Tugas Praktikum 3a dan 3b
Irvanal Haq
9/11/2021
Tugas 3a.
Menjalankan beberapa fungsi SQLite di R seperti inner_join, left_join, right_join, full_join, semi_join, dan anti_join.
# Mengaktifkan library yang dibutuhkan
library(tidyverse)## -- Attaching packages --------------------------------------- tidyverse 1.3.1 --## v ggplot2 3.3.5 v purrr 0.3.4
## v tibble 3.1.4 v dplyr 1.0.7
## v tidyr 1.1.3 v stringr 1.4.0
## v readr 2.0.1 v forcats 0.5.1## -- Conflicts ------------------------------------------ tidyverse_conflicts() --
## x dplyr::filter() masks stats::filter()
## x dplyr::lag() masks stats::lag()library(RSQLite)
library(DBI)
# Koneksi terhadap database
path1 = "E:\\Irvan\\chinook.db"
chinook<-DBI::dbConnect(RSQLite::SQLite(),path1)
class(chinook)## [1] "SQLiteConnection"
## attr(,"package")
## [1] "RSQLite"# Melihat tabel
RSQLite::dbListTables(chinook)## [1] "albums" "artists" "customers" "employees"
## [5] "genres" "invoice_items" "invoices" "media_types"
## [9] "playlist_track" "playlists" "sqlite_sequence" "sqlite_stat1"
## [13] "tracks"# Mengakses Tabel albums
albums<-dplyr::tbl(chinook,"albums")
class(albums)## [1] "tbl_SQLiteConnection" "tbl_dbi" "tbl_sql"
## [4] "tbl_lazy" "tbl"albums## # Source: table<albums> [?? x 3]
## # Database: sqlite 3.36.0 [E:\Irvan\chinook.db]
## AlbumId Title ArtistId
## <int> <chr> <int>
## 1 1 For Those About To Rock We Salute You 1
## 2 2 Balls to the Wall 2
## 3 3 Restless and Wild 2
## 4 4 Let There Be Rock 1
## 5 5 Big Ones 3
## 6 6 Jagged Little Pill 4
## 7 7 Facelift 5
## 8 8 Warner 25 Anos 6
## 9 9 Plays Metallica By Four Cellos 7
## 10 10 Audioslave 8
## # ... with more rows# Mengakses Tabel albums
artists<-dplyr::tbl(chinook,"artists")
class(artists)## [1] "tbl_SQLiteConnection" "tbl_dbi" "tbl_sql"
## [4] "tbl_lazy" "tbl"artists## # Source: table<artists> [?? x 2]
## # Database: sqlite 3.36.0 [E:\Irvan\chinook.db]
## ArtistId Name
## <int> <chr>
## 1 1 AC/DC
## 2 2 Accept
## 3 3 Aerosmith
## 4 4 Alanis Morissette
## 5 5 Alice In Chains
## 6 6 Antônio Carlos Jobim
## 7 7 Apocalyptica
## 8 8 Audioslave
## 9 9 BackBeat
## 10 10 Billy Cobham
## # ... with more rows# Penggunaan inner_join()
inner_join(artists,albums)## Joining, by = "ArtistId"## # Source: lazy query [?? x 4]
## # Database: sqlite 3.36.0 [E:\Irvan\chinook.db]
## ArtistId Name AlbumId Title
## <int> <chr> <int> <chr>
## 1 1 AC/DC 1 For Those About To Rock We Salute You
## 2 2 Accept 2 Balls to the Wall
## 3 2 Accept 3 Restless and Wild
## 4 1 AC/DC 4 Let There Be Rock
## 5 3 Aerosmith 5 Big Ones
## 6 4 Alanis Morissette 6 Jagged Little Pill
## 7 5 Alice In Chains 7 Facelift
## 8 6 Antônio Carlos Jobim 8 Warner 25 Anos
## 9 7 Apocalyptica 9 Plays Metallica By Four Cellos
## 10 8 Audioslave 10 Audioslave
## # ... with more rows# Penggunaan left_join()
left_join(artists,albums)## Joining, by = "ArtistId"## # Source: lazy query [?? x 4]
