library(readxl)
## Warning: package 'readxl' was built under R version 4.1.2
manipulasioutflow <- read_excel(path = "D:/Matkul Sem2/Linear Algebra/pivot outflow jawa.xlsx")
manipulasioutflow
## # A tibble: 7 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 DKI Jak~ 1.02e5 1.36e5 1.49e5 1.52e5 1.64e5 1.71e5 1.82e5 1.88e5 1.98e5 1.64e5
## 2 Jawa 8.35e4 1.11e5 9.90e4 1.47e5 1.72e5 1.91e5 2.29e5 2.53e5 2.72e5 2.51e5
## 3 Jawa Ba~ 2.08e4 2.89e4 2.31e4 4.09e4 4.71e4 4.94e4 5.38e4 6.14e4 6.17e4 5.72e4
## 4 Jawa Te~ 2.00e4 2.85e4 2.95e4 3.91e4 4.68e4 5.37e4 6.28e4 6.94e4 7.24e4 7.23e4
## 5 Yogyaka~ 7.54e3 9.49e3 9.71e3 1.32e4 1.41e4 1.30e4 1.68e4 2.04e4 2.14e4 1.66e4
## 6 Jawa Ti~ 3.52e4 4.45e4 3.67e4 5.39e4 6.36e4 7.45e4 9.34e4 9.80e4 1.06e5 9.34e4
## 7 Banten 0 0 0 0 0 0 2.11e3 4.05e3 1.10e4 1.18e4
## # ... 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()
Bantentahun <- select(manipulasioutflow, '2012', '2017','2021')
Bantentahun
## # A tibble: 7 x 3
## `2012` `2017` `2021`
## <dbl> <dbl> <dbl>
## 1 136467. 181553. 94033.
## 2 111363. 228905. 143340.
## 3 28895. 53825. 34763.
## 4 28493. 62761. 44455.
## 5 9486. 16810. 9652.
## 6 44489. 93396. 46029.
## 7 0 2113. 8441.
library(tidyverse)
jawa2011 <- select(manipulasioutflow, '2011')
jawa2011
## # A tibble: 7 x 1
## `2011`
## <dbl>
## 1 101604.
## 2 83511.
## 3 20782.
## 4 19975.
## 5 7538.
## 6 35217.
## 7 0
library(tidyverse)
jawamin2011 <- select(manipulasioutflow, -'2011')
jawamin2011
## # A tibble: 7 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 DKI Jak~ 1.36e5 1.49e5 1.52e5 1.64e5 1.71e5 1.82e5 1.88e5 1.98e5 1.64e5 9.40e4
## 2 Jawa 1.11e5 9.90e4 1.47e5 1.72e5 1.91e5 2.29e5 2.53e5 2.72e5 2.51e5 1.43e5
## 3 Jawa Ba~ 2.89e4 2.31e4 4.09e4 4.71e4 4.94e4 5.38e4 6.14e4 6.17e4 5.72e4 3.48e4
## 4 Jawa Te~ 2.85e4 2.95e4 3.91e4 4.68e4 5.37e4 6.28e4 6.94e4 7.24e4 7.23e4 4.45e4
## 5 Yogyaka~ 9.49e3 9.71e3 1.32e4 1.41e4 1.30e4 1.68e4 2.04e4 2.14e4 1.66e4 9.65e3
## 6 Jawa Ti~ 4.45e4 3.67e4 5.39e4 6.36e4 7.45e4 9.34e4 9.80e4 1.06e5 9.34e4 4.60e4
## 7 Banten 0 0 0 0 0 2.11e3 4.05e3 1.10e4 1.18e4 8.44e3
library(dplyr)
jawatahun2 <- manipulasioutflow %>% rename('2010' = '2011')
head(jawatahun2)
## # 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 DKI Jak~ 1.02e5 1.36e5 1.49e5 1.52e5 1.64e5 1.71e5 1.82e5 1.88e5 1.98e5 1.64e5
## 2 Jawa 8.35e4 1.11e5 9.90e4 1.47e5 1.72e5 1.91e5 2.29e5 2.53e5 2.72e5 2.51e5
## 3 Jawa Ba~ 2.08e4 2.89e4 2.31e4 4.09e4 4.71e4 4.94e4 5.38e4 6.14e4 6.17e4 5.72e4
## 4 Jawa Te~ 2.00e4 2.85e4 2.95e4 3.91e4 4.68e4 5.37e4 6.28e4 6.94e4 7.24e4 7.23e4
## 5 Yogyaka~ 7.54e3 9.49e3 9.71e3 1.32e4 1.41e4 1.30e4 1.68e4 2.04e4 2.14e4 1.66e4
## 6 Jawa Ti~ 3.52e4 4.45e4 3.67e4 5.39e4 6.36e4 7.45e4 9.34e4 9.80e4 1.06e5 9.34e4
## # ... with 1 more variable: 2021 <dbl>
library(dplyr)
Bantentahun <- manipulasioutflow %>%
filter(Provinsi == 'banten') %>%
select('2011','2012')
Bantentahun
## # A tibble: 0 x 2
## # ... with 2 variables: 2011 <dbl>, 2012 <dbl>
library(dplyr)
jawa2 <- manipulasioutflow %>%
filter(Provinsi == 'jawa timur', Provinsi == 'jawa') %>%
select('2011','2012')
jawa2
## # A tibble: 0 x 2
## # ... with 2 variables: 2011 <dbl>, 2012 <dbl>
str(manipulasioutflow)
