我有data.frame
,我需要从中提取样本。每年我都需要根据人口权重进行50次观察。以下是一些示例代码:
library(dplyr)
set.seed(1234)
ex.df <- data.frame(value=runif(1000),
year = rep(1991:2010, each=50),
group= sample(c("A", "B", "C"), 1000, replace=T)) %>%
mutate(pop.weight = ifelse(group=="A", 0.5,
ifelse(group=="B", 0.3,
ifelse(group=="C", 0.2, group))))
set.seed(1234)
test <- ex.df %>%
group_by(year) %>%
sample_n(50, weight=pop.weight) %>%
ungroup()
table(test$group)/sum(table(test$group))
A B C
0.329 0.319 0.352
小组A
应代表约50%,小组B
代表30%,C
代表大约20%。我错过了什么?
答案 0 :(得分:1)
设置replace = TRUE
。您希望每年进行50次观察,但ex.df
每年仅包含50次观察,如果replace = FALSE
它只返回不同顺序的相同行。
set.seed(1234)
test <- ex.df %>%
group_by(year) %>%
sample_n(50, weight=pop.weight, replace = TRUE) %>%
ungroup()
table(test$group)/sum(table(test$group))
# A B C
# 0.509 0.299 0.192
或者您可以在ex.df
中增加每年的观察数。在下面的示例中,我将每年的观察值更改为5000,结果test
中的比率看起来合理。
set.seed(1234)
ex.df <- data.frame(value=runif(100000),
year = rep(1991:2010, each=5000),
group= sample(c("A", "B", "C"), 1000, replace=T)) %>%
mutate(pop.weight = ifelse(group=="A", 0.5,
ifelse(group=="B", 0.3,
ifelse(group=="C", 0.2, group))))
set.seed(1234)
test <- ex.df %>%
group_by(year) %>%
sample_n(50, weight=pop.weight) %>%
ungroup()
table(test$group)/sum(table(test$group))
# A B C
# 0.515 0.276 0.209