library(readxl)
## Warning: package 'readxl' was built under R version 4.1.2
manipulasiinflow2 <- read_excel(path = "D:/Matkul Sem2/Linear Algebra/pivot inflow jawa.xlsx")
manipulasiinflow2
## # A tibble: 6 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 Jawa 1.24e5 1.60e5 1.35e5 2.17e5 2.30e5 2.62e5 2.78e5 3.07e5 3.25e5 2.59e5
## 2 Jawa Ba~ 4.38e4 6.06e4 3.52e4 7.87e4 8.13e4 8.80e4 8.32e4 8.72e4 9.48e4 7.69e4
## 3 Jawa Te~ 3.51e4 4.33e4 4.22e4 6.05e4 6.52e4 7.28e4 7.70e4 8.78e4 9.08e4 8.50e4
## 4 Yogyaka~ 6.49e3 9.17e3 8.94e3 1.39e4 1.48e4 1.74e4 1.75e4 2.06e4 2.09e4 7.35e3
## 5 Jawa Ti~ 3.85e4 4.74e4 4.87e4 6.43e4 6.88e4 8.34e4 9.84e4 1.06e5 1.14e5 8.68e4
## 6 Banten 0 0 0 0 0 0 1.49e3 4.83e3 4.48e3 3.40e3
## # ... 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()
jawatimurtahun <- select(manipulasiinflow2, '2012', '2017','2021')
jawatimurtahun
## # A tibble: 6 x 3
## `2012` `2017` `2021`
## <dbl> <dbl> <dbl>
## 1 160482. 277609. 187816.
## 2 60629. 83220. 57295.
## 3 43298. 77031. 62024.
## 4 9173. 17483. 6714.
## 5 47383. 98380. 58986.
## 6 0 1495. 2798.
library(tidyverse)
jawatimur2011 <- select(manipulasiinflow2, '2011')
jawatimur2011
## # A tibble: 6 x 1
## `2011`
## <dbl>
## 1 123917.
## 2 43775.
## 3 35137.
## 4 6490.
## 5 38515.
## 6 0
library(tidyverse)
jawatimurmin2011 <- select(manipulasiinflow2, -'2011')
jawatimurmin2011
## # A tibble: 6 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 Jawa 1.60e5 1.35e5 2.17e5 2.30e5 2.62e5 2.78e5 3.07e5 3.25e5 2.59e5 1.88e5
## 2 Jawa Ba~ 6.06e4 3.52e4 7.87e4 8.13e4 8.80e4 8.32e4 8.72e4 9.48e4 7.69e4 5.73e4
## 3 Jawa Te~ 4.33e4 4.22e4 6.05e4 6.52e4 7.28e4 7.70e4 8.78e4 9.08e4 8.50e4 6.20e4
## 4 Yogyaka~ 9.17e3 8.94e3 1.39e4 1.48e4 1.74e4 1.75e4 2.06e4 2.09e4 7.35e3 6.71e3
## 5 Jawa Ti~ 4.74e4 4.87e4 6.43e4 6.88e4 8.34e4 9.84e4 1.06e5 1.14e5 8.68e4 5.90e4
## 6 Banten 0 0 0 0 0 1.49e3 4.83e3 4.48e3 3.40e3 2.80e3
library(dplyr)
bantentahun2 <- manipulasiinflow2 %>% rename('2010' = '2011')
head(bantentahun2)
## # 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 Jawa 1.24e5 1.60e5 1.35e5 2.17e5 2.30e5 2.62e5 2.78e5 3.07e5 3.25e5 2.59e5
## 2 Jawa Ba~ 4.38e4 6.06e4 3.52e4 7.87e4 8.13e4 8.80e4 8.32e4 8.72e4 9.48e4 7.69e4
## 3 Jawa Te~ 3.51e4 4.33e4 4.22e4 6.05e4 6.52e4 7.28e4 7.70e4 8.78e4 9.08e4 8.50e4
## 4 Yogyaka~ 6.49e3 9.17e3 8.94e3 1.39e4 1.48e4 1.74e4 1.75e4 2.06e4 2.09e4 7.35e3
## 5 Jawa Ti~ 3.85e4 4.74e4 4.87e4 6.43e4 6.88e4 8.34e4 9.84e4 1.06e5 1.14e5 8.68e4
## 6 Banten 0 0 0 0 0 0 1.49e3 4.83e3 4.48e3 3.40e3
## # ... with 1 more variable: 2021 <dbl>
library(dplyr)
yogyakarta <- manipulasiinflow2 %>%
filter(Provinsi == 'yogyakarta') %>%
select('2011','2012')
yogyakarta
## # A tibble: 0 x 2
## # ... with 2 variables: 2011 <dbl>, 2012 <dbl>
library(dplyr)
jawa2 <- manipulasiinflow2 %>%
filter(Provinsi == 'yogyakarta', Provinsi == 'jawa barat') %>%
select('2011','2012')
jawa2
## # A tibble: 0 x 2
## # ... with 2 variables: 2011 <dbl>, 2012 <dbl>
str(manipulasiinflow2)
