library(readxl)
## Warning: package 'readxl' was built under R version 4.1.2
manipulasioutflow <- read_excel(path = "D:/Matkul Sem2/Linear Algebra/pivot outflow sumatera.xlsx")
manipulasioutflow
## # A tibble: 8 x 12
## Provinsi `2011` `2012` `2013` `2014` `2015` `2016` `2017` `2018` `2019` `2020`
## <chr> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl>
## 1 Sumatera 80092. 85235. 1.03e5 1.02e5 1.09e5 1.22e5 1.34e5 1.36e5 1.53e5 1.41e5
## 2 Sumater~ 22176. 22495. 1.92e4 2.64e4 2.79e4 3.20e4 3.52e4 3.69e4 4.41e4 3.98e4
## 3 Sumater~ 5300. 6434. 6.51e3 7.06e3 7.47e3 9.20e3 1.08e4 8.45e3 9.46e3 8.76e3
## 4 Jambi 5217. 5013. 6.30e3 8.36e3 8.32e3 7.77e3 8.43e3 8.46e3 9.20e3 8.95e3
## 5 Sumater~ 14524. 15600. 1.27e4 1.34e4 1.35e4 1.58e4 1.70e4 1.79e4 1.91e4 1.83e4
## 6 Bengkulu 2561. 2959. 6.49e3 4.58e3 4.85e3 5.16e3 5.45e3 5.50e3 6.84e3 6.56e3
## 7 Lampung 5724. 6376. 4.57e3 8.34e3 9.95e3 1.04e4 1.34e4 1.37e4 1.56e4 1.39e4
## 8 Kep. Ba~ 0 0 0 3.22e2 2.00e3 2.68e3 2.75e3 2.74e3 4.17e3 3.90e3
## # ... with 1 more variable: 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 3.1.4 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 'tidyr' was built under R version 4.1.2
## Warning: package 'readr' was built under R version 4.1.2
## Warning: package 'purrr' was built under R version 4.1.2
## Warning: package 'dplyr' was built under R version 4.1.2
## Warning: package 'forcats' was built under R version 4.1.2
## -- Conflicts ------------------------------------------ tidyverse_conflicts() --
## x dplyr::filter() masks stats::filter()
## x dplyr::lag() masks stats::lag()
lampungtahun <- select(manipulasioutflow, '2012', '2017','2021')
lampungtahun
## # A tibble: 8 x 3
## `2012` `2017` `2021`
## <dbl> <dbl> <dbl>
## 1 85235. 133606. 86627.
## 2 22495. 35243. 23453.
## 3 6434. 10754. 5941.
## 4 5013. 8434. 6046.
## 5 15600. 16981. 11436.
## 6 2959. 5447. 4681.
## 7 6376. 13359. 8050.
## 8 0 2750. 3493.
library(tidyverse)
sumatera2011 <- select(manipulasioutflow, '2011')
sumatera2011
## # A tibble: 8 x 1
## `2011`
## <dbl>
## 1 80092.
## 2 22176.
## 3 5300.
## 4 5217.
## 5 14524.
## 6 2561.
## 7 5724.
## 8 0
library(tidyverse)
sumateramin2011 <- select(manipulasioutflow, -'2011')
