loading library

library(lattice)
library(ggplot2)
library(dplyr)
## 
## Attaching package: 'dplyr'
## The following objects are masked from 'package:stats':
## 
##     filter, lag
## The following objects are masked from 'package:base':
## 
##     intersect, setdiff, setequal, union
library(tidyr)
library(readxl)
library(tmap)
library(sf)
## Linking to GEOS 3.13.0, GDAL 3.8.5, PROJ 9.5.1; sf_use_s2() is TRUE
library(raster)
## Loading required package: sp
## 
## Attaching package: 'raster'
## The following object is masked from 'package:dplyr':
## 
##     select
library(readxl)
databali<- read_excel("Downloads/data_macro_bali.xlsx")
library(readr)
datamakro <- read_csv("Downloads/macro_indicators.csv")
## Rows: 1200 Columns: 15
## ── Column specification ────────────────────────────────────────────────────────
## Delimiter: ","
## chr  (4): country, region, dev_level, shock_event
## dbl (11): year, gdp_growth, gdp_level, inflation, policy_rate, unemployment,...
## 
## 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.

#Nomor 1 ##Data develop dan emerging

datadevelop<-subset(datamakro,`dev_level`%in%c("developed"))
dataemerging<-subset(datamakro,`dev_level`%in%c("emerging"))

##4 negara yg dipilih (developed autralia dan jepang, emerging thailand dan indonesia)

datanegara<-subset(datamakro,`country`%in%c("Australia","Japan","Thailand","Indonesia"))

###menyesuaikan tanggal

library(lubridate)
## 
## Attaching package: 'lubridate'
## The following objects are masked from 'package:raster':
## 
##     intersect, union
## The following objects are masked from 'package:base':
## 
##     date, intersect, setdiff, union
datanegara$year <- suppressWarnings(
  ymd(paste0(as.character(datanegara$year), "-01-01"))
)

###time series plot inflation

ggplot(datanegara,
       aes(x=year,
           y=inflation,
           colour=country))+
  geom_line()+
  theme_minimal()

###time series plot unemployement

ggplot(datanegara,
       aes(x=year,
           y=unemployment,
           colour=country))+
  geom_line()+
  theme_minimal()

#nomor 2

xyplot(inflation~gdp_growth|factor(country),
       data=datadevelop)

xyplot(inflation~gdp_growth|factor(country),
       data=dataemerging)

xyplot(inflation~gdp_growth|factor(region),
       groups=country,
       data=datadevelop)

xyplot(inflation~gdp_growth|factor(region),
       groups=country,
       data=dataemerging)

#nomer 3

ggplot(datadevelop,
       aes(x=year,
           y=unemployment,
           colour=region))+
  geom_line()+
  theme_minimal()

ggplot(dataemerging,
       aes(x=year,
           y=unemployment))+
  geom_line()+
  theme_minimal()