问题描述
R编码的新手，我一直在尝试使用dplyr的group_by格式化/合并df中的行.但是，我还没到那里.
very new to R coding and I've been trying to format/merge rows in a df using group_by from dplyr. However, I'm not quite there yet.
这是我的数据表的简化.前三个条目共享相同的ID，后两个条目共享相同的ID.
This is a simplification of my data table. The first three entries share the same id, and the last two entries share the same id.
ID Assay1 Assay2 Assay3 Assay4 Assay5
13,12 Months,<=-65C 12 NA NA NA NA
13,12 Months,<=-65C NA 11 NA NA NA
13,12 Months,<=-65C NA NA 33 NA NA
09,06 Months,<=-65C 112 NA NA NA NA
09,06 Months,<=-65C NA 115 NA NA NA
我想实现以下目标:
ID Assay1 Assay2 Assay3 Assay4 Assay5
13,12 Months,<=-65C 12 11 33 NA NA
09,06 Months,<=-65C 112 115 NA NA NA
以便将AssayValueX中的值合并到每个唯一ID的一行中.我已经将group_by与summary一起使用，但是我不希望有Summary ...我想要一个包含合并行的新df！如果其他功能更适合实现此目的，请告诉我.
So that the values in AssayValueX are merged into one row per unique id. I've used group_by with summarise but I dont want a summary... I want a new df with the merged rows! If other functions are more appropriate to achieve this, please let me know.
推荐答案
您可以使用dplyr和zoo
df %>%
group_by(ID) %>%
mutate_each(funs(na.locf(., na.rm = FALSE, fromLast = FALSE)))%>%filter(row_number()==n())
ID Assay1 Assay2 Assay3 Assay4 Assay5
13,12 Months,<=-65C 12 11 33 NA NA
09,06 Months,<=-65C 112 115 NA NA NA
编辑
关于您的其他问题
数据:
ID Assay1 Assay2 Assay3 Assay4 Assay5
1 13,12 Months,<=-65C 12 13 NA NA NA
2 13,12 Months,<=-65C 11 11 999 NA NA
3 13,12 Months,<=-65C NA NA 33 NA NA
4 09,06 Months,<=-65C 112 NA NA NA NA
5 09,06 Months,<=-65C NA 115 NA NA NA
解决方案
df=df %>%
group_by(ID) %>%
summarise_all(funs(toString(na.omit(.))))
df[df=='']=NA
> df
ID Assay1 Assay2 Assay3 Assay4 Assay5
<chr> <chr> <chr> <chr> <chr> <chr>
1 09,06 Months,<=-65C 112 115 <NA> <NA> <NA>
2 13,12 Months,<=-65C 12, 11 13, 11 999, 33 <NA> <NA>
这篇关于合并行，并用group_by和填充空白位置?的文章就介绍到这了，希望我们推荐的答案对大家有所帮助，也希望大家多多支持！