R Dependency Test

Code
Author

Yonghun Suh

Published

October 7, 2024

This is the first post in a Quarto blog. Welcome!



See: https://github.com/quarto-dev/quarto-actions/blob/main/examples/example-03-dependencies.md



library(yaml)
library(tidyverse)
library(data.table)
library(sf)
library(terra)
library(tmap)
library(leafem)

Tidyverse

read_csv("./data/SVI_2000_US.csv")
Rows: 65081 Columns: 82
── Column specification ────────────────────────────────────────────────────────
Delimiter: ","
chr  (9): STATE_FIPS, CNTY_FIPS, STCOFIPS, TRACT, FIPS, STATE_NAME, STATE_AB...
dbl (73): G1V1R, G1V2R, G1V3R, G1V4R, G2V1R, G2V2R, G2V3R, G2V4R, G3V1R, G3V...

ℹ Use `spec()` to retrieve the full column specification for this data.
ℹ Specify the column types or set `show_col_types = FALSE` to quiet this message.
# A tibble: 65,081 × 82
   STATE_FIPS CNTY_FIPS STCOFIPS TRACT FIPS  STATE_NAME STATE_ABBR COUNTY  G1V1R
   <chr>      <chr>     <chr>    <chr> <chr> <chr>      <chr>      <chr>   <dbl>
 1 01         001       01001    0201… 0100… Alabama    AL         Autau… 0.127 
 2 01         001       01001    0202… 0100… Alabama    AL         Autau… 0.227 
 3 01         001       01001    0203… 0100… Alabama    AL         Autau… 0.0766
 4 01         001       01001    0204… 0100… Alabama    AL         Autau… 0.0454
 5 01         001       01001    0205… 0100… Alabama    AL         Autau… 0.0367
 6 01         001       01001    0206… 0100… Alabama    AL         Autau… 0.152 
 7 01         001       01001    0207… 0100… Alabama    AL         Autau… 0.11  
 8 01         001       01001    0208… 0100… Alabama    AL         Autau… 0.0844
 9 01         001       01001    0209… 0100… Alabama    AL         Autau… 0.138 
10 01         001       01001    0210… 0100… Alabama    AL         Autau… 0.176 
# ℹ 65,071 more rows
# ℹ 73 more variables: G1V2R <dbl>, G1V3R <dbl>, G1V4R <dbl>, G2V1R <dbl>,
#   G2V2R <dbl>, G2V3R <dbl>, G2V4R <dbl>, G3V1R <dbl>, G3V2R <dbl>,
#   G4V1R <dbl>, G4V2R <dbl>, G4V3R <dbl>, G4V4R <dbl>, G4V5R <dbl>,
#   USG1V1P <dbl>, USG1V2P <dbl>, USG1V3P <dbl>, USG1V4P <dbl>, USG1TP <dbl>,
#   USG2V1P <dbl>, USG2V2P <dbl>, USG2V3P <dbl>, USG2V4P <dbl>, USG2TP <dbl>,
#   USG3V1P <dbl>, USG3V2P <dbl>, USG3TP <dbl>, USG4V1P <dbl>, USG4V2P <dbl>, …

