Problem 5 - Mapping Trials

library(foreign)
library(readxl)

## Warning: package 'readxl' was built under R version 3.4.4

datapenn <- read_excel("F:/HU/ANLY 512/Problem Set 5/pennsylv/pennsylv.dbf.xlsx")
names(datapenn)

##   [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"

library(ggmap)

## Warning: package 'ggmap' was built under R version 3.4.4

## Loading required package: ggplot2

## Warning: package 'ggplot2' was built under R version 3.4.4

ACC Trauma Hospitals in PA

acc_trauma <- subset(datapenn, acc_trauma=="Y")
qmplot(x, y, data = acc_trauma, legend = "none", colour= I('blue'), mapcolor = "color", extent = "panel",darken = 0.1, main = "ACC Trauma Hospitals in PA", xlab = "Longitude", ylab = "Latitude", source = 'google', maptype = 'terrain', size = I(3), zoom = 6)

## Map from URL : http://maps.googleapis.com/maps/api/staticmap?center=40.995052,-77.505472&zoom=6&size=640x640&scale=2&maptype=terrain&language=en-EN&sensor=false

We observe that most of the ACC Trauma Hospitals are concentrate around Philadelphia.

Surgical Hospitals in PA

surgical <- subset(datapenn, surgical=="Y")
qmplot(x, y, data = surgical, legend = "none", colour= I('blue'), mapcolor = "color", extent = "panel",darken = 0.1, main = "Surgical Hospitals in PA", xlab = "Longitude", ylab = "Latitude", source = 'google', maptype = 'terrain', size = I(2), zoom = 7)

## Map from URL : http://maps.googleapis.com/maps/api/staticmap?center=40.995052,-77.729609&zoom=7&size=640x640&scale=2&maptype=terrain&language=en-EN&sensor=false

We observe that surgical hosiptals are spread out across Pennsylvania with a more important concentration in the East. The density is more important around bigger cities like Philadelphia and Pittsburgh.

Hospitals with Chemotherapy in PA

chemo <- subset(datapenn, chemo=="Y")
qmplot(x, y, data = chemo, main = "Hospitals with Chemotherapy in PA",color= I('green'),maptype = "toner-lite", source = 'stamen', zoom = 8)

## Map from URL : http://tile.stamen.com/toner-lite/8/70/94.png

## Map from URL : http://tile.stamen.com/toner-lite/8/71/94.png

## Map from URL : http://tile.stamen.com/toner-lite/8/72/94.png

## Map from URL : http://tile.stamen.com/toner-lite/8/73/94.png

## Map from URL : http://tile.stamen.com/toner-lite/8/74/94.png

## Map from URL : http://tile.stamen.com/toner-lite/8/70/95.png

## Map from URL : http://tile.stamen.com/toner-lite/8/71/95.png

## Map from URL : http://tile.stamen.com/toner-lite/8/72/95.png

## Map from URL : http://tile.stamen.com/toner-lite/8/73/95.png

## Map from URL : http://tile.stamen.com/toner-lite/8/74/95.png

## Map from URL : http://tile.stamen.com/toner-lite/8/70/96.png

## Map from URL : http://tile.stamen.com/toner-lite/8/71/96.png

## Map from URL : http://tile.stamen.com/toner-lite/8/72/96.png

## Map from URL : http://tile.stamen.com/toner-lite/8/73/96.png

## Map from URL : http://tile.stamen.com/toner-lite/8/74/96.png

## Map from URL : http://tile.stamen.com/toner-lite/8/70/97.png

## Map from URL : http://tile.stamen.com/toner-lite/8/71/97.png

## Map from URL : http://tile.stamen.com/toner-lite/8/72/97.png

## Map from URL : http://tile.stamen.com/toner-lite/8/73/97.png

## Map from URL : http://tile.stamen.com/toner-lite/8/74/97.png

## Warning: `panel.margin` is deprecated. Please use `panel.spacing` property
## instead

We observe a strong concentration of hospitals with chemotherapy around Phildelphia.

Hospitals with ICU Beds

qmplot(x, y, data = datapenn, size = icu_beds, mdaptype = "toner-lite", color = I("blue")
)

## Using zoom = 8...

## Warning: `panel.margin` is deprecated. Please use `panel.spacing` property
## instead

## Warning: Ignoring unknown parameters: mdaptype

## Warning: Removed 208 rows containing missing values (geom_point).

The most hopsitals with more than 100 ICU beds are in Philadelphia and Pittsburgh. The rest of hospitals across PA have less than 100 ICU beds.

ACC Trauma in Philadelphia

acc_traumaCounty <- subset(acc_trauma, county=="Philadelphia")
qmplot(x, y, data = acc_traumaCounty, legend = "none", colour= I('blue'), mapcolor = "color", extent = "panel",darken = 0.1, main = "ACC Trauma Hospitals in Philadelphia", xlab = "Longitude", ylab = "Latitude", source = 'google', maptype = 'roadmap', zoom = 12)

## Map from URL : http://maps.googleapis.com/maps/api/staticmap?center=40.009619,-75.087825&zoom=12&size=640x640&scale=2&maptype=roadmap&language=en-EN&sensor=false