sumateramin2011
## # A tibble: 8 x 11
## Provinsi `2012` `2013` `2014` `2015` `2016` `2017` `2018` `2019` `2020` `2021`
## <chr> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl>
## 1 Sumatera 85235. 1.03e5 1.02e5 1.09e5 1.22e5 1.34e5 1.36e5 1.53e5 1.41e5 86627.
## 2 Sumater~ 22495. 1.92e4 2.64e4 2.79e4 3.20e4 3.52e4 3.69e4 4.41e4 3.98e4 23453.
## 3 Sumater~ 6434. 6.51e3 7.06e3 7.47e3 9.20e3 1.08e4 8.45e3 9.46e3 8.76e3 5941.
## 4 Jambi 5013. 6.30e3 8.36e3 8.32e3 7.77e3 8.43e3 8.46e3 9.20e3 8.95e3 6046.
## 5 Sumater~ 15600. 1.27e4 1.34e4 1.35e4 1.58e4 1.70e4 1.79e4 1.91e4 1.83e4 11436.
## 6 Bengkulu 2959. 6.49e3 4.58e3 4.85e3 5.16e3 5.45e3 5.50e3 6.84e3 6.56e3 4681.
## 7 Lampung 6376. 4.57e3 8.34e3 9.95e3 1.04e4 1.34e4 1.37e4 1.56e4 1.39e4 8050.
## 8 Kep. Ba~ 0 0 3.22e2 2.00e3 2.68e3 2.75e3 2.74e3 4.17e3 3.90e3 3493.
library(dplyr)
sumateratahun2 <- manipulasioutflow %>% rename('2010' = '2011')
head(sumateratahun2)
## # A tibble: 6 x 12
## Provinsi `2010` `2012` `2013` `2014` `2015` `2016` `2017` `2018` `2019` `2020`
## <chr> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl>
## 1 Sumatera 80092. 85235. 1.03e5 1.02e5 1.09e5 1.22e5 1.34e5 1.36e5 1.53e5 1.41e5
## 2 Sumater~ 22176. 22495. 1.92e4 2.64e4 2.79e4 3.20e4 3.52e4 3.69e4 4.41e4 3.98e4
## 3 Sumater~ 5300. 6434. 6.51e3 7.06e3 7.47e3 9.20e3 1.08e4 8.45e3 9.46e3 8.76e3
## 4 Jambi 5217. 5013. 6.30e3 8.36e3 8.32e3 7.77e3 8.43e3 8.46e3 9.20e3 8.95e3
## 5 Sumater~ 14524. 15600. 1.27e4 1.34e4 1.35e4 1.58e4 1.70e4 1.79e4 1.91e4 1.83e4
## 6 Bengkulu 2561. 2959. 6.49e3 4.58e3 4.85e3 5.16e3 5.45e3 5.50e3 6.84e3 6.56e3
## # ... with 1 more variable: 2021 <dbl>
library(dplyr)
bengkulu <- manipulasioutflow %>%
filter(Provinsi == 'bengkulu') %>%
select('2011','2012')
bengkulu
## # A tibble: 0 x 2
## # ... with 2 variables: 2011 <dbl>, 2012 <dbl>
library(dplyr)
sumatera2 <- manipulasioutflow %>%
filter(Provinsi == 'jambi', Provinsi == 'Bengkulu') %>%
select('2011','2012')
sumatera2
## # A tibble: 0 x 2
## # ... with 2 variables: 2011 <dbl>, 2012 <dbl>
str(manipulasioutflow)
## tibble [8 x 12] (S3: tbl_df/tbl/data.frame)
## $ Provinsi: chr [1:8] "Sumatera" "Sumatera Utara" "Sumatera Barat" "Jambi" ...
## $ 2011 : num [1:8] 80092 22176 5300 5217 14524 ...
## $ 2012 : num [1:8] 85235 22495 6434 5013 15600 ...
## $ 2013 : num [1:8] 103288 19235 6511 6302 12693 ...
## $ 2014 : num [1:8] 102338 26391 7060 8361 13372 ...
## $ 2015 : num [1:8] 109186 27877 7471 8325 13484 ...
## $ 2016 : num [1:8] 121992 31959 9198 7774 15756 ...
## $ 2017 : num [1:8] 133606 35243 10754 8434 16981 ...
## $ 2018 : num [1:8] 135676 36908 8447 8459 17931 ...
## $ 2019 : num [1:8] 153484 44051 9465 9204 19121 ...
## $ 2020 : num [1:8] 140589 39758 8763 8950 18309 ...
## $ 2021 : num [1:8] 86627 23453 5941 6046 11436 ...
str(manipulasioutflow %>% group_by(Provinsi))
