library(readxl)
datainflowsumatera <- read_excel(path = "sumatera.xlsx")
datainflowsumatera
## # A tibble: 10 x 12
## Propinsi `2011` `2012` `2013` `2014` `2015` `2016` `2017` `2018` `2019`
## <chr> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl>
## 1 Aceh 2308. 2620. 36337. 4.57e3 4710. 5775. 5514. 5799. 7509.
## 2 Sumatera Utara 23238. 25981. 18120. 3.05e4 30254. 34427. 35617. 41769. 47112.
## 3 Sumatera Barat 9385. 11192. 14056. 1.41e4 13309. 14078. 15312. 15058. 14750.
## 4 Riau 3012. 4447. 8933. 6.36e3 7156. 8211. 8553. 10730. 10915.
## 5 Kep. Riau 1426. 2236. 3378. 2.56e3 3218. 4317. 4412. 5134. 6077.
## 6 Jambi 1868. 2138. 3047. 5.17e3 4978. 4398. 4404. 5657. 6486.
## 7 Sumatera Sela~ 7820. 9126. 8647. 1.00e4 10797. 12752. 13075. 14267. 14812.
## 8 Bengkulu 1153. 1201. 2378. 3.26e3 2791. 2889. 3620. 4150. 5789.
## 9 Lampung 7690. 6969. 3474. 9.45e3 8160. 9373. 12078. 13415. 17046.
## 10 Kep. Bangka B~ 0 0 0 1.37e1 1177. 1544. 1164. 1517. 3265.
## # ... with 2 more variables: `2020` <dbl>, `2021` <dbl>
library(tidyverse)
## Warning: package 'tidyverse' was built under R version 4.1.2
## -- 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
## Warning: package 'ggplot2' was built under R version 4.1.2
## Warning: package 'tibble' was built under R version 4.1.2
## Warning: package 'tidyr' was built under R version 4.1.2
## Warning: package 'readr' was built under R version 4.1.2
## Warning: package 'dplyr' was built under R version 4.1.2
## -- Conflicts ------------------------------------------ tidyverse_conflicts() --
## x dplyr::filter() masks stats::filter()
## x dplyr::lag() masks stats::lag()
sumatera2011 <- select(datainflowsumatera, '2011')
sumatera2011
## # A tibble: 10 x 1
## `2011`
## <dbl>
## 1 2308.
## 2 23238.
## 3 9385.
## 4 3012.
## 5 1426.
## 6 1868.
## 7 7820.
## 8 1153.
## 9 7690.
## 10 0
library(tidyverse)
sumateranon2011 <- select(datainflowsumatera, -'2011')
sumateranon2011
## # A tibble: 10 x 11
## Propinsi `2012` `2013` `2014` `2015` `2016` `2017` `2018` `2019` `2020`
## <chr> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl>
## 1 Aceh 2620. 36337. 4.57e3 4710. 5775. 5514. 5799. 7509. 6641.
## 2 Sumatera Utara 25981. 18120. 3.05e4 30254. 34427. 35617. 41769. 47112. 36609.
## 3 Sumatera Barat 11192. 14056. 1.41e4 13309. 14078. 15312. 15058. 14750. 10696.
## 4 Riau 4447. 8933. 6.36e3 7156. 8211. 8553. 10730. 10915. 9148.
## 5 Kep. Riau 2236. 3378. 2.56e3 3218. 4317. 4412. 5134. 6077. 6175.
## 6 Jambi 2138. 3047. 5.17e3 4978. 4398. 4404. 5657. 6486. 5628.
## 7 Sumatera Sela~ 9126. 8647. 1.00e4 10797. 12752. 13075. 14267. 14812. 11756.
## 8 Bengkulu 1201. 2378. 3.26e3 2791. 2889. 3620. 4150. 5789. 4971.
## 9 Lampung 6969. 3474. 9.45e3 8160. 9373. 12078. 13415. 17046. 15158.
## 10 Kep. Bangka B~ 0 0 1.37e1 1177. 1544. 1164. 1517. 3265. 2562.
## # ... with 1 more variable: `2021` <dbl>
sumatera2012 <- datainflowsumatera %>% select('2012')