## # Database: sqlite 3.36.0 [E:\Irvan\chinook.db]
## ArtistId Name AlbumId Title
## <int> <chr> <int> <chr>
## 1 1 AC/DC 1 For Those About To Rock We Salute You
## 2 1 AC/DC 4 Let There Be Rock
## 3 2 Accept 2 Balls to the Wall
## 4 2 Accept 3 Restless and Wild
## 5 3 Aerosmith 5 Big Ones
## 6 4 Alanis Morissette 6 Jagged Little Pill
## 7 5 Alice In Chains 7 Facelift
## 8 6 Antônio Carlos Jobim 8 Warner 25 Anos
## 9 6 Antônio Carlos Jobim 34 Chill: Brazil (Disc 2)
## 10 7 Apocalyptica 9 Plays Metallica By Four Cellos
## # ... with more rows# Penggunaan right_join()
right_join(artists,albums)## Joining, by = "ArtistId"## # Source: lazy query [?? x 4]
## # Database: sqlite 3.36.0 [E:\Irvan\chinook.db]
## ArtistId Name AlbumId Title
## <int> <chr> <int> <chr>
## 1 1 AC/DC 1 For Those About To Rock We Salute You
## 2 2 Accept 2 Balls to the Wall
## 3 2 Accept 3 Restless and Wild
## 4 1 AC/DC 4 Let There Be Rock
## 5 3 Aerosmith 5 Big Ones
## 6 4 Alanis Morissette 6 Jagged Little Pill
## 7 5 Alice In Chains 7 Facelift
## 8 6 Antônio Carlos Jobim 8 Warner 25 Anos
## 9 7 Apocalyptica 9 Plays Metallica By Four Cellos
## 10 8 Audioslave 10 Audioslave
## # ... with more rows# Penggunaan full_join()
full_join(artists,albums)## Joining, by = "ArtistId"## # Source: lazy query [?? x 4]
## # Database: sqlite 3.36.0 [E:\Irvan\chinook.db]
## ArtistId Name AlbumId Title
## <int> <chr> <int> <chr>
## 1 1 AC/DC 1 For Those About To Rock We Salute You
## 2 1 AC/DC 4 Let There Be Rock
## 3 2 Accept 2 Balls to the Wall
## 4 2 Accept 3 Restless and Wild
## 5 3 Aerosmith 5 Big Ones
## 6 4 Alanis Morissette 6 Jagged Little Pill
## 7 5 Alice In Chains 7 Facelift
## 8 6 Antônio Carlos Jobim 8 Warner 25 Anos
## 9 6 Antônio Carlos Jobim 34 Chill: Brazil (Disc 2)
## 10 7 Apocalyptica 9 Plays Metallica By Four Cellos
## # ... with more rows# Penggunaan semi_join
semi_join(artists,albums)## Joining, by = "ArtistId"## # Source: lazy query [?? x 2]
## # Database: sqlite 3.36.0 [E:\Irvan\chinook.db]
## ArtistId Name
## <int> <chr>
## 1 1 AC/DC
## 2 2 Accept
## 3 3 Aerosmith
## 4 4 Alanis Morissette
## 5 5 Alice In Chains
## 6 6 Antônio Carlos Jobim
## 7 7 Apocalyptica
## 8 8 Audioslave
## 9 9 BackBeat
## 10 10 Billy Cobham
## # ... with more rows# Penggunaan anti_join
anti_join(artists,albums)## Joining, by = "ArtistId"## # Source: lazy query [?? x 2]
## # Database: sqlite 3.36.0 [E:\Irvan\chinook.db]
## ArtistId Name
## <int> <chr>
## 1 25 Milton Nascimento & Bebeto
## 2 26 Azymuth
## 3 28 João Gilberto
## 4 29 Bebel Gilberto
## 5 30 Jorge Vercilo
## 6 31 Baby Consuelo
## 7 32 Ney Matogrosso
## 8 33 Luiz Melodia
## 9 34 Nando Reis
## 10 35 Pedro LuÃs & A Parede
## # ... with more rowsTugas 3b. Membuat peta Sulawesi Tenggara
# Mengaktifkan Library yang dibutuhkan
library(shiny)
library(leaflet)
library(RColorBrewer)
library(tidyverse)
