SLIDE 1
id sex age 1 m 19 2 m 22 3 NA NA 4 f 19 5 f 18 id score 2 10 3 18 4 21 4 23 5 9 5 11 6 11 6 12 7 3
Data Relations id score id sex age 2 10 1 m 19 3 18 2 m - - PowerPoint PPT Presentation
Data Relations id score id sex age 2 10 1 m 19 3 18 2 m - - PowerPoint PPT Presentation
Data Relations id score id sex age 2 10 1 m 19 3 18 2 m 22 4 21 3 NA NA 4 23 4 f 19 5 9 5 f 18 5 11 6 11 6 12 7 3 *_join(x, y) x y *_join(subject, exp, id) id score id sex age 2 10 1 m 19 3 18
SLIDE 2
SLIDE 3
id sex age 1 m 19 2 m 22 3 NA NA 4 f 19 5 f 18 id score 2 10 3 18 4 21 4 23 5 9 5 11 6 11 6 12 7 3
*_join(subject, exp, “id”)
SLIDE 4
x y left_join(x, y)
SLIDE 5
left_join(subject, exp)
id sex age 1 m 19 2 m 22 3 NA NA 4 f 19 5 f 18 id score 2 10 3 18 4 21 4 23 5 9 5 11 6 11 6 12 7 3 id sex age score 1 m 19 NA 2 m 22 10 3 NA NA 18 4 f 19 21 4 f 19 23 5 f 18 9 5 f 18 11
SLIDE 6
x y left_join(y, x)
SLIDE 7
left_join(exp, subject)
id sex age 1 m 19 2 m 22 3 NA NA 4 f 19 5 f 18 id score 2 10 3 18 4 21 4 23 5 9 5 11 6 11 6 12 7 3 id score sex age 2 10 m 22 3 18 NA NA 4 21 f 19 4 23 f 19 5 9 f 18 5 11 f 18 6 11 NA NA 6 12 NA NA 7 3 NA NA
SLIDE 8
x y right_join(x, y)
SLIDE 9
right_join(x, y)
id sex age 1 m 19 2 m 22 3 NA NA 4 f 19 5 f 18 id score 2 10 3 18 4 21 4 23 5 9 5 11 6 11 6 12 7 3 id sex age score 2 m 22 10 3 NA NA 18 4 f 19 21 4 f 19 23 5 f 18 9 5 f 18 11 6 NA NA 11 6 NA NA 12 7 NA NA 3
SLIDE 10
x y inner_join(x, y)
SLIDE 11
id sex age 1 m 19 2 m 22 3 NA NA 4 f 19 5 f 18 id score 2 10 3 18 4 21 4 23 5 9 5 11 6 11 6 12 7 3
inner_join(subject, exp)
id sex age score 2 m 22 10 3 NA NA 18 4 f 19 21 4 f 19 23 5 f 18 9 5 f 18 11
SLIDE 12
x y full_join(x, y)
SLIDE 13
id sex age 1 m 19 2 m 22 3 NA NA 4 f 19 5 f 18 id score 2 10 3 18 4 21 4 23 5 9 5 11 6 11 6 12 7 3
full_join(subject, exp)
id sex age score 1 m 19 NA 2 m 22 10 3 NA NA 18 4 f 19 21 4 f 19 23 5 f 18 9 5 f 18 11 6 NA NA 11 6 NA NA 12 7 NA NA 3
SLIDE 14
x y semi_join(x, y)
*only columns from x; no duplicate rows, even if >1 match in y
SLIDE 15
id sex age 1 m 19 2 m 22 3 NA NA 4 f 19 5 f 18 id score 2 10 3 18 4 21 4 23 5 9 5 11 6 11 6 12 7 3
semi_join(subject, exp)
id sex age 2 m 22 3 NA NA 4 f 19 5 f 18
SLIDE 16
x y semi_join(y, x)
*only columns from y; no duplicate rows, even if >1 match in x
SLIDE 17
id score 2 10 3 18 4 21 4 23 5 9 5 11
semi_join(exp, subject)
id sex age 1 m 19 2 m 22 3 NA NA 4 f 19 5 f 18 id score 2 10 3 18 4 21 4 23 5 9 5 11 6 11 6 12 7 3
SLIDE 18
x y anti_join(x, y)
SLIDE 19
id sex age 1 m 19 2 m 22 3 NA NA 4 f 19 5 f 18 id score 2 10 3 18 4 21 4 23 5 9 5 11 6 11 6 12 7 3
anti_join(subject, exp)
id sex age 1 m 19
SLIDE 20
x y anti_join(y, x)
SLIDE 21
anti_join(exp, subject)
id score 6 11 6 12 7 3 id sex age 1 m 19 2 m 22 3 NA NA 4 f 19 5 f 18 id score 2 10 3 18 4 21 4 23 5 9 5 11 6 11 6 12 7 3
SLIDE 22
id sex age 1 m 19 2 m 22 3 NA NA 4 f 19 5 f 18
bind_rows(subject, new_subjects)
id sex age 6 m 19 7 m 16 8 f 20 9 f 19 id sex age 1 m 19 2 m 22 3 NA NA 4 f 19 5 f 18 6 m 19 7 m 16 8 f 20 9 f 19
+ =
SLIDE 23
id sex age 1 m 19 2 m 22 3 NA NA 4 f 19 5 f 18
bind_cols(subject, new_info)
colour red
- range
yellow green blue
+ =
id sex age colour 1 m 19 red 2 m 22 orange 3 NA NA yellow 4 f 19 green 5 f 18 blue
SLIDE 24
id sex age 1 m 19 2 m 22 3 NA NA 4 f 19 5 f 18
intersect(subject, new_subjects)
id sex age 4 f 19 5 f 18 6 m 19 7 m 16 8 f 20 9 f 19 id sex age 4 f 19 5 f 18
=
SLIDE 25
union(subject, new_subjects)
id sex age 4 f 19 5 f 18 6 m 19 7 m 16 8 f 20 9 f 19
=
id sex age 1 m 19 2 m 22 3 NA NA 4 f 19 5 f 18 6 m 19 7 m 16 8 f 20 9 f 19 id sex age 1 m 19 2 m 22 3 NA NA 4 f 19 5 f 18
SLIDE 26
setdiff(subject, new_subjects)
id sex age 4 f 19 5 f 18 6 m 19 7 m 16 8 f 20 9 f 19
=
id sex age 1 m 19 2 m 22 3 NA NA id sex age 1 m 19 2 m 22 3 NA NA 4 f 19 5 f 18
SLIDE 27
setdiff(new_subjects, subject)
id sex age 4 f 19 5 f 18 6 m 19 7 m 16 8 f 20 9 f 19
=
id sex age 1 m 19 2 m 22 3 NA NA 4 f 19 5 f 18 id sex age 6 m 19 7 m 16 8 f 20 9 f 19