我有多个数据框,如下所示: 列中有许多物种,我在这里没有报道。 D1:
Year Region Sites Depth Transect Pharia pyramidatus
2000 LP BALLENA 5 1 0.03
2000 LP ISLOTES 5 1 0.20
2000 LP NORTE 5 1 0.10
2000 LP NORTE 20 1 0.00
D2
Year Region Sites Depth Transect Pharia pyramidatus
2010 LP PLAYA 5 1 0.03
2010 LP ISLOTES 5 1 0.20
2010 LP NORTE 5 1 0.10
2010 LP NORTE 20 1 0.00
D3
Year Region Sites Depth Transect Pharia pyramidatus
2016 LP BALLENA 5 1 0.03
2016 LP ISLOTES 5 1 0.20
2016 LP SUR 5 1 0.10
2016 LP NORTE 20 1 0.00
我想要做的是提取仅在每个年中出现的同一网站(Reef
),并将结果转换为一个应如下所示的数据框:
Year Region Reef Depth Transect Pharia pyramidatus
2000 LP ISLOTES 5 1 0.20
2000 LP NORTE 5 1 0.10
2000 LP NORTE 20 1 0.00
2010 LP ISLOTES 5 1 0.20
2010 LP NORTE 5 1 0.10
2010 LP NORTE 20 1 0.00
2016 LP ISLOTES 5 1 0.20
2016 LP NORTE 20 1 0.00
非常感谢你的帮助
答案 0 :(得分:1)
dplyr
的解决方案:
library(dplyr)
rbind(df1, df2, df3) %>%
group_by(Reef) %>%
filter(n_distinct(Year) == 3)
<强>结果:强>
# A tibble: 8 x 6
# Groups: Reef [2]
Year Region Reef Depth Transect Pharia_pyramidatus
<int> <fctr> <fctr> <int> <int> <dbl>
1 2000 LP ISLOTES 5 1 0.2
2 2000 LP NORTE 5 1 0.1
3 2000 LP NORTE 20 1 0.0
4 2010 LP ISLOTES 5 1 0.2
5 2010 LP NORTE 5 1 0.1
6 2010 LP NORTE 20 1 0.0
7 2016 LP ISLOTES 5 1 0.2
8 2016 LP NORTE 20 1 0.0
备注:强>
n_distinct
计算每个Year
的不同Reef
的数量(因为我group_by(Reef)
)。我想要distinct_n == 3
,因为我只希望返回Reef
每个Year
都有记录的行,在这种情况下为3年。在更一般的情况下,如果还有更多Year
,您可能需要先查找数据框的Year
范围,然后根据该范围查找filter
,例如以下内容:
rbind(df1, df2, df3) %>%
mutate(Year_distinct = n_distinct(Year)) %>%
group_by(Reef) %>%
filter(n_distinct(Year) == Year_distinct) %>%
select(-Year_distinct)
数据:强>
df1 = read.table(text = "Year Region Reef Depth Transect Pharia_pyramidatus
2000 LP BALLENA 5 1 0.03
2000 LP ISLOTES 5 1 0.20
2000 LP NORTE 5 1 0.10
2000 LP NORTE 20 1 0.00", header = TRUE)
df2 = read.table(text = "Year Region Reef Depth Transect Pharia_pyramidatus
2010 LP PLAYA 5 1 0.03
2010 LP ISLOTES 5 1 0.20
2010 LP NORTE 5 1 0.10
2010 LP NORTE 20 1 0.00", header = TRUE)
df3 = read.table(text = "Year Region Reef Depth Transect Pharia_pyramidatus
2016 LP BALLENA 5 1 0.03
2016 LP ISLOTES 5 1 0.20
2016 LP SUR 5 1 0.10
2016 LP NORTE 20 1 0.00", header = TRUE)