Copy Right @Abdullah Umar @Prof Dr Suhartono M.Kom @Magister Informatika UIN Maulana Malik
Ini merupakan ujicoba Dasar Relational Data sains dengan RStudio
Langkah 1
library(tidyverse)
## Warning: package 'tidyverse' was built under R version 4.0.4
## -- Attaching packages --------------------------------------- tidyverse 1.3.0 --
## v ggplot2 3.3.3 v purrr 0.3.4
## v tibble 3.1.0 v dplyr 1.0.5
## v tidyr 1.1.3 v stringr 1.4.0
## v readr 1.4.0 v forcats 0.5.1
## Warning: package 'ggplot2' was built under R version 4.0.4
## Warning: package 'tibble' was built under R version 4.0.4
## Warning: package 'tidyr' was built under R version 4.0.4
## Warning: package 'readr' was built under R version 4.0.4
## Warning: package 'purrr' was built under R version 4.0.4
## Warning: package 'dplyr' was built under R version 4.0.4
## Warning: package 'stringr' was built under R version 4.0.4
## Warning: package 'forcats' was built under R version 4.0.4
## -- Conflicts ------------------------------------------ tidyverse_conflicts() --
## x dplyr::filter() masks stats::filter()
## x dplyr::lag() masks stats::lag()
Langkah 2
x <- tribble(
~key, ~val_x,
1, "x1",
2, "x2",
3, "x3"
)
y <- tribble(
~key, ~val_y,
1, "y1",
2, "y2",
4, "y3"
)
Langkah 3
x
## # A tibble: 3 x 2
## key val_x
## <dbl> <chr>
## 1 1 x1
## 2 2 x2
## 3 3 x3
y
## # A tibble: 3 x 2
## key val_y
## <dbl> <chr>
## 1 1 y1
## 2 2 y2
## 3 4 y3
Langkah 4
x %>%
inner_join(y, by = "key")
## # A tibble: 2 x 3
## key val_x val_y
## <dbl> <chr> <chr>
## 1 1 x1 y1
## 2 2 x2 y2
Langkah 5
x <- tribble(
~key, ~val_x,
1, "x1",
2, "x2",
3, "x3"
)
y <- tribble(
~key, ~val_y,
1, "y1",
2, "y2",
4, "y3"
)
Langkah 6
left_join(x,y)
## Joining, by = "key"
## # A tibble: 3 x 3
## key val_x val_y
## <dbl> <chr> <chr>
## 1 1 x1 y1
## 2 2 x2 y2
## 3 3 x3 <NA>
Langkah 7
right_join(x,y)
## Joining, by = "key"
## # A tibble: 3 x 3
## key val_x val_y
## <dbl> <chr> <chr>
## 1 1 x1 y1
## 2 2 x2 y2
## 3 4 <NA> y3
Langkah 8
full_join(x,y)
## Joining, by = "key"
## # A tibble: 4 x 3
## key val_x val_y
## <dbl> <chr> <chr>
## 1 1 x1 y1
## 2 2 x2 y2
## 3 3 x3 <NA>
## 4 4 <NA> y3
Langkah 9
x <- tribble(
~key, ~val_x,
1, "x1",
2, "x2",
2, "x3",
1, "x4"
)
y <- tribble(
~key, ~val_y,
1, "y1",
2, "y2"
)
Langkah 10
left_join(x, y, by = "key")
## # A tibble: 4 x 3
## key val_x val_y
## <dbl> <chr> <chr>
## 1 1 x1 y1
## 2 2 x2 y2
## 3 2 x3 y2
## 4 1 x4 y1
Langkah 11
x <- tribble(
~key, ~val_x,
1, "x1",
2, "x2",
2, "x3",
3, "x4"
)
y <- tribble(
~key, ~val_y,
1, "y1",
2, "y2",
2, "y3",
3, "y4"
)
left_join(x, y, by = "key")
## # A tibble: 6 x 3
## key val_x val_y
## <dbl> <chr> <chr>
## 1 1 x1 y1
## 2 2 x2 y2
## 3 2 x2 y3
## 4 2 x3 y2
## 5 2 x3 y3
## 6 3 x4 y4
Langkah 12
x <- tribble(
~key, ~val_x,
1, "x1",
2, "x2",
3, "x3"
)
y <- tribble(
~key, ~val_y,
1, "y1",
2, "y2",
4, "y3"
)
semi_join(x, y, by = "key")
## # A tibble: 2 x 2
## key val_x
## <dbl> <chr>
## 1 1 x1
## 2 2 x2
Langkah 13
x <- tribble(
~key, ~val_x,
1, "x1",
2, "x2",
2, "x3",
3, "x4"
)
y <- tribble(
~key, ~val_y,
1, "y1",
2, "y2",
2, "y3",
3, "y4"
)
semi_join(x, y, by = "key")
## # A tibble: 4 x 2
## key val_x
## <dbl> <chr>
## 1 1 x1
## 2 2 x2
## 3 2 x3
## 4 3 x4
Langkah 14
x <- tribble(
~key, ~val_x,
1, "x1",
2, "x2",
3, "x3"
)
y <- tribble(
~key, ~val_y,
1, "y1",
2, "y2",
4, "y3"
)
anti_join(x, y, by = "key")
## # A tibble: 1 x 2
## key val_x
## <dbl> <chr>
## 1 3 x3
Langkah 15
df1 <- tribble(
~x, ~y,
1, 1,
2, 1
)
df2 <- tribble(
~x, ~y,
1, 1,
1, 2
)
df2
## # A tibble: 2 x 2
## x y
## <dbl> <dbl>
## 1 1 1
## 2 1 2
Langkah 16
intersect(df1, df2)
## # A tibble: 1 x 2
## x y
## <dbl> <dbl>
## 1 1 1
Langkah 17
union(df1, df2)
## # A tibble: 3 x 2
## x y
## <dbl> <dbl>
## 1 1 1
## 2 2 1
## 3 1 2
Langkah 18
setdiff(df1, df2)
## # A tibble: 1 x 2
## x y
## <dbl> <dbl>
## 1 2 1
Langkah 19
setdiff(df2, df1)
## # A tibble: 1 x 2
## x y
## <dbl> <dbl>
## 1 1 2