sumatera2012
## # A tibble: 10 x 1
## `2012`
## <dbl>
## 1 2620.
## 2 25981.
## 3 11192.
## 4 4447.
## 5 2236.
## 6 2138.
## 7 9126.
## 8 1201.
## 9 6969.
## 10 0
library(dplyr)
sumateratahun <- datainflowsumatera %>% rename('2010' = '2011')
head(sumateratahun)
## # A tibble: 6 x 12
## Propinsi `2010` `2012` `2013` `2014` `2015` `2016` `2017` `2018` `2019` `2020`
## <chr> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl>
## 1 Aceh 2308. 2620. 36337. 4567. 4710. 5775. 5514. 5799. 7509. 6641.
## 2 Sumater~ 23238. 25981. 18120. 30503. 30254. 34427. 35617. 41769. 47112. 36609.
## 3 Sumater~ 9385. 11192. 14056. 14103. 13309. 14078. 15312. 15058. 14750. 10696.
## 4 Riau 3012. 4447. 8933. 6358. 7156. 8211. 8553. 10730. 10915. 9148.
## 5 Kep. Ri~ 1426. 2236. 3378. 2563. 3218. 4317. 4412. 5134. 6077. 6175.
## 6 Jambi 1868. 2138. 3047. 5169. 4978. 4398. 4404. 5657. 6486. 5628.
## # ... with 1 more variable: `2021` <dbl>
library(dplyr)
sumateraaceh <- datainflowsumatera %>%
filter(Propinsi == 'Aceh') %>%
select('2011','2012')
sumateraaceh
## # A tibble: 1 x 2
## `2011` `2012`
## <dbl> <dbl>
## 1 2308. 2620.
library(dplyr)
sumateraup1 <- datainflowsumatera %>%
filter(Propinsi == 'Aceh', Propinsi == 'Bengkulu') %>%
select('2011','2012')
sumateraup1
## # A tibble: 0 x 2
## # ... with 2 variables: 2011 <dbl>, 2012 <dbl>
str(datainflowsumatera)
## tibble [10 x 12] (S3: tbl_df/tbl/data.frame)
## $ Propinsi: chr [1:10] "Aceh" "Sumatera Utara" "Sumatera Barat" "Riau" ...
## $ 2011 : num [1:10] 2308 23238 9385 3012 1426 ...
## $ 2012 : num [1:10] 2620 25981 11192 4447 2236 ...
## $ 2013 : num [1:10] 36337 18120 14056 8933 3378 ...
## $ 2014 : num [1:10] 4567 30503 14103 6358 2563 ...
## $ 2015 : num [1:10] 4710 30254 13309 7156 3218 ...
## $ 2016 : num [1:10] 5775 34427 14078 8211 4317 ...
## $ 2017 : num [1:10] 5514 35617 15312 8553 4412 ...
## $ 2018 : num [1:10] 5799 41769 15058 10730 5134 ...
## $ 2019 : num [1:10] 7509 47112 14750 10915 6077 ...
## $ 2020 : num [1:10] 6641 36609 10696 9148 6175 ...
## $ 2021 : num [1:10] 3702 31840 10748 7769 5009 ...
str(datainflowsumatera %>% group_by(Propinsi))