library(raster)## Loading required package: sp##
## Attaching package: 'raster'## The following object is masked from 'package:dplyr':
##
## select## The following object is masked from 'package:tidyr':
##
## extractlibrary(sf)## Linking to GEOS 3.9.0, GDAL 3.2.1, PROJ 7.2.1library(sp)
library(scales)##
## Attaching package: 'scales'## The following object is masked from 'package:purrr':
##
## discard## The following object is masked from 'package:readr':
##
## col_factorlibrary(ggsn)## Loading required package: grid##
## Attaching package: 'ggsn'## The following object is masked from 'package:raster':
##
## scalebarlibrary(plotly)##
## Attaching package: 'plotly'## The following object is masked from 'package:raster':
##
## select## The following object is masked from 'package:ggplot2':
##
## last_plot## The following object is masked from 'package:stats':
##
## filter## The following object is masked from 'package:graphics':
##
## layoutlibrary(dbscan)
library(rgdal)## Please note that rgdal will be retired by the end of 2023,
## plan transition to sf/stars/terra functions using GDAL and PROJ
## at your earliest convenience.
##
## rgdal: version: 1.5-25, (SVN revision 1143)
## Geospatial Data Abstraction Library extensions to R successfully loaded
## Loaded GDAL runtime: GDAL 3.2.1, released 2020/12/29
## Path to GDAL shared files: C:/Users/ASUS/Documents/R/win-library/4.1/rgdal/gdal
## GDAL binary built with GEOS: TRUE
## Loaded PROJ runtime: Rel. 7.2.1, January 1st, 2021, [PJ_VERSION: 721]
## Path to PROJ shared files: C:/Users/ASUS/Documents/R/win-library/4.1/rgdal/proj
## PROJ CDN enabled: FALSE
## Linking to sp version:1.4-5
## To mute warnings of possible GDAL/OSR exportToProj4() degradation,
## use options("rgdal_show_exportToProj4_warnings"="none") before loading sp or rgdal.
## Overwritten PROJ_LIB was C:/Users/ASUS/Documents/R/win-library/4.1/rgdal/projlibrary(spatialreg)## Loading required package: spData## To access larger datasets in this package, install the spDataLarge
## package with: `install.packages('spDataLarge',
## repos='https://nowosad.github.io/drat/', type='source')`## Loading required package: Matrix##
## Attaching package: 'Matrix'## The following objects are masked from 'package:tidyr':
##
## expand, pack, unpacklibrary(spatial)
library(mapview)
library(dplyr)
library(tidyselect)
library(tidyr)
library(rgeos)## rgeos version: 0.5-7, (SVN revision 676)
## GEOS runtime version: 3.9.1-CAPI-1.14.2
## Please note that rgeos will be retired by the end of 2023,
## plan transition to sf functions using GEOS at your earliest convenience.
## GEOS using OverlayNG
## Linking to sp version: 1.4-5
## Polygon checking: TRUEpath1="E:\\Irvan\\PETA UNTUK YOUTUBE PAPUA\\gadm36_IDN_2.shp"
indonesia <- st_read(path1)## Reading layer `gadm36_IDN_2' from data source
## `E:\Irvan\PETA UNTUK YOUTUBE PAPUA\gadm36_IDN_2.shp' using driver `ESRI Shapefile'
## Simple feature collection with 502 features and 13 fields
## Geometry type: MULTIPOLYGON
## Dimension: XY
## Bounding box: xmin: 95.0097 ymin: -11.00762 xmax: 141.0194 ymax: 6.076941
## Geodetic CRS: WGS 84# Membuat Peta Indonesia
indonesia %>% plot()## Warning: plotting the first 10 out of 13 attributes; use max.plot = 13 to plot
## all
names(indonesia)## [1] "GID_0" "NAME_0" "GID_1" "NAME_1" "NL_NAME_1" "GID_2"
## [7] "NAME_2" "VARNAME_2" "NL_NAME_2" "TYPE_2" "ENGTYPE_2" "CC_2"
## [13] "HASC_2" "geometry"#Mengambil 1 peta
indonesia %>% select(GID_1) %>% plot()
# Melihat nama-nama provinsi
indonesia$NAME_1## [1] "Aceh" "Aceh" "Aceh"