data.table

fread("./data/SVI_2000_US.csv") |> head()
   STATE_FIPS CNTY_FIPS STCOFIPS TRACT       FIPS STATE_NAME STATE_ABBR  COUNTY
        <int>     <int>    <int> <int>      <i64>     <char>     <char>  <char>
1:          1         1     1001 20100 1001020100    Alabama         AL Autauga
2:          1         1     1001 20200 1001020200    Alabama         AL Autauga
3:          1         1     1001 20300 1001020300    Alabama         AL Autauga
4:          1         1     1001 20400 1001020400    Alabama         AL Autauga
5:          1         1     1001 20500 1001020500    Alabama         AL Autauga
6:          1         1     1001 20600 1001020600    Alabama         AL Autauga
    G1V1R  G1V2R G1V3R  G1V4R  G2V1R  G2V2R  G2V3R  G2V4R  G3V1R  G3V2R  G4V1R
    <num>  <num> <num>  <num>  <num>  <num>  <num>  <num>  <num>  <num>  <num>
1: 0.1268 0.0527 17771 0.1841 0.0782 0.2783 0.2032 0.1018 0.0447 0.0000 0.0000
2: 0.2270 0.0997 14217 0.3249 0.1215 0.2735 0.3466 0.1176 0.6691 0.0045 0.0092
3: 0.0766 0.0288 18346 0.1699 0.1338 0.2890 0.1902 0.1130 0.1794 0.0056 0.0317
4: 0.0454 0.0351 19741 0.1341 0.1510 0.2500 0.1842 0.0560 0.0621 0.0000 0.0310
5: 0.0367 0.0166 24510 0.0863 0.0682 0.3079 0.1193 0.0654 0.1121 0.0059 0.0246
6: 0.1521 0.0550 16395 0.2386 0.0938 0.3034 0.2214 0.1101 0.2078 0.0185 0.0000
    G4V2R  G4V3R  G4V4R  G4V5R USG1V1P USG1V2P USG1V3P USG1V4P USG1TP USG2V1P
    <num>  <num>  <num>  <num>   <num>   <num>   <num>   <num>  <num>   <num>
1: 0.2075 0.0090 0.0409 0.0389   0.604   0.541   0.566   0.518  0.591   0.214
2: 0.0198 0.0544 0.0705 0.0140   0.829   0.837   0.790   0.814  0.904   0.495
3: 0.0143 0.0141 0.0582 0.0270   0.390   0.211   0.533   0.473  0.367   0.580
4: 0.0492 0.0181 0.0301 0.0040   0.209   0.306   0.452   0.355  0.264   0.687
5: 0.0070 0.0182 0.0241 0.0000   0.153   0.061   0.258   0.194  0.067   0.162
6: 0.3373 0.0182 0.0571 0.0000   0.682   0.566   0.658   0.659  0.706   0.306
   USG2V2P USG2V3P USG2V4P USG2TP USG3V1P USG3V2P USG3TP USG4V1P USG4V2P
     <num>   <num>   <num>  <num>   <num>   <num>  <num>   <num>   <num>
1:   0.675   0.547   0.754  0.609   0.169   0.000  0.000   0.000   0.872
2:   0.641   0.971   0.850  0.935   0.828   0.061  0.375   0.332   0.592
3:   0.739   0.473   0.820  0.818   0.488   0.072  0.142   0.477   0.571
4:   0.456   0.439   0.315  0.440   0.233   0.000  0.002   0.474   0.662
5:   0.829   0.119   0.421  0.236   0.370   0.081  0.078   0.441   0.512
6:   0.811   0.644   0.811  0.802   0.527   0.289  0.344   0.000   0.954
   USG4V3P USG4V4P USG4V5P USG4TP  USTP USG1V1F USG1V2F USG1V3F USG1V4F USG1TF
     <num>   <num>   <num>  <num> <num>   <num>   <num>   <num>   <num>  <num>
1:   0.048   0.316   0.945  0.574 0.450       0       0       0       0      0
2:   0.421   0.532   0.846  0.782 0.854       0       0       0       0      0
3:   0.070   0.454   0.879  0.682 0.522       0       0       0       0      0
4:   0.107   0.215   0.000  0.280 0.183       0       0       0       0      0
5:   0.109   0.159   0.000  0.206 0.078       0       0       0       0      0
6:   0.109   0.446   0.000  0.302 0.557       0       0       0       0      0
   USG2V1F USG2V2F USG2V3F USG2V4F USG2TF USG3V1F USG3V2F USG3TF USG4V1F
     <num>   <num>   <num>   <num>  <num>   <num>   <num>  <num>   <num>
1:       0       0       0       0      0       0       0      0       0
2:       0       0       1       0      1       0       0      0       0
3:       0       0       0       0      0       0       0      0       0
4:       0       0       0       0      0       0       0      0       0
5:       0       0       0       0      0       0       0      0       0
6:       0       0       0       0      0       0       0      0       0
   USG4V2F USG4V3F USG4V4F USG4V5F USG4TF  USTF Totpop2000 Totalhu G1V1N G1V2N
     <num>   <num>   <num>   <num>  <num> <num>      <num>   <num> <num> <num>
1:       0       0       0       1      1     1       1879     742   227    46
2:       0       0       0       0      0     1       1934     758   433    80
3:       0       0       0       0      0     0       3339    1263   250    42
4:       0       0       0       0      0     0       4556    1871   207    77
5:       0       0       0       0      0     0       6040    2277   222    49
6:       1       0       0       0      1     1       3378    1352   514    90
   G1V4N G2V1N G2V2N G2V3N G2V4N G3V1N G3V2N G4V1N G4V2N G4V3N G4V4N G4V5N
   <num> <num> <num> <num> <num> <num> <num> <num> <num> <num> <num> <num>
1:   226   147   523   339    73    84     0     0   154     6    27    73
2:   376   235   529   603    74  1294     8     7    15    37    48    27
3:   362   447   965   549   136   599    17    40    18    17    70    90
4:   412   688  1139   777    98   283     0    58    92    32    53    18
5:   326   412  1860   644   143   677    33    56    16    40    53     0
6:   487   317  1025   689   132   702    58     0   456    22    69     0
                                     Shape Shape.STArea() Shape.STLength()
                                    <char>          <num>            <num>
1: (-86.49001754505039, 32.47712149572407)   0.0009407913       0.15003547
2: (-86.47336703419953, 32.47430466837865)   0.0003177997       0.09226531
3:  (-86.4602033958281, 32.47548170589444)   0.0005147620       0.10013704
4: (-86.44371817489963, 32.47198623491002)   0.0006099415       0.11676753
5: (-86.42267086235849, 32.45886190833748)   0.0011041460       0.16854121
6: (-86.47834504936274, 32.44206725458296)   0.0007950631       0.16149683

Simple Features

read_sf("./data/test.gpkg") |> st_geometry() |> plot()

Terra

vect("./data/test.gpkg") |> plot()

Themetic Map(tmap) & leafem

tmap_mode("view")
tmap mode set to interactive viewing
park_list <- read_sf("./data/test.gpkg") %>% 
    filter(grepl("서울",소재지지번주소)) %>%
    select(공원명,소재지지번주소)

{
  tm_basemap(c("OpenStreetMap.HOT",
               "https://mt1.google.com/vt/lyrs=y&hl=en&z={z}&x={x}&y={y}",
               "https://mt1.google.com/vt/lyrs=s&hl=en&z={z}&x={x}&y={y}"),
             group = list(c("OpenStreetMap.HOT",
                       "Google Satellite Imagery w/ label",
                       "Google Satellite Imagery wo/ label"))) +
    tm_shape(park_list)  +                                  
    tm_dots(size=.1,
            col = "red", 
            border.col="white",
            border.lwd=3,
            id="name") -> themap
  
  
  
  tmap_leaflet(themap)|>
    addMouseCoordinates()
  
}