscopi"
##  [31] "deliv_rms"  "dental"     "detox_alc_" "diag_radio" "diag_xray" 
##  [36] "doh_hosp"   "doh_phone"  "emer_dept"  "endoscopie" "fac_id"    
##  [41] "facility"   "flu_old"    "fred_con_1" "fred_conta" "fred_email"
##  [46] "fred_fax"   "fred_hosp"  "fred_pager" "fred_phone" "gamma_knif"
##  [51] "gen_outpat" "gene_counc" "heart_tran" "helipad"    "hemodial_c"
##  [56] "hemodial_m" "hosp_id"    "hospice"    "hyper_cham" "icu"       
##  [61] "icu_beds"   "icu_sus_be" "inpat_flu_" "inpat_pneu" "kidney_tra"
##  [66] "labor_rms"  "lic_beds"   "lic_dent"   "lic_dos"    "lic_mds"   
##  [71] "lic_pod"    "linear_acc" "lithotrips" "liver_tran" "loc_method"
##  [76] "ltc"        "mcd"        "mcd_key"    "mcd_name"   "medical"   
##  [81] "mob_ccu"    "mob_icu"    "mri"        "ms1"        "neo2_beds" 
##  [86] "neo2_sus_b" "neo3_beds"  "neo3_sus_b" "neuro_surg" "neurology" 
##  [91] "obs_gyn"    "occ_ther"   "optometry"  "organ_bank" "ped_trauma"
##  [96] "pediatric"  "pet"        "pharmacy"   "phys_med"   "phys_ther" 
## [101] "podiatry"   "providerid" "psych"      "psych_inpa" "reg_trauma"
## [106] "resp_ther"  "so_flu_65u" "social_wor" "speech_pat" "street"    
## [111] "surgical"   "surgical_s" "thera_radi" "typ_org"    "typ_serv"  
## [116] "ultrasound" "x"          "y"          "zip"

Now create 5 maps, including descriptions, that highlight the spatial distribution of hospital services in the state of PA. Upload these maps as a document to rpubs.com and submit that link to the Canvas assignment.

Map 1 shows the distribution of hospitals that do not have an organ bank in Philadelphia

organbank = subset(dat, organ_bank=="N")
organbankPhl = subset(organbank, city == "Philadelphia")
qmplot(x,y, data = organbankPhl, colour = I('blue'), size = I(3), main = "Hospitals in Philadelphia without Organ Bank", xlab = "Longitude", ylab = "Latitude")
## Using zoom = 12...
## Source : http://tile.stamen.com/terrain/12/1191/1549.png
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Map 2 shows all emergency department hospitals in Pennsylvania

emergency <- subset(dat, emer_dept == "Y")
qmplot(x,y,data=emergency,colour=I('blue'),size=I(2), main = "All Hospital Locations in Pennsylvania with emergency department", xlab = "Longitude", ylab = "Latitude")
## Using zoom = 8...
## Source : http://tile.stamen.com/terrain/8/70/94.png
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Map 3 shows all hospitals with Neurosurgery compatibility in Philadlephia.

neurosur = subset(dat, neuro_surg == "Y")
neurosurDA = subset(neurosur, county == "Philadelphia")
qmplot(x,y, data = neurosurDA, colour = I('blue'),size = I(2) , main = "Hospitals in Philadelphia with Neurosurgery capability", xlab = "Longitude", ylab = "Latitude")
## Using zoom = 12...

Map 4 is a density chart showing hospitals with helipad in Pennsylvania

helipad = subset(dat, helipad == "Y")
g <-qmplot(x,y,data=helipad,colour=I('black'),size=I(2), main = "Helipad Density In PA", xlab = "Longitude", ylab = "Latitude")
## Using zoom = 8...
g <- g+stat_density2d(aes(x = x, y = y, fill=..level..), data=helipad,geom="polygon", alpha=0.2)
g + scale_fill_gradient(low = "green", high = "red")

Map 5 shows all the hospitals with chemotherapy capabaility in Philadelphia

chemo = subset(dat, chemo == "Y")
chemoPHLMO = subset(chemo, county == "Philadelphia")
qmplot(x,y, data = chemoPHLMO, colour = I('black'),size = I(3) , main = "Hospitals with Chemotherapy in Philadelphia county", xlab = "Longitude", ylab = "Latitude")
## Using zoom = 12...