## [4] "Aceh" "Aceh" "Aceh"
## [7] "Aceh" "Aceh" "Aceh"
## [10] "Aceh" "Aceh" "Aceh"
## [13] "Aceh" "Aceh" "Aceh"
## [16] "Aceh" "Aceh" "Aceh"
## [19] "Aceh" "Aceh" "Aceh"
## [22] "Aceh" "Aceh" "Bali"
## [25] "Bali" "Bali" "Bali"
## [28] "Bali" "Bali" "Bali"
## [31] "Bali" "Bali" "Bangka Belitung"
## [34] "Bangka Belitung" "Bangka Belitung" "Bangka Belitung"
## [37] "Bangka Belitung" "Bangka Belitung" "Bangka Belitung"
## [40] "Banten" "Banten" "Banten"
## [43] "Banten" "Banten" "Banten"
## [46] "Banten" "Banten" "Bengkulu"
## [49] "Bengkulu" "Bengkulu" "Bengkulu"
## [52] "Bengkulu" "Bengkulu" "Bengkulu"
## [55] "Bengkulu" "Bengkulu" "Bengkulu"
## [58] "Gorontalo" "Gorontalo" "Gorontalo"
## [61] "Gorontalo" "Gorontalo" "Gorontalo"
## [64] "Gorontalo" "Jakarta Raya" "Jakarta Raya"
## [67] "Jakarta Raya" "Jakarta Raya" "Jakarta Raya"
## [70] "Jakarta Raya" "Jambi" "Jambi"
## [73] "Jambi" "Jambi" "Jambi"
## [76] "Jambi" "Jambi" "Jambi"
## [79] "Jambi" "Jambi" "Jambi"
## [82] "Jawa Barat" "Jawa Barat" "Jawa Barat"
## [85] "Jawa Barat" "Jawa Barat" "Jawa Barat"
## [88] "Jawa Barat" "Jawa Barat" "Jawa Barat"
## [91] "Jawa Barat" "Jawa Barat" "Jawa Barat"
## [94] "Jawa Barat" "Jawa Barat" "Jawa Barat"
## [97] "Jawa Barat" "Jawa Barat" "Jawa Barat"
## [100] "Jawa Barat" "Jawa Barat" "Jawa Barat"
## [103] "Jawa Barat" "Jawa Barat" "Jawa Barat"
## [106] "Jawa Barat" "Jawa Barat" "Jawa Barat"
## [109] "Jawa Tengah" "Jawa Tengah" "Jawa Tengah"
## [112] "Jawa Tengah" "Jawa Tengah" "Jawa Tengah"
## [115] "Jawa Tengah" "Jawa Tengah" "Jawa Tengah"
## [118] "Jawa Tengah" "Jawa Tengah" "Jawa Tengah"
## [121] "Jawa Tengah" "Jawa Tengah" "Jawa Tengah"
## [124] "Jawa Tengah" "Jawa Tengah" "Jawa Tengah"
## [127] "Jawa Tengah" "Jawa Tengah" "Jawa Tengah"
## [130] "Jawa Tengah" "Jawa Tengah" "Jawa Tengah"
## [133] "Jawa Tengah" "Jawa Tengah" "Jawa Tengah"
## [136] "Jawa Tengah" "Jawa Tengah" "Jawa Tengah"
## [139] "Jawa Tengah" "Jawa Tengah" "Jawa Tengah"
## [142] "Jawa Tengah" "Jawa Tengah" "Jawa Tengah"
## [145] "Jawa Timur" "Jawa Timur" "Jawa Timur"
## [148] "Jawa Timur" "Jawa Timur" "Jawa Timur"
## [151] "Jawa Timur" "Jawa Timur" "Jawa Timur"
## [154] "Jawa Timur" "Jawa Timur" "Jawa Timur"
## [157] "Jawa Timur" "Jawa Timur" "Jawa Timur"
## [160] "Jawa Timur" "Jawa Timur" "Jawa Timur"
## [163] "Jawa Timur" "Jawa Timur" "Jawa Timur"
## [166] "Jawa Timur" "Jawa Timur" "Jawa Timur"
## [169] "Jawa Timur" "Jawa Timur" "Jawa Timur"
## [172] "Jawa Timur" "Jawa Timur" "Jawa Timur"
## [175] "Jawa Timur" "Jawa Timur" "Jawa Timur"
## [178] "Jawa Timur" "Jawa Timur" "Jawa Timur"
## [181] "Jawa Timur" "Jawa Timur" "Kalimantan Barat"
## [184] "Kalimantan Barat" "Kalimantan Barat" "Kalimantan Barat"
## [187] "Kalimantan Barat" "Kalimantan Barat" "Kalimantan Barat"
## [190] "Kalimantan Barat" "Kalimantan Barat" "Kalimantan Barat"
## [193] "Kalimantan Barat" "Kalimantan Barat" "Kalimantan Barat"
## [196] "Kalimantan Barat" "Kalimantan Selatan" "Kalimantan Selatan"
## [199] "Kalimantan Selatan" "Kalimantan Selatan" "Kalimantan Selatan"
## [202] "Kalimantan Selatan" "Kalimantan Selatan" "Kalimantan Selatan"
## [205] "Kalimantan Selatan" "Kalimantan Selatan" "Kalimantan Selatan"
## [208] "Kalimantan Selatan" "Kalimantan Selatan" "Kalimantan Tengah"
## [211] "Kalimantan Tengah" "Kalimantan Tengah" "Kalimantan Tengah"
## [214] "Kalimantan Tengah" "Kalimantan Tengah" "Kalimantan Tengah"
## [217] "Kalimantan Tengah" "Kalimantan