## grouped_df [8 x 12] (S3: grouped_df/tbl_df/tbl/data.frame)
## $ Provinsi: chr [1:8] "Sumatera" "Sumatera Utara" "Sumatera Barat" "Jambi" ...
## $ 2011 : num [1:8] 80092 22176 5300 5217 14524 ...
## $ 2012 : num [1:8] 85235 22495 6434 5013 15600 ...
## $ 2013 : num [1:8] 103288 19235 6511 6302 12693 ...
## $ 2014 : num [1:8] 102338 26391 7060 8361 13372 ...
## $ 2015 : num [1:8] 109186 27877 7471 8325 13484 ...
## $ 2016 : num [1:8] 121992 31959 9198 7774 15756 ...
## $ 2017 : num [1:8] 133606 35243 10754 8434 16981 ...
## $ 2018 : num [1:8] 135676 36908 8447 8459 17931 ...
## $ 2019 : num [1:8] 153484 44051 9465 9204 19121 ...
## $ 2020 : num [1:8] 140589 39758 8763 8950 18309 ...
## $ 2021 : num [1:8] 86627 23453 5941 6046 11436 ...
## - attr(*, "groups")= tibble [8 x 2] (S3: tbl_df/tbl/data.frame)
## ..$ Provinsi: chr [1:8] "Bengkulu" "Jambi" "Kep. Bangka Belitung" "Lampung" ...
## ..$ .rows : list<int> [1:8]
## .. ..$ : int 6
## .. ..$ : int 4
## .. ..$ : int 8
## .. ..$ : int 7
## .. ..$ : int 1
## .. ..$ : int 3
## .. ..$ : int 5
## .. ..$ : int 2
## .. ..@ ptype: int(0)
## ..- attr(*, ".drop")= logi TRUE
sumatera3 <- manipulasioutflow %>%
group_by(Provinsi)
sumatera3
## # A tibble: 8 x 12
## # Groups: Provinsi [8]
## Provinsi `2011` `2012` `2013` `2014` `2015` `2016` `2017` `2018` `2019` `2020`
## <chr> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl>
## 1 Sumatera 80092. 85235. 1.03e5 1.02e5 1.09e5 1.22e5 1.34e5 1.36e5 1.53e5 1.41e5
## 2 Sumater~ 22176. 22495. 1.92e4 2.64e4 2.79e4 3.20e4 3.52e4 3.69e4 4.41e4 3.98e4
## 3 Sumater~ 5300. 6434. 6.51e3 7.06e3 7.47e3 9.20e3 1.08e4 8.45e3 9.46e3 8.76e3
## 4 Jambi 5217. 5013. 6.30e3 8.36e3 8.32e3 7.77e3 8.43e3 8.46e3 9.20e3 8.95e3
## 5 Sumater~ 14524. 15600. 1.27e4 1.34e4 1.35e4 1.58e4 1.70e4 1.79e4 1.91e4 1.83e4
## 6 Bengkulu 2561. 2959. 6.49e3 4.58e3 4.85e3 5.16e3 5.45e3 5.50e3 6.84e3 6.56e3
## 7 Lampung 5724. 6376. 4.57e3 8.34e3 9.95e3 1.04e4 1.34e4 1.37e4 1.56e4 1.39e4
## 8 Kep. Ba~ 0 0 0 3.22e2 2.00e3 2.68e3 2.75e3 2.74e3 4.17e3 3.90e3
## # ... with 1 more variable: 2021 <dbl>
manipulasioutflow %>%
filter(Provinsi == 'jambi') %>%
count('2011', sort = TRUE)
## # A tibble: 0 x 2
## # ... with 2 variables: "2011" <chr>, n <int>
sumatera4 <- manipulasioutflow %>%
mutate('2010' = manipulasioutflow$'2011'/2)
sumatera4
## # A tibble: 8 x 13
## Provinsi `2011` `2012` `2013` `2014` `2015` `2016` `2017` `2018` `2019` `2020`
## <chr> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl>
## 1 Sumatera 80092. 85235. 1.03e5 1.02e5 1.09e5 1.22e5 1.34e5 1.36e5 1.53e5 1.41e5
## 2 Sumater~ 22176. 22495. 1.92e4 2.64e4 2.79e4 3.20e4 3.52e4 3.69e4 4.41e4 3.98e4
## 3 Sumater~ 5300. 6434. 6.51e3 7.06e3 7.47e3 9.20e3 1.08e4 8.45e3 9.46e3 8.76e3
## 4 Jambi 5217. 5013. 6.30e3 8.36e3 8.32e3 7.77e3 8.43e3 8.46e3 9.20e3 8.95e3
## 5 Sumater~ 14524. 15600. 1.27e4 1.34e4 1.35e4 1.58e4 1.70e4 1.79e4 1.91e4 1.83e4
## 6 Bengkulu 2561. 2959. 6.49e3 4.58e3 4.85e3 5.16e3 5.45e3 5.50e3 6.84e3 6.56e3
## 7 Lampung 5724. 6376. 4.57e3 8.34e3 9.95e3 1.04e4 1.34e4 1.37e4 1.56e4 1.39e4
## 8 Kep. Ba~ 0 0 0 3.22e2 2.00e3 2.68e3 2.75e3 2.74e3 4.17e3 3.90e3
## # ... with 2 more variables: 2021 <dbl>, 2010 <dbl>
ggplot(data = manipulasioutflow, mapping = aes(x = Provinsi, y = `2011`)) +
geom_point()
ggplot(data = manipulasioutflow, mapping = aes(x = Provinsi, y = `2012`)) +
geom_point()
