#load libraries
knitr::opts_chunk$set(echo = TRUE, warning=FALSE)

library(tidyverse)  # Modern data science workflow

── Attaching core tidyverse packages ──────────────────────── tidyverse 2.0.0 ──
✔ dplyr     1.1.0     ✔ readr     2.1.4
✔ forcats   1.0.0     ✔ stringr   1.5.0
✔ ggplot2   3.4.1     ✔ tibble    3.1.8
✔ lubridate 1.9.2     ✔ tidyr     1.3.0
✔ purrr     1.0.1     
── Conflicts ────────────────────────────────────────── tidyverse_conflicts() ──
✖ dplyr::filter() masks stats::filter()
✖ dplyr::lag()    masks stats::lag()
ℹ Use the ]8;;http://conflicted.r-lib.org/conflicted package]8;; to force all conflicts to become errors

library(sf)         # Simple features for R

Linking to GEOS 3.10.2, GDAL 3.4.2, PROJ 8.2.1; sf_use_s2() is TRUE

library(tmap)       # Thematic Maps
library(tmaptools)  # Thematic Maps Tools
library(RColorBrewer) # ColorBrewer Palettes
library(leaflet)    # Interactive web maps
library(rgdal)      # Bindings for the Geospatial Data Abstraction Library

Loading required package: sp
Please note that rgdal will be retired during 2023,
plan transition to sf/stars/terra functions using GDAL and PROJ
at your earliest convenience.
See https://r-spatial.org/r/2022/04/12/evolution.html and https://github.com/r-spatial/evolution
rgdal: version: 1.6-6, (SVN revision 1201)
Geospatial Data Abstraction Library extensions to R successfully loaded
Loaded GDAL runtime: GDAL 3.4.2, released 2022/03/08
Path to GDAL shared files: /Library/Frameworks/R.framework/Versions/4.2/Resources/library/rgdal/gdal
GDAL binary built with GEOS: FALSE 
Loaded PROJ runtime: Rel. 8.2.1, January 1st, 2022, [PJ_VERSION: 821]
Path to PROJ shared files: /Library/Frameworks/R.framework/Versions/4.2/Resources/library/rgdal/proj
PROJ CDN enabled: FALSE
Linking to sp version:1.6-0
To mute warnings of possible GDAL/OSR exportToProj4() degradation,
use options("rgdal_show_exportToProj4_warnings"="none") before loading sp or rgdal.

library(rgeos)      # Interface to Geometry Engine - Open Source 

rgeos version: 0.6-2, (SVN revision 693)
 GEOS runtime version: 3.10.2-CAPI-1.16.0 
 Please note that rgeos will be retired during 2023,
plan transition to sf functions using GEOS at your earliest convenience.
 GEOS using OverlayNG
 Linking to sp version: 1.6-0 
 Polygon checking: TRUE 


Attaching package: 'rgeos'

The following object is masked from 'package:dplyr':

    symdiff

#change the presentation of decimal numbers to 4 and avoid scientific notation
options(prompt="R> ", digits=4, scipen=999)

#read data
dat <- read_csv("/Users/selinkumbaraci/Desktop/Spring 2023/Sustainable Finance/Solar.csv")

Rows: 67 Columns: 2
── Column specification ────────────────────────────────────────────────────────
Delimiter: ","
dbl (2): id, Solar Radiation Value

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.

mapData <- read_sf("/Users/selinkumbaraci/Desktop/Spring 2023/Sustainable Finance/MAP/MAP.shp")

#check coordinate reference system
st_crs(mapData)

Coordinate Reference System:
  User input: WGS 84 
  wkt:
GEOGCRS["WGS 84",
    DATUM["World Geodetic System 1984",
        ELLIPSOID["WGS 84",6378137,298.257223563,
            LENGTHUNIT["metre",1]]],
    PRIMEM["Greenwich",0,
        ANGLEUNIT["degree",0.0174532925199433]],
    CS[ellipsoidal,2],
        AXIS["latitude",north,
            ORDER[1],
            ANGLEUNIT["degree",0.0174532925199433]],
        AXIS["longitude",east,
            ORDER[2],
            ANGLEUNIT["degree",0.0174532925199433]],
    ID["EPSG",4326]]

#merge the data
dat_map <- inner_join(
  dat,
  mapData,
  by = "id")

#keep data as sf object
dat_map <- st_as_sf(dat_map)
st_crs(mapData)

Coordinate Reference System:
  User input: WGS 84 
  wkt:
GEOGCRS["WGS 84",
    DATUM["World Geodetic System 1984",
        ELLIPSOID["WGS 84",6378137,298.257223563,
            LENGTHUNIT["metre",1]]],
    PRIMEM["Greenwich",0,
        ANGLEUNIT["degree",0.0174532925199433]],
    CS[ellipsoidal,2],
        AXIS["latitude",north,
            ORDER[1],
            ANGLEUNIT["degree",0.0174532925199433]],
        AXIS["longitude",east,
            ORDER[2],
            ANGLEUNIT["degree",0.0174532925199433]],
    ID["EPSG",4326]]

#static map
tmap_options(check.and.fix = TRUE)

tm_shape(dat_map) + 
  tm_fill("Solar Radiation Value",
          style = "quantile",
          n = 7,
          palette = "Reds") +
  tm_layout(
    legend.outside = TRUE,
    frame = FALSE)

#interactive map
tmap_options(check.and.fix = TRUE)

tmap_mode("view")

tmap mode set to interactive viewing

tm_shape(dat_map) + 
  tm_fill("Solar Radiation Value",
          palette = "Reds",
          id="province",
          popup.vars=c("Solar Radiation Value")
          ) + 
    tm_legend(outside=TRUE) +
  tm_layout(frame = FALSE)