Tengah" "Kalimantan Tengah"
## [220] "Kalimantan Tengah" "Kalimantan Tengah" "Kalimantan Tengah"
## [223] "Kalimantan Tengah" "Kalimantan Timur" "Kalimantan Timur"
## [226] "Kalimantan Timur" "Kalimantan Timur" "Kalimantan Timur"
## [229] "Kalimantan Timur" "Kalimantan Timur" "Kalimantan Timur"
## [232] "Kalimantan Timur" "Kalimantan Timur" "Kalimantan Timur"
## [235] "Kalimantan Timur" "Kalimantan Timur" "Kalimantan Timur"
## [238] "Kepulauan Riau" "Kepulauan Riau" "Kepulauan Riau"
## [241] "Kepulauan Riau" "Kepulauan Riau" "Kepulauan Riau"
## [244] "Kepulauan Riau" "Lampung" "Lampung"
## [247] "Lampung" "Lampung" "Lampung"
## [250] "Lampung" "Lampung" "Lampung"
## [253] "Lampung" "Lampung" "Lampung"
## [256] "Lampung" "Lampung" "Lampung"
## [259] "Maluku" "Maluku" "Maluku"
## [262] "Maluku" "Maluku" "Maluku"
## [265] "Maluku" "Maluku" "Maluku"
## [268] "Maluku" "Maluku" "Maluku Utara"
## [271] "Maluku Utara" "Maluku Utara" "Maluku Utara"
## [274] "Maluku Utara" "Maluku Utara" "Maluku Utara"
## [277] "Maluku Utara" "Maluku Utara" "Nusa Tenggara Barat"
## [280] "Nusa Tenggara Barat" "Nusa Tenggara Barat" "Nusa Tenggara Barat"
## [283] "Nusa Tenggara Barat" "Nusa Tenggara Barat" "Nusa Tenggara Barat"
## [286] "Nusa Tenggara Barat" "Nusa Tenggara Barat" "Nusa Tenggara Barat"
## [289] "Nusa Tenggara Timur" "Nusa Tenggara Timur" "Nusa Tenggara Timur"
## [292] "Nusa Tenggara Timur" "Nusa Tenggara Timur" "Nusa Tenggara Timur"
## [295] "Nusa Tenggara Timur" "Nusa Tenggara Timur" "Nusa Tenggara Timur"
## [298] "Nusa Tenggara Timur" "Nusa Tenggara Timur" "Nusa Tenggara Timur"
## [301] "Nusa Tenggara Timur" "Nusa Tenggara Timur" "Nusa Tenggara Timur"
## [304] "Nusa Tenggara Timur" "Nusa Tenggara Timur" "Nusa Tenggara Timur"
## [307] "Nusa Tenggara Timur" "Nusa Tenggara Timur" "Nusa Tenggara Timur"
## [310] "Papua" "Papua" "Papua"
## [313] "Papua" "Papua" "Papua"
## [316] "Papua" "Papua" "Papua"
## [319] "Papua" "Papua" "Papua"
## [322] "Papua" "Papua" "Papua"
## [325] "Papua" "Papua" "Papua"
## [328] "Papua" "Papua" "Papua"
## [331] "Papua" "Papua" "Papua"
## [334] "Papua" "Papua" "Papua"
## [337] "Papua" "Papua" "Papua Barat"
## [340] "Papua Barat" "Papua Barat" "Papua Barat"
## [343] "Papua Barat" "Papua Barat" "Papua Barat"
## [346] "Papua Barat" "Papua Barat" "Papua Barat"
## [349] "Papua Barat" "Riau" "Riau"
## [352] "Riau" "Riau" "Riau"
## [355] "Riau" "Riau" "Riau"
## [358] "Riau" "Riau" "Riau"
## [361] "Riau" "Sulawesi Barat" "Sulawesi Barat"
## [364] "Sulawesi Barat" "Sulawesi Barat" "Sulawesi Barat"
## [367] "Sulawesi Selatan" "Sulawesi Selatan" "Sulawesi Selatan"
## [370] "Sulawesi Selatan" "Sulawesi Selatan" "Sulawesi Selatan"
## [373] "Sulawesi Selatan" "Sulawesi Selatan" "Sulawesi Selatan"
## [376] "Sulawesi Selatan" "Sulawesi Selatan" "Sulawesi Selatan"
## [379] "Sulawesi Selatan" "Sulawesi Selatan" "Sulawesi Selatan"
## [382] "Sulawesi Selatan" "Sulawesi Selatan" "Sulawesi Selatan"
## [385] "Sulawesi Selatan" "Sulawesi Selatan" "Sulawesi Selatan"
## [388] "Sulawesi Selatan" "Sulawesi Selatan" "Sulawesi Selatan"
## [391] "Sulawesi Tengah" "Sulawesi Tengah" "Sulawesi Tengah"
## [394] "Sulawesi Tengah" "Sulawesi Tengah" "Sulawesi Tengah"
## [397] "Sulawesi Tengah" "Sulawesi Tengah" "Sulawesi Tengah"
## [400] "Sulawesi Tengah" "Sulawesi Tengah" "Sulawesi Tenggara"
## [403] "Sulawesi Tenggara" "Sulawesi Tenggara" "Sulawesi Tenggara"
## [406] "Sulawesi Tenggara" "Sulawesi Tenggara" "Sulawesi