## tibble [7 x 12] (S3: tbl_df/tbl/data.frame)
## $ Provinsi: chr [1:7] "DKI Jakarta" "Jawa" "Jawa Barat" "Jawa Tengah" ...
## $ 2011 : num [1:7] 101604 83511 20782 19975 7538 ...
## $ 2012 : num [1:7] 136467 111363 28895 28493 9486 ...
## $ 2013 : num [1:7] 149241 98969 23067 29529 9708 ...
## $ 2014 : num [1:7] 152276 147069 40857 39110 13171 ...
## $ 2015 : num [1:7] 163750 171568 47063 46840 14080 ...
## $ 2016 : num [1:7] 170614 190568 49405 53659 13013 ...
## $ 2017 : num [1:7] 181553 228905 53825 62761 16810 ...
## $ 2018 : num [1:7] 187820 253125 61358 69368 20357 ...
## $ 2019 : num [1:7] 197818 271957 61692 72363 21353 ...
## $ 2020 : num [1:7] 163779 251363 57235 72342 16619 ...
## $ 2021 : num [1:7] 94033 143340 34763 44455 9652 ...
str(manipulasioutflow %>% group_by(Provinsi))
## grouped_df [7 x 12] (S3: grouped_df/tbl_df/tbl/data.frame)
## $ Provinsi: chr [1:7] "DKI Jakarta" "Jawa" "Jawa Barat" "Jawa Tengah" ...
## $ 2011 : num [1:7] 101604 83511 20782 19975 7538 ...
## $ 2012 : num [1:7] 136467 111363 28895 28493 9486 ...
## $ 2013 : num [1:7] 149241 98969 23067 29529 9708 ...
## $ 2014 : num [1:7] 152276 147069 40857 39110 13171 ...
## $ 2015 : num [1:7] 163750 171568 47063 46840 14080 ...
## $ 2016 : num [1:7] 170614 190568 49405 53659 13013 ...
## $ 2017 : num [1:7] 181553 228905 53825 62761 16810 ...
## $ 2018 : num [1:7] 187820 253125 61358 69368 20357 ...
## $ 2019 : num [1:7] 197818 271957 61692 72363 21353 ...
## $ 2020 : num [1:7] 163779 251363 57235 72342 16619 ...
## $ 2021 : num [1:7] 94033 143340 34763 44455 9652 ...
## - attr(*, "groups")= tibble [7 x 2] (S3: tbl_df/tbl/data.frame)
## ..$ Provinsi: chr [1:7] "Banten" "DKI Jakarta" "Jawa" "Jawa Barat" ...
## ..$ .rows : list<int> [1:7]
## .. ..$ : int 7
## .. ..$ : int 1
## .. ..$ : int 2
## .. ..$ : int 3
## .. ..$ : int 4
## .. ..$ : int 6
## .. ..$ : int 5
## .. ..@ ptype: int(0)
## ..- attr(*, ".drop")= logi TRUE
jawa3 <- manipulasioutflow %>%
group_by(Provinsi)
jawa3
## # A tibble: 7 x 12
## # Groups: Provinsi [7]
## Provinsi `2011` `2012` `2013` `2014` `2015` `2016` `2017` `2018` `2019` `2020`
## <chr> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl>
## 1 DKI Jak~ 1.02e5 1.36e5 1.49e5 1.52e5 1.64e5 1.71e5 1.82e5 1.88e5 1.98e5 1.64e5
## 2 Jawa 8.35e4 1.11e5 9.90e4 1.47e5 1.72e5 1.91e5 2.29e5 2.53e5 2.72e5 2.51e5
## 3 Jawa Ba~ 2.08e4 2.89e4 2.31e4 4.09e4 4.71e4 4.94e4 5.38e4 6.14e4 6.17e4 5.72e4
## 4 Jawa Te~ 2.00e4 2.85e4 2.95e4 3.91e4 4.68e4 5.37e4 6.28e4 6.94e4 7.24e4 7.23e4
## 5 Yogyaka~ 7.54e3 9.49e3 9.71e3 1.32e4 1.41e4 1.30e4 1.68e4 2.04e4 2.14e4 1.66e4
## 6 Jawa Ti~ 3.52e4 4.45e4 3.67e4 5.39e4 6.36e4 7.45e4 9.34e4 9.80e4 1.06e5 9.34e4
## 7 Banten 0 0 0 0 0 0 2.11e3 4.05e3 1.10e4 1.18e4
## # ... with 1 more variable: 2021 <dbl>
manipulasioutflow %>%
filter(Provinsi == 'jawa barat') %>%
count('2011', sort = TRUE)
## # A tibble: 0 x 2
## # ... with 2 variables: "2011" <chr>, n <int>
jawa4 <- manipulasioutflow %>%
mutate('2010' = manipulasioutflow$'2011'/2)
jawa4
## # A tibble: 7 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 DKI Jak~ 1.02e5 1.36e5 1.49e5 1.52e5 1.64e5 1.71e5 1.82e5 1.88e5 1.98e5 1.64e5
## 2 Jawa 8.35e4 1.11e5 9.90e4 1.47e5 1.72e5 1.91e5 2.29e5 2.53e5 2.72e5 2.51e5
## 3 Jawa Ba~ 2.08e4 2.89e4 2.31e4 4.09e4 4.71e4 4.94e4 5.38e4 6.14e4 6.17e4 5.72e4
## 4 Jawa Te~ 2.00e4 2.85e4 2.95e4 3.91e4 4.68e4 5.37e4 6.28e4 6.94e4 7.24e4 7.23e4
## 5 Yogyaka~ 7.54e3 9.49e3 9.71e3 1.32e4 1.41e4 1.30e4 1.68e4 2.04e4 2.14e4 1.66e4
## 6 Jawa Ti~ 3.52e4 4.45e4 3.67e4 5.39e4 6.36e4 7.45e4 9.34e4 9.80e4 1.06e5 9.34e4
## 7 Banten 0 0 0 0 0 0 2.11e3 4.05e3 1.10e4 1.18e4
## # ... 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()