## grouped_df [10 x 12] (S3: grouped_df/tbl_df/tbl/data.frame)
## $ Propinsi: chr [1:10] "Aceh" "Sumatera Utara" "Sumatera Barat" "Riau" ...
## $ 2011 : num [1:10] 2308 23238 9385 3012 1426 ...
## $ 2012 : num [1:10] 2620 25981 11192 4447 2236 ...
## $ 2013 : num [1:10] 36337 18120 14056 8933 3378 ...
## $ 2014 : num [1:10] 4567 30503 14103 6358 2563 ...
## $ 2015 : num [1:10] 4710 30254 13309 7156 3218 ...
## $ 2016 : num [1:10] 5775 34427 14078 8211 4317 ...
## $ 2017 : num [1:10] 5514 35617 15312 8553 4412 ...
## $ 2018 : num [1:10] 5799 41769 15058 10730 5134 ...
## $ 2019 : num [1:10] 7509 47112 14750 10915 6077 ...
## $ 2020 : num [1:10] 6641 36609 10696 9148 6175 ...
## $ 2021 : num [1:10] 3702 31840 10748 7769 5009 ...
## - attr(*, "groups")= tibble [10 x 2] (S3: tbl_df/tbl/data.frame)
## ..$ Propinsi: chr [1:10] "Aceh" "Bengkulu" "Jambi" "Kep. Bangka Belitung" ...
## ..$ .rows : list<int> [1:10]
## .. ..$ : int 1
## .. ..$ : int 8
## .. ..$ : int 6
## .. ..$ : int 10
## .. ..$ : int 5
## .. ..$ : int 9
## .. ..$ : int 4
## .. ..$ : int 3
## .. ..$ : int 7
## .. ..$ : int 2
## .. ..@ ptype: int(0)
## ..- attr(*, ".drop")= logi TRUE
sumateraup3 <- datainflowsumatera %>%
group_by(Propinsi)
sumateraup3
## # A tibble: 10 x 12
## # Groups: Propinsi [10]
## Propinsi `2011` `2012` `2013` `2014` `2015` `2016` `2017` `2018` `2019`
## <chr> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl>
## 1 Aceh 2308. 2620. 36337. 4.57e3 4710. 5775. 5514. 5799. 7509.
## 2 Sumatera Utara 23238. 25981. 18120. 3.05e4 30254. 34427. 35617. 41769. 47112.
## 3 Sumatera Barat 9385. 11192. 14056. 1.41e4 13309. 14078. 15312. 15058. 14750.
## 4 Riau 3012. 4447. 8933. 6.36e3 7156. 8211. 8553. 10730. 10915.
## 5 Kep. Riau 1426. 2236. 3378. 2.56e3 3218. 4317. 4412. 5134. 6077.
## 6 Jambi 1868. 2138. 3047. 5.17e3 4978. 4398. 4404. 5657. 6486.
## 7 Sumatera Sela~ 7820. 9126. 8647. 1.00e4 10797. 12752. 13075. 14267. 14812.
## 8 Bengkulu 1153. 1201. 2378. 3.26e3 2791. 2889. 3620. 4150. 5789.
## 9 Lampung 7690. 6969. 3474. 9.45e3 8160. 9373. 12078. 13415. 17046.
## 10 Kep. Bangka B~ 0 0 0 1.37e1 1177. 1544. 1164. 1517. 3265.
## # ... with 2 more variables: `2020` <dbl>, `2021` <dbl>
datainflowsumatera %>%
filter(Propinsi == 'Aceh') %>%
count('2011', sort = TRUE)
## # A tibble: 1 x 2
## `"2011"` n
## <chr> <int>
## 1 2011 1
sumateraacehup1 <- datainflowsumatera %>%
mutate('2010' = datainflowsumatera$'2011'/2)
sumateraacehup1
## # A tibble: 10 x 13
## Propinsi `2011` `2012` `2013` `2014` `2015` `2016` `2017` `2018` `2019`
## <chr> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl>
## 1 Aceh 2308. 2620. 36337. 4.57e3 4710. 5775. 5514. 5799. 7509.
## 2 Sumatera Utara 23238. 25981. 18120. 3.05e4 30254. 34427. 35617. 41769. 47112.
## 3 Sumatera Barat 9385. 11192. 14056. 1.41e4 13309. 14078. 15312. 15058. 14750.
## 4 Riau 3012. 4447. 8933. 6.36e3 7156. 8211. 8553. 10730. 10915.
## 5 Kep. Riau 1426. 2236. 3378. 2.56e3 3218. 4317. 4412. 5134. 6077.
## 6 Jambi 1868. 2138. 3047. 5.17e3 4978. 4398. 4404. 5657. 6486.
## 7 Sumatera Sela~ 7820. 9126. 8647. 1.00e4 10797. 12752. 13075. 14267. 14812.
## 8 Bengkulu 1153. 1201. 2378. 3.26e3 2791. 2889. 3620. 4150. 5789.
## 9 Lampung 7690. 6969. 3474. 9.45e3 8160. 9373. 12078. 13415. 17046.
## 10 Kep. Bangka B~ 0 0 0 1.37e1 1177. 1544. 1164. 1517. 3265.
## # ... with 3 more variables: `2020` <dbl>, `2021` <dbl>, `2010` <dbl>
ggplot(data = datainflowsumatera, mapping = aes(x = Propinsi, y = `2011`)) +
geom_point()
