[英]r collapsing data from multiple columns into one
我知道关于这个主题有很多问题,所以如果这是一个重复的问题我会道歉。 我正在尝试将数据集中的多个列折叠为一列:
假设这是我正在使用的数据集的结构,
df <- data.frame(
cbind(
variable_1 = c('Var1', NA, NA,'Var1'),
variable_2 = c('Var2', 'No', NA, NA),
variable_3 = c(NA, NA, 'Var3', NA),
variable_4 = c(NA, 'Var4', NA, NA),
variable_5 = c(NA, 'No', 'Var5', NA),
variable_6 = c(NA, NA, 'Var6', NA)
))
variable_1 variable_2 variable_3 variable_4 variable_5 variable_6
Var1 Var2 NA NA NA NA
NA No NA Var4 No NA
NA NA Var3 NA Var5 Var6
Var1 NA NA NA NA NA
我期待的是像这样的一列variable_7
variable_1 variable_2 variable_3 variable_4 variable_5 variable_6 variable_7
Var1 Var2 NA NA NA NA Var1, Var2
NA No NA Var4 No NA Var4
NA NA Var3 NA Var5 Var6 Var3, Var5, Var6
Var1 NA NA NA NA NA Var1
任何帮助实现这一点非常感谢。
df$variable_7 <- apply(df, 1, function(x) paste(x[!is.na(x) & x != "No"], collapse = ", "));
df;
# variable_1 variable_2 variable_3 variable_4 variable_5 variable_6
#1 Var1 Var2 <NA> <NA> <NA> <NA>
#2 <NA> No <NA> Var4 No <NA>
#3 <NA> <NA> Var3 <NA> Var5 Var6
#4 Var1 <NA> <NA> <NA> <NA> <NA>
# variable_7
#1 Var1, Var2
#2 Var4
#3 Var3, Var5, Var6
#4 Var1
说明:使用apply
和paste(..., collapse = ", ")
连接所有行条目( NA
和"No"
除外)并存储在新列variable_7
。
df <- data.frame(
cbind(
variable_1 = c('Var1', NA, NA,'Var1'),
variable_2 = c('Var2', 'No', NA, NA),
variable_3 = c(NA, NA, 'Var3', NA),
variable_4 = c(NA, 'Var4', NA, NA),
variable_5 = c(NA, 'No', 'Var5', NA),
variable_6 = c(NA, NA, 'Var6', NA)
))
我想,如果有n行,那么objective就是在每行中创建一个包含字符Var
的逗号分隔字符串的n向量。 (如果您打算使用其他标准来分隔所需和不需要的值,则相应地更改grep
。)
apply(df, 1, function(x) toString(grep("Var", x, value = TRUE)))
## [1] "Var1, Var2" "Var4" "Var3, Var5, Var6" "Var1"
使用data.table
'重新data.table
'方法而不是循环/应用
library(data.table)
setDT(df)
df[, id := .I][
melt(df, id.vars = "id")[grepl("Var", value), .(variable_7 = paste0(value, collapse = ",")), by = .(id)]
, on = "id"
, nomatch = 0
][order(id)]
# variable_1 variable_2 variable_3 variable_4 variable_5 variable_6 id variable_7
# 1: Var1 Var2 NA NA NA NA 1 Var1,Var2
# 2: NA No NA Var4 No NA 2 Var4
# 3: NA NA Var3 NA Var5 Var6 3 Var3,Var5,Var6
# 4: Var1 NA NA NA NA NA 4 Var1
使用dplyr
的解决方案。 df4
是最终输出。 请看我是如何创建数据框df
。 cbind
不是必需的,添加stringsAsFactors = FALSE
以防止创建因子列会很棒。
library(dplyr)
library(tidyr)
df2 <- df %>% mutate(ID = 1:n())
df3 <- df2 %>%
gather(Variable, Value, -ID, na.rm = TRUE) %>%
filter(!Value %in% "No") %>%
group_by(ID) %>%
summarise(variable_7 = toString(Value))
df4 <- df2 %>%
left_join(df3, by = "ID") %>%
select(-ID)
df4
# variable_1 variable_2 variable_3 variable_4 variable_5 variable_6 variable_7
# 1 Var1 Var2 <NA> <NA> <NA> <NA> Var1, Var2
# 2 <NA> No <NA> Var4 No <NA> Var4
# 3 <NA> <NA> Var3 <NA> Var5 Var6 Var3, Var5, Var6
# 4 Var1 <NA> <NA> <NA> <NA> <NA> Var1
数据
df <- data.frame(
variable_1 = c('Var1', NA, NA,'Var1'),
variable_2 = c('Var2', 'No', NA, NA),
variable_3 = c(NA, NA, 'Var3', NA),
variable_4 = c(NA, 'Var4', NA, NA),
variable_5 = c(NA, 'No', 'Var5', NA),
variable_6 = c(NA, NA, 'Var6', NA),
stringsAsFactors = FALSE
)
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