## tibble [6 x 12] (S3: tbl_df/tbl/data.frame)
## $ Provinsi: chr [1:6] "Jawa" "Jawa Barat" "Jawa Tengah" "Yogyakarta" ...
## $ 2011 : num [1:6] 123917 43775 35137 6490 38515 ...
## $ 2012 : num [1:6] 160482 60629 43298 9173 47383 ...
## $ 2013 : num [1:6] 134998 35190 42182 8939 48687 ...
## $ 2014 : num [1:6] 217303 78660 60476 13890 64276 ...
## $ 2015 : num [1:6] 230141 81303 65198 14831 68808 ...
## $ 2016 : num [1:6] 261607 88036 72782 17350 83439 ...
## $ 2017 : num [1:6] 277609 83220 77031 17483 98380 ...
## $ 2018 : num [1:6] 306911 87243 87829 20574 106433 ...
## $ 2019 : num [1:6] 324624 94846 90751 20899 113651 ...
## $ 2020 : num [1:6] 259444 76883 84970 7348 86848 ...
## $ 2021 : num [1:6] 187816 57295 62024 6714 58986 ...
str(manipulasiinflow2 %>% group_by(Provinsi))
## grouped_df [6 x 12] (S3: grouped_df/tbl_df/tbl/data.frame)
## $ Provinsi: chr [1:6] "Jawa" "Jawa Barat" "Jawa Tengah" "Yogyakarta" ...
## $ 2011 : num [1:6] 123917 43775 35137 6490 38515 ...
## $ 2012 : num [1:6] 160482 60629 43298 9173 47383 ...
## $ 2013 : num [1:6] 134998 35190 42182 8939 48687 ...
## $ 2014 : num [1:6] 217303 78660 60476 13890 64276 ...
## $ 2015 : num [1:6] 230141 81303 65198 14831 68808 ...
## $ 2016 : num [1:6] 261607 88036 72782 17350 83439 ...
## $ 2017 : num [1:6] 277609 83220 77031 17483 98380 ...
## $ 2018 : num [1:6] 306911 87243 87829 20574 106433 ...
## $ 2019 : num [1:6] 324624 94846 90751 20899 113651 ...
## $ 2020 : num [1:6] 259444 76883 84970 7348 86848 ...
## $ 2021 : num [1:6] 187816 57295 62024 6714 58986 ...
## - attr(*, "groups")= tibble [6 x 2] (S3: tbl_df/tbl/data.frame)
## ..$ Provinsi: chr [1:6] "Banten" "Jawa" "Jawa Barat" "Jawa Tengah" ...
## ..$ .rows : list<int> [1:6]
## .. ..$ : int 6
## .. ..$ : int 1
## .. ..$ : int 2
## .. ..$ : int 3
## .. ..$ : int 5
## .. ..$ : int 4
## .. ..@ ptype: int(0)
## ..- attr(*, ".drop")= logi TRUE
jawa3 <- manipulasiinflow2 %>%
group_by(Provinsi)
jawa2
## # A tibble: 0 x 2
## # ... with 2 variables: 2011 <dbl>, 2012 <dbl>
manipulasiinflow2 %>%
filter(Provinsi == 'Banten') %>%
count('2011', sort = TRUE)
## # A tibble: 1 x 2
## `"2011"` n
## <chr> <int>
## 1 2011 1
jawa4 <- manipulasiinflow2%>%
mutate('2010' = manipulasiinflow2$'2011'/2)
jawa4
## # A tibble: 6 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 Jawa 1.24e5 1.60e5 1.35e5 2.17e5 2.30e5 2.62e5 2.78e5 3.07e5 3.25e5 2.59e5
## 2 Jawa Ba~ 4.38e4 6.06e4 3.52e4 7.87e4 8.13e4 8.80e4 8.32e4 8.72e4 9.48e4 7.69e4
## 3 Jawa Te~ 3.51e4 4.33e4 4.22e4 6.05e4 6.52e4 7.28e4 7.70e4 8.78e4 9.08e4 8.50e4
## 4 Yogyaka~ 6.49e3 9.17e3 8.94e3 1.39e4 1.48e4 1.74e4 1.75e4 2.06e4 2.09e4 7.35e3
## 5 Jawa Ti~ 3.85e4 4.74e4 4.87e4 6.43e4 6.88e4 8.34e4 9.84e4 1.06e5 1.14e5 8.68e4
## 6 Banten 0 0 0 0 0 0 1.49e3 4.83e3 4.48e3 3.40e3
## # ... with 2 more variables: 2021 <dbl>, 2010 <dbl>
ggplot(data = manipulasiinflow2, mapping = aes(x = Provinsi, y = `2011`)) +
geom_point()
ggplot(data = manipulasiinflow2, mapping = aes(x = Provinsi, y = `2012`)) +
geom_point()
