使用另一个数据帧按组从数据帧中采样 n 行
Sample n rows from a data frame by group using another data frame
希望根据另一个数据框的条件按组从一个数据框中随机抽取 n 行。
示例：
根据 manufacturer 和 year 分组从 ggplot2::mpg 数据框中随机采样行，其中 n = pick_df 数据的 pick 列帧.
i.e. randomly sample 3 rows from ggplot2::mpg that are hondas made in 2008, 10 volkswagens made in 1999, 2 audis made in 1999, etc.
manufacturer year pick
<chr> <int> <int>
1 honda 2008 3
2 volkswagen 1999 10
3 audi 1999 6
4 land rover 2008 2
5 subaru 1999 6
预期输出：
manufacturer model displ year cyl trans drv cty hwy fl class
<chr> <chr> <dbl> <int> <int> <chr> <chr> <int> <int> <chr> <chr>
1 honda civic 1.8 2008 4 manual(m5) f 26 34 r subcompact
2 honda civic 1.8 2008 4 auto(l5) f 25 36 r subcompact
3 honda civic 1.8 2008 4 auto(l5) f 24 36 c subcompact
4 volkswagen gti 2.8 1999 6 manual(m5) f 17 24 r compact
5 volkswagen passat 2.8 1999 6 manual(m5) f 18 26 p midsize
6 volkswagen new beetle 1.9 1999 4 auto(l4) f 29 41 d subcompact
7 volkswagen new beetle 2 1999 4 auto(l4) f 19 26 r subcompact
8 volkswagen jetta 1.9 1999 4 manual(m5) f 33 44 d compact
9 volkswagen passat 2.8 1999 6 auto(l5) f 16 26 p midsize
10 volkswagen jetta 2.8 1999 6 auto(l4) f 16 23 r compact
11 volkswagen new beetle 2 1999 4 manual(m5) f 21 29 r subcompact
12 volkswagen passat 1.8 1999 4 manual(m5) f 21 29 p midsize
13 volkswagen gti 2 1999 4 auto(l4) f 19 26 r compact
...27 rows total...
Header 从中采样的 mpg 数据帧：
manufacturer model displ year cyl trans drv cty hwy fl class
<chr> <chr> <dbl> <int> <int> <chr> <chr> <int> <int> <chr> <chr>
1 audi a4 1.8 1999 4 auto(l5) f 18 29 p compact
2 audi a4 1.8 1999 4 manual(m5) f 21 29 p compact
3 audi a4 2 2008 4 manual(m6) f 20 31 p compact
4 audi a4 2 2008 4 auto(av) f 21 30 p compact
5 audi a4 2.8 1999 6 auto(l5) f 16 26 p compact
6 audi a4 2.8 1999 6 manual(m5) f 18 26 p compact
7 audi a4 3.1 2008 6 auto(av) f 18 27 p compact
8 audi a4 quattro 1.8 1999 4 manual(m5) 4 18 26 p compact
9 audi a4 quattro 1.8 1999 4 auto(l5) 4 16 25 p compact
10 audi a4 quattro 2 2008 4 manual(m6) 4 20 28 p compact
reprex 的数据来源：
选择数据框的来源pick_df:
structure(list(manufacturer = c("honda", "volkswagen", "audi",
"land rover", "subaru"), year = c(2008L, 1999L, 1999L, 2008L,
1999L), pick = c(3L, 10L, 6L, 2L, 6L)), class = c("tbl_df", "tbl",
"data.frame"), row.names = c(NA, -5L))
mpg 要采样的数据框：
ggplot2::mpg
到目前为止已经试过了
我可以使用过滤器或可能的切片，但编码都是手动的。真实用例有数千行和数百组。
filter(mpg, manufacturer=='honda', year==2008) %>% sample_n(3)
filter(mpg, manufacturer=='volkswagen', year==1999) %>% sample_n(10)
etc...
编辑：
可以循环过滤，但是有点丑：
df <- mpg[0,]
for(i in 1:nrow(pick_df)){
temp <- filter(mpg, manufacturer==pick_df$manufacturer[i], year==pick_df$year[i]) %>% sample_n(pick_df$pick[i])
df <- rbind(temp,df)
}
我们可以用 'pick_df' 做一个 inner_join，按 'manufacturer'、'year' 分组，根据 first 得到 sample_n 'pick'
的值
library(dplyr)
library(ggplot20
mpg %>%
inner_join(pick_df) %>%
group_by(manufacturer, year) %>%
sample_n(first(pick))
# A tibble: 27 x 12
# Groups: manufacturer, year [5]
# manufacturer model displ year cyl trans drv cty hwy fl class pick
# <chr> <chr> <dbl> <int> <int> <chr> <chr> <int> <int> <chr> <chr> <int>
# 1 audi a4 quattro 1.8 1999 4 auto(l5) 4 16 25 p compact 6
# 2 audi a6 quattro 2.8 1999 6 auto(l5) 4 15 24 p midsize 6
# 3 audi a4 2.8 1999 6 auto(l5) f 16 26 p compact 6
# 4 audi a4 quattro 2.8 1999 6 auto(l5) 4 15 25 p compact 6
# 5 audi a4 1.8 1999 4 auto(l5) f 18 29 p compact 6
# 6 audi a4 2.8 1999 6 manual(m5) f 18 26 p compact 6
# 7 honda civic 1.8 2008 4 manual(m5) f 26 34 r subcompact 3
# 8 honda civic 2 2008 4 manual(m6) f 21 29 p subcompact 3
# 9 honda civic 1.8 2008 4 auto(l5) f 24 36 c subcompact 3
#10 land rover range rover 4.2 2008 8 auto(s6) 4 12 18 r suv 2
# … with 17 more rows
希望根据另一个数据框的条件按组从一个数据框中随机抽取 n 行。
示例：
根据 manufacturer 和 year 分组从 ggplot2::mpg 数据框中随机采样行，其中 n = pick_df 数据的 pick 列帧.