Tenggara"
## [409] "Sulawesi Tenggara" "Sulawesi Tenggara" "Sulawesi Tenggara"
## [412] "Sulawesi Tenggara" "Sulawesi Tenggara" "Sulawesi Utara"
## [415] "Sulawesi Utara" "Sulawesi Utara" "Sulawesi Utara"
## [418] "Sulawesi Utara" "Sulawesi Utara" "Sulawesi Utara"
## [421] "Sulawesi Utara" "Sulawesi Utara" "Sulawesi Utara"
## [424] "Sulawesi Utara" "Sulawesi Utara" "Sulawesi Utara"
## [427] "Sulawesi Utara" "Sulawesi Utara" "Sumatera Barat"
## [430] "Sumatera Barat" "Sumatera Barat" "Sumatera Barat"
## [433] "Sumatera Barat" "Sumatera Barat" "Sumatera Barat"
## [436] "Sumatera Barat" "Sumatera Barat" "Sumatera Barat"
## [439] "Sumatera Barat" "Sumatera Barat" "Sumatera Barat"
## [442] "Sumatera Barat" "Sumatera Barat" "Sumatera Barat"
## [445] "Sumatera Barat" "Sumatera Barat" "Sumatera Barat"
## [448] "Sumatera Barat" "Sumatera Selatan" "Sumatera Selatan"
## [451] "Sumatera Selatan" "Sumatera Selatan" "Sumatera Selatan"
## [454] "Sumatera Selatan" "Sumatera Selatan" "Sumatera Selatan"
## [457] "Sumatera Selatan" "Sumatera Selatan" "Sumatera Selatan"
## [460] "Sumatera Selatan" "Sumatera Selatan" "Sumatera Selatan"
## [463] "Sumatera Selatan" "Sumatera Utara" "Sumatera Utara"
## [466] "Sumatera Utara" "Sumatera Utara" "Sumatera Utara"
## [469] "Sumatera Utara" "Sumatera Utara" "Sumatera Utara"
## [472] "Sumatera Utara" "Sumatera Utara" "Sumatera Utara"
## [475] "Sumatera Utara" "Sumatera Utara" "Sumatera Utara"
## [478] "Sumatera Utara" "Sumatera Utara" "Sumatera Utara"
## [481] "Sumatera Utara" "Sumatera Utara" "Sumatera Utara"
## [484] "Sumatera Utara" "Sumatera Utara" "Sumatera Utara"
## [487] "Sumatera Utara" "Sumatera Utara" "Sumatera Utara"
## [490] "Sumatera Utara" "Sumatera Utara" "Sumatera Utara"
## [493] "Sumatera Utara" "Sumatera Utara" "Sumatera Utara"
## [496] "Sumatera Utara" "Sumatera Utara" "Yogyakarta"
## [499] "Yogyakarta" "Yogyakarta" "Yogyakarta"
## [502] "Yogyakarta"# Mengambil daerah Sulawesi Tenggara
Sultra <- indonesia %>%
subset(indonesia$NAME_1 == "Sulawesi Tenggara")# Melihat data Sulawesi Tenggara
Sultra## Simple feature collection with 12 features and 13 fields
## Geometry type: MULTIPOLYGON
## Dimension: XY
## Bounding box: xmin: 120.8645 ymin: -6.218151 xmax: 124.6219 ymax: -2.779383
## Geodetic CRS: WGS 84
## First 10 features:
## GID_0 NAME_0 GID_1 NAME_1 NL_NAME_1 GID_2
## 402 IDN Indonesia IDN.28_1 Sulawesi Tenggara <NA> IDN.28.1_1
## 403 IDN Indonesia IDN.28_1 Sulawesi Tenggara <NA> IDN.28.2_1
## 404 IDN Indonesia IDN.28_1 Sulawesi Tenggara <NA> IDN.28.4_1
## 405 IDN Indonesia IDN.28_1 Sulawesi Tenggara <NA> IDN.28.3_1
## 406 IDN Indonesia IDN.28_1 Sulawesi Tenggara <NA> IDN.28.5_1
## 407 IDN Indonesia IDN.28_1 Sulawesi Tenggara <NA> IDN.28.7_1
## 408 IDN Indonesia IDN.28_1 Sulawesi Tenggara <NA> IDN.28.6_1
## 409 IDN Indonesia IDN.28_1 Sulawesi Tenggara <NA> IDN.28.10_1
## 410 IDN Indonesia IDN.28_1 Sulawesi Tenggara <NA> IDN.28.8_1
## 411 IDN Indonesia IDN.28_1 Sulawesi Tenggara <NA> IDN.28.9_1
## NAME_2 VARNAME_2 NL_NAME_2 TYPE_2 ENGTYPE_2 CC_2 HASC_2
## 402 Bau-Bau <NA> <NA> Kota City 7472 ID.SG.BA
## 403 Bombana <NA> <NA> Kabupaten Regency 7406 ID.SG.BO
## 404 Buton <NA> <NA> Kabupaten Regency 7401 ID.SG.BN
## 405 Buton Utara <NA> <NA> Kabupaten Regency 7409 ID.SG.BT
## 406 Kendari <NA> <NA> Kota City 7471 ID.SG.KM
## 407 Kolaka <NA> <NA> Kabupaten Regency 7404 ID.SG.KO
## 408 Kolaka Utara <NA> <NA> Kabupaten Regency 7408 ID.SG.KU
## 409 Konawe <NA> <NA> Kabupaten Regency 7403 ID.SG.KN
## 410 Konawe Selatan <NA> <NA> Kabupaten Regency 7405 ID.SG.KS
## 411 Konawe Utara <NA> <NA> Kabupaten Regency 7410 ID.SG.KW
## geometry
## 402 MULTIPOLYGON (((122.6305 -5...
