TUGAS 3 PRAKTIKUM STA581

Load Package

library(sf)
library(ggplot2)
library(tigris)
library(dplyr)

Reading Spatial Data

Admin3Kecamatan<-"C:/Admin3Kecamatan/idn_admbnda_adm3_bps_20200401.shp"

Seperti apa file SHP tersebut di R, bisa memakai fungsi glimpse dari Package dplyr

glimpse(Admin3Kecamatan)

 chr "C:/Admin3Kecamatan/idn_admbnda_adm3_bps_20200401.shp"

Perlu merubahnya menjadi melalui fungsi ‘st_read’ dari Package ‘sf’

Admin3<-st_read(Admin3Kecamatan)

Reading layer `idn_admbnda_adm3_bps_20200401' from data source 
  `C:\Admin3Kecamatan\idn_admbnda_adm3_bps_20200401.shp' using driver `ESRI Shapefile'
Simple feature collection with 7069 features and 16 fields
Geometry type: MULTIPOLYGON
Dimension:     XY
Bounding box:  xmin: 95.01079 ymin: -11.00762 xmax: 141.0194 ymax: 6.07693
Geodetic CRS:  WGS 84

glimpse(Admin3)

Rows: 7,069
Columns: 17
$ Shape_Leng <dbl> 0.2798656, 0.7514001, 0.6900061, 0.6483629, 0.2437073, 1.35~
$ Shape_Area <dbl> 0.003107633, 0.016925540, 0.024636382, 0.010761277, 0.00116~
$ ADM3_EN    <chr> "2 X 11 Enam Lingkung", "2 X 11 Kayu Tanam", "Abab", "Abang~
$ ADM3_PCODE <chr> "ID1306050", "ID1306052", "ID1612030", "ID5107050", "ID7471~
$ ADM3_REF   <chr> NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA,~
$ ADM3ALT1EN <chr> NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA,~
$ ADM3ALT2EN <chr> NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA,~
$ ADM2_EN    <chr> "Padang Pariaman", "Padang Pariaman", "Penukal Abab Lematan~
$ ADM2_PCODE <chr> "ID1306", "ID1306", "ID1612", "ID5107", "ID7471", "ID9432",~
$ ADM1_EN    <chr> "Sumatera Barat", "Sumatera Barat", "Sumatera Selatan", "Ba~
$ ADM1_PCODE <chr> "ID13", "ID13", "ID16", "ID51", "ID74", "ID94", "ID94", "ID~
$ ADM0_EN    <chr> "Indonesia", "Indonesia", "Indonesia", "Indonesia", "Indone~
$ ADM0_PCODE <chr> "ID", "ID", "ID", "ID", "ID", "ID", "ID", "ID", "ID", "ID",~
$ date       <date> 2019-12-20, 2019-12-20, 2019-12-20, 2019-12-20, 2019-12-20~
$ validOn    <date> 2020-04-01, 2020-04-01, 2020-04-01, 2020-04-01, 2020-04-01~
$ validTo    <date> NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA~
$ geometry   <MULTIPOLYGON [°]> MULTIPOLYGON (((100.2811 -0..., MULTIPOLYGON (~

Memasukkan Data via File CSV

MayongKecamatan<-read.csv("C:/Admin3Kecamatan/idn_admbnda_adm3_bps_20200401.csv", header=TRUE, sep=";")
MayongKecamatan

   Shape_Leng  Shape_Area     ADM3_EN ADM3_PCODE  ADM2_EN ADM2_PCODE
1 0,372759694 0,003650121    Adimulyo  ID3305150  Kebumen     ID3305
2 0,444395499 0,006079204     Adipala  ID3301150  Cilacap     ID3301
3 0,390257247 0,002185526    Adiwerna  ID3328120    Tegal     ID3328
4 0,419229316 0,005623467   Ajibarang  ID3302140 Banyumas     ID3302
5 0,439972345 0,004725463       Alian  ID3305110  Kebumen     ID3305
6 0,433768738 0,005262669       Ambal  ID3305070  Kebumen     ID3305
7 0,269274639 0,002261475    Ambarawa  ID3322100 Semarang     ID3322
8 0,790341341 0,008031387       Ampel  ID3309020 Boyolali     ID3309
9 0,587343424 0,004548679 Ampelgading  ID3327110 Pemalang     ID3327
      ADM1_EN DATA
1 Jawa Tengah   NA
2 Jawa Tengah   NA
3 Jawa Tengah   NA
4 Jawa Tengah   NA
5 Jawa Tengah   NA
6 Jawa Tengah   NA
7 Jawa Tengah   NA
8 Jawa Tengah   NA
9 Jawa Tengah   NA
 [ reached 'max' / getOption("max.print") -- omitted 568 rows ]

Merge Data

merged_MayongKecamatan <- geo_join(spatial_data=Admin3, 
                                  data_frame=MayongKecamatan, by_sp="ADM3_PCODE", 
                                  by_df="ADM3_PCODE", how = "inner")

Atur Warna

mycol <- c("green", "yellow", "red", "red4")

Menampilkan Plot Peta Chloropleth

pDATA<-ggplot()+
  geom_sf(data=merged_MayongKecamatan,aes(fill=DATA))+
  scale_fill_gradientn(colours=mycol)+
  labs(title="Mayong dan Jepara")
pDATA