i.e. randomly sample 3 rows from
ggplot2::mpgthat are hondas made in 2008, 10 volkswagens made in 1999, 2 audis made in 1999, etc.
manufacturer year pick
<chr> <int> <int>
1 honda 2008 3
2 volkswagen 1999 10
3 audi 1999 6
4 land rover 2008 2
5 subaru 1999 6
预期输出：
manufacturer model displ year cyl trans drv cty hwy fl class
<chr> <chr> <dbl> <int> <int> <chr> <chr> <int> <int> <chr> <chr>
1 honda civic 1.8 2008 4 manual(m5) f 26 34 r subcompact
2 honda civic 1.8 2008 4 auto(l5) f 25 36 r subcompact
3 honda civic 1.8 2008 4 auto(l5) f 24 36 c subcompact
4 volkswagen gti 2.8 1999 6 manual(m5) f 17 24 r compact
5 volkswagen passat 2.8 1999 6 manual(m5) f 18 26 p midsize
6 volkswagen new beetle 1.9 1999 4 auto(l4) f 29 41 d subcompact
7 volkswagen new beetle 2 1999 4 auto(l4) f 19 26 r subcompact
8 volkswagen jetta 1.9 1999 4 manual(m5) f 33 44 d compact
9 volkswagen passat 2.8 1999 6 auto(l5) f 16 26 p midsize
10 volkswagen jetta 2.8 1999 6 auto(l4) f 16 23 r compact
11 volkswagen new beetle 2 1999 4 manual(m5) f 21 29 r subcompact
12 volkswagen passat 1.8 1999 4 manual(m5) f 21 29 p midsize
13 volkswagen gti 2 1999 4 auto(l4) f 19 26 r compact
...27 rows total...
Header 从中采样的 mpg 数据帧：
manufacturer model displ year cyl trans drv cty hwy fl class
<chr> <chr> <dbl> <int> <int> <chr> <chr> <int> <int> <chr> <chr>
1 audi a4 1.8 1999 4 auto(l5) f 18 29 p compact
2 audi a4 1.8 1999 4 manual(m5) f 21 29 p compact
3 audi a4 2 2008 4 manual(m6) f 20 31 p compact
4 audi a4 2 2008 4 auto(av) f 21 30 p compact
5 audi a4 2.8 1999 6 auto(l5) f 16 26 p compact
6 audi a4 2.8 1999 6 manual(m5) f 18 26 p compact
7 audi a4 3.1 2008 6 auto(av) f 18 27 p compact
8 audi a4 quattro 1.8 1999 4 manual(m5) 4 18 26 p compact
9 audi a4 quattro 1.8 1999 4 auto(l5) 4 16 25 p compact
10 audi a4 quattro 2 2008 4 manual(m6) 4 20 28 p compact
reprex 的数据来源：
选择数据框的来源pick_df:
structure(list(manufacturer = c("honda", "volkswagen", "audi",
"land rover", "subaru"), year = c(2008L, 1999L, 1999L, 2008L,
1999L), pick = c(3L, 10L, 6L, 2L, 6L)), class = c("tbl_df", "tbl",
"data.frame"), row.names = c(NA, -5L))
mpg 要采样的数据框：
ggplot2::mpg
到目前为止已经试过了
我可以使用过滤器或可能的切片，但编码都是手动的。真实用例有数千行和数百组。
filter(mpg, manufacturer=='honda', year==2008) %>% sample_n(3)
filter(mpg, manufacturer=='volkswagen', year==1999) %>% sample_n(10)
etc...
编辑： 可以循环过滤，但是有点丑：
df <- mpg[0,]
for(i in 1:nrow(pick_df)){
temp <- filter(mpg, manufacturer==pick_df$manufacturer[i], year==pick_df$year[i]) %>% sample_n(pick_df$pick[i])
df <- rbind(temp,df)
}
我们可以用 'pick_df' 做一个 inner_join，按 'manufacturer'、'year' 分组，根据 first 得到 sample_n 'pick'
library(dplyr)
library(ggplot20
mpg %>%
inner_join(pick_df) %>%
group_by(manufacturer, year) %>%
sample_n(first(pick))
# A tibble: 27 x 12
# Groups: manufacturer, year [5]
# manufacturer model displ year cyl trans drv cty hwy fl class pick
# <chr> <chr> <dbl> <int> <int> <chr> <chr> <int> <int> <chr> <chr> <int>
# 1 audi a4 quattro 1.8 1999 4 auto(l5) 4 16 25 p compact 6
# 2 audi a6 quattro 2.8 1999 6 auto(l5) 4 15 24 p midsize 6
# 3 audi a4 2.8 1999 6 auto(l5) f 16 26 p compact 6
# 4 audi a4 quattro 2.8 1999 6 auto(l5) 4 15 25 p compact 6
# 5 audi a4 1.8 1999 4 auto(l5) f 18 29 p compact 6
# 6 audi a4 2.8 1999 6 manual(m5) f 18 26 p compact 6
# 7 honda civic 1.8 2008 4 manual(m5) f 26 34 r subcompact 3
# 8 honda civic 2 2008 4 manual(m6) f 21 29 p subcompact 3
# 9 honda civic 1.8 2008 4 auto(l5) f 24 36 c subcompact 3
#10 land rover range rover 4.2 2008 8 auto(s6) 4 12 18 r suv 2
# … with 17 more rows