## 403 MULTIPOLYGON (((122.0586 -5...
## 404 MULTIPOLYGON (((122.7368 -6...
## 405 MULTIPOLYGON (((123.0521 -4...
## 406 MULTIPOLYGON (((122.6059 -4...
## 407 MULTIPOLYGON (((121.4914 -4...
## 408 MULTIPOLYGON (((121.0525 -3...
## 409 MULTIPOLYGON (((123.1423 -4...
## 410 MULTIPOLYGON (((122.2181 -4...
## 411 MULTIPOLYGON (((122.4865 -3...# Melihat nama-nama Kabutpaten/Kota di Sulawesi Tenggara
Sultra$NAME_2## [1] "Bau-Bau" "Bombana" "Buton" "Buton Utara"
## [5] "Kendari" "Kolaka" "Kolaka Utara" "Konawe"
## [9] "Konawe Selatan" "Konawe Utara" "Muna" "Wakatobi"#simulasi jumlah penduduk Sulawesi Tenggara dengan jumlah 3 juta orang
#disebar secara acak ke 12 Kabupaten/Kota
jumlahpenduduk = sample(3000000, 12)
jumlahpenduduk## [1] 517962 2062807 1354448 1438940 1557579 1630763 1720337 2817522 836488
## [10] 2411557 1164075 2084362# Menambahkan kolom jumlah penduduk
Sultra <- Sultra %>% add_column(jumlahpenduduk)# Melihat data Sulawesi Tenggara
Sultra## Simple feature collection with 12 features and 14 fields
## Geometry type: MULTIPOLYGON
## Dimension: XY
## Bounding box: xmin: 120.8645 ymin: -6.218151 xmax: 124.6219 ymax: -2.779383
## Geodetic CRS: WGS 84
## First 10 features:
## GID_0 NAME_0 GID_1 NAME_1 NL_NAME_1 GID_2
## 402 IDN Indonesia IDN.28_1 Sulawesi Tenggara <NA> IDN.28.1_1
## 403 IDN Indonesia IDN.28_1 Sulawesi Tenggara <NA> IDN.28.2_1
## 404 IDN Indonesia IDN.28_1 Sulawesi Tenggara <NA> IDN.28.4_1
## 405 IDN Indonesia IDN.28_1 Sulawesi Tenggara <NA> IDN.28.3_1
## 406 IDN Indonesia IDN.28_1 Sulawesi Tenggara <NA> IDN.28.5_1
## 407 IDN Indonesia IDN.28_1 Sulawesi Tenggara <NA> IDN.28.7_1
## 408 IDN Indonesia IDN.28_1 Sulawesi Tenggara <NA> IDN.28.6_1
## 409 IDN Indonesia IDN.28_1 Sulawesi Tenggara <NA> IDN.28.10_1
## 410 IDN Indonesia IDN.28_1 Sulawesi Tenggara <NA> IDN.28.8_1
## 411 IDN Indonesia IDN.28_1 Sulawesi Tenggara <NA> IDN.28.9_1
## NAME_2 VARNAME_2 NL_NAME_2 TYPE_2 ENGTYPE_2 CC_2 HASC_2
## 402 Bau-Bau <NA> <NA> Kota City 7472 ID.SG.BA
## 403 Bombana <NA> <NA> Kabupaten Regency 7406 ID.SG.BO
## 404 Buton <NA> <NA> Kabupaten Regency 7401 ID.SG.BN
## 405 Buton Utara <NA> <NA> Kabupaten Regency 7409 ID.SG.BT
## 406 Kendari <NA> <NA> Kota City 7471 ID.SG.KM
## 407 Kolaka <NA> <NA> Kabupaten Regency 7404 ID.SG.KO
## 408 Kolaka Utara <NA> <NA> Kabupaten Regency 7408 ID.SG.KU
## 409 Konawe <NA> <NA> Kabupaten Regency 7403 ID.SG.KN
## 410 Konawe Selatan <NA> <NA> Kabupaten Regency 7405 ID.SG.KS
## 411 Konawe Utara <NA> <NA> Kabupaten Regency 7410 ID.SG.KW
## geometry jumlahpenduduk
## 402 MULTIPOLYGON (((122.6305 -5... 517962
## 403 MULTIPOLYGON (((122.0586 -5... 2062807
## 404 MULTIPOLYGON (((122.7368 -6... 1354448
## 405 MULTIPOLYGON (((123.0521 -4... 1438940
## 406 MULTIPOLYGON (((122.6059 -4... 1557579
## 407 MULTIPOLYGON (((121.4914 -4... 1630763
## 408 MULTIPOLYGON (((121.0525 -3... 1720337
## 409 MULTIPOLYGON (((123.1423 -4... 2817522
## 410 MULTIPOLYGON (((122.2181 -4... 836488
## 411 MULTIPOLYGON (((122.4865 -3... 2411557# Membuat Peta Sulawesi Tenggara
pal <- colorNumeric(
palette = "YlGnBu",
domain = Sultra$jumlahpenduduk
)
m <- leaflet(Sultra) %>%
addTiles() %>%
addPolygons(
color = ~pal(jumlahpenduduk),
weight = 2,
opacity = 1,
dashArray = "3",
fillOpacity = 0.7,
