Dosen Pengampu : Prof. Dr. Suhartono, Mkom

library(readxl)
datainflowsulampua <- read_excel(path = "sulampua.xlsx")
## Warning in strptime(x, format, tz = tz): unable to identify current timezone 'C':
## please set environment variable 'TZ'
datainflowsulampua
## # A tibble: 10 x 12
##    Provinsi       `2011` `2012` `2013` `2014` `2015` `2016` `2017` `2018` `2019`
##    <chr>           <dbl>  <dbl>  <dbl>  <dbl>  <dbl>  <dbl>  <dbl>  <dbl>  <dbl>
##  1 Sulawesi Utara  5671.  6635. 21646. 7.37e3 6.29e3  7266.  7044.  7781.  7809.
##  2 Sulawesi Teng~  1563.  1885.  1520. 3.00e3 2.59e3  2665.  2806.  3701.  4042.
##  3 Sulawesi Sela~ 10593. 13702. 17770. 1.94e4 1.96e4 21043. 18803. 21894. 24749.
##  4 Sulawesi Teng~   659.   964.  6093. 2.26e3 2.38e3  3491.  3618.  3632.  4390.
##  5 Sulawesi Barat     0      0      0  0      4.92e1   536.   746.   606.   542.
##  6 Gorontalo          0      0      0  0      0          0      0   1088.  1983.
##  7 Maluku Utara     586.   633. 10273. 1.01e3 1.01e3  1259.  1339.  1530.  1924.
##  8 Maluku          1273.  1147.  4341. 1.78e3 1.79e3  2367.  2484.  3210.  4056.
##  9 Papua           4710.  6047.  2131. 6.79e3 6.10e3  6291.  6353.  8076.  9259.
## 10 Papua Barat        0      0      0  1.17e1 5.18e2   818.   933.  1153.  1448.
## # ... with 2 more variables: `2020` <dbl>, `2021` <dbl>
library(tidyverse)
## -- Attaching packages --------------------------------------- tidyverse 1.3.1 --
## v ggplot2 3.3.5     v purrr   0.3.4
## v tibble  3.1.6     v dplyr   1.0.8
## v tidyr   1.2.0     v stringr 1.4.0
## v readr   2.1.2     v forcats 0.5.1
## -- Conflicts ------------------------------------------ tidyverse_conflicts() --
## x dplyr::filter() masks stats::filter()
## x dplyr::lag()    masks stats::lag()
datasulampua <- datainflowsulampua  %>%
  pivot_longer (
  cols = 2:12,
  names_to = "years",
  values_to = "cases"
  )
datasulampua
## # A tibble: 110 x 3
##    Provinsi       years  cases
##    <chr>          <chr>  <dbl>
##  1 Sulawesi Utara 2011   5671.
##  2 Sulawesi Utara 2012   6635.
##  3 Sulawesi Utara 2013  21646.
##  4 Sulawesi Utara 2014   7374.
##  5 Sulawesi Utara 2015   6286.
##  6 Sulawesi Utara 2016   7266.
##  7 Sulawesi Utara 2017   7044.
##  8 Sulawesi Utara 2018   7781.
##  9 Sulawesi Utara 2019   7809.
## 10 Sulawesi Utara 2020   6324.
## # ... with 100 more rows
ggplot(data = datasulampua) +
  geom_col(
    mapping = aes(x = years, y = cases, fill = Provinsi),
    width = 1
  )