highlight = highlightOptions(
weight = 5,
color = "#666",
dashArray = "",
fillOpacity = 0.7,
bringToFront = TRUE),
label = paste0(Sultra$NAME_2, " ", Sultra$jumlahpenduduk),
labelOptions = labelOptions(
style = list("font-weight" = "normal", padding = "3px 8px"),
textsize = "15px",
direction = "auto")
)
m# Menambahkan Legend Pada Peta Sulawesi Tenggara
pal <- colorNumeric(
palette = "YlGnBu",
domain = Sultra$jumlahpenduduk
)
m <- leaflet(Sultra) %>%
addTiles() %>%
addPolygons(
color = ~pal(jumlahpenduduk),
weight = 2,
opacity = 1,
dashArray = "3",
fillOpacity = 0.7,
highlight = highlightOptions(
weight = 5,
color = "#666",
dashArray = "",
fillOpacity = 0.7,
bringToFront = TRUE),
label = paste0(Sultra$NAME_2, " ", Sultra$jumlahpenduduk),
labelOptions = labelOptions(
style = list("font-weight" = "normal", padding = "3px 8px"),
textsize = "15px",
direction = "auto")
) %>%
addLegend(
position = "bottomright",
pal = pal,
values = ~jumlahpenduduk,
title = "Jumlah Penduduk"
)
m#Membuat Koordinat Titik Tengah Setiap Wilayah
library(sf)
library(ggplot2)
nc <- st_read(path1)## Reading layer `gadm36_IDN_2' from data source
## `E:\Irvan\PETA UNTUK YOUTUBE PAPUA\gadm36_IDN_2.shp' using driver `ESRI Shapefile'
## Simple feature collection with 502 features and 13 fields
## Geometry type: MULTIPOLYGON
## Dimension: XY
## Bounding box: xmin: 95.0097 ymin: -11.00762 xmax: 141.0194 ymax: 6.076941
## Geodetic CRS: WGS 84nc <- nc %>%
subset(nc$NAME_1 == "Sulawesi Tenggara") %>%
dplyr::select(NAME_2)
sf_cent <- st_centroid(nc)## Warning in st_centroid.sf(nc): st_centroid assumes attributes are constant over
## geometries of xclass(sf_cent)## [1] "sf" "data.frame"A = sf_cent[2]
datakoordinat = st_coordinates(A)
datakoordinat## X Y
## 1 122.6753 -5.429898
## 2 121.8507 -4.797686
## 3 122.7333 -5.367801
## 4 123.0160 -4.701452
## 5 122.5326 -4.000391
## 6 121.5765 -3.927887
## 7 121.1563 -3.247666
## 8 122.0348 -3.597952
## 9 122.4208 -4.262691
## 10 121.9969 -3.385118
## 11 122.5954 -4.902196
## 12 123.7951 -5.575268xlong = datakoordinat[,1]
ylat = datakoordinat[,2]
xlong## 1 2 3 4 5 6 7 8
## 122.6753 121.8507 122.7333 123.0160 122.5326 121.5765 121.1563 122.0348
## 9 10 11 12
## 122.4208 121.9969 122.5954 123.7951ylat## 1 2 3 4 5 6 7 8
## -5.429898 -4.797686 -5.367801 -4.701452 -4.000391 -3.927887 -3.247666 -3.597952
## 9 10 11 12
## -4.262691 -3.385118 -4.902196 -5.575268# Memberi label dan jumlah penduduk tiap Kabupaten/Kota
pal <- colorNumeric(
palette = "YlGnBu",
domain = Sultra$jumlahpenduduk
)
gambarpeta <- leaflet(Sultra) %>%
addTiles() %>%
addPolygons(
color = ~pal(jumlahpenduduk),
weight = 2,
opacity = 1,
dashArray = "3",
fillOpacity = 0.7,
highlight = highlightOptions(
weight = 5,
color = "#666",
dashArray = "",
fillOpacity = 0.7,
bringToFront = TRUE),
label = paste0(Sultra$NAME_2, " ", Sultra$jumlahpenduduk),
labelOptions = labelOptions(
style = list("font-weight" = "normal", padding = "3px 8px"),
textsize = "15px",
direction = "auto")
) %>%
addLegend(
position = "bottomright",
pal = pal,
values = ~jumlahpenduduk,
title = "Jumlah Penduduk"
) %>%
addMarkers(xlong, ylat,
label = paste0(Sultra$NAME_2, " ", Sultra$jumlahpenduduk) ,
labelOptions = labelOptions(noHide = T, textsize = "1px", direction = "bottom",
style = list(
"color" = "red",
"font-family" = "serif",
"font-style" = "italic",
"box-shadow" = "3px 3px rgba(0,0,0,0.25)",
"font-size" = "12px",
"border-color" = "rgba(0,0,0,0.5)"
))
)
gambarpeta