根据r中列的值添加遗漏值 [英] add missed value based on the value of the column in r
问题描述
vector1 < -
data.frame(
名称=a,
age= 10,
fruit= c(orange,cherry,apple),
count= c (b,b,b,b,b,b,b,b,b,b,b,b,b,b,b,b) =b,
age= 33,
fruit= c(apple,mango),
count= c(1,1),
tag= c(2,2)
)
vector3 < -
data.frame(
name=c,
age= 58,
fruit= c(cherry,apple),
count= c(1,1),
tag= c (1,1)
)
list < - list(vector1,vector2,vector3)
print(list)
这是我的测试:
默认值< c(cherry,
orange,
apple,
mango)
)){
#print(list [[num]])
list [[num]]< - rbind(
list [[num]],
data.frame(
name= list [[num]] $ name,
age= list [[num]] $ age,
fruit= setdiff(default ,list [[num]] $ fruit),#add missed value
count= 0,
tag= 1#未找到解决方案
)
)
print(paste0(--------------,num,--------))
print(list)
}
#print(list)
我试图找到哪个水果在数据框中丢失,果实基于标签的值。例如,在第一个数据框中,有标签1和2.如果标签1的值没有默认水果,例如苹果和香蕉期望格式如下所示:
$ $ $ $ $ $ $ $ $ $ $ $ $ $ $ $ $ $ $ $ $ $ $ ]
名称年龄水果计数标签
1 a 10橙色1 1
2 a 10樱桃1 1
3 a 10苹果1 2
4 a 10芒果0 1
5 a 10苹果0 1
6 a 10芒果0 2
7 a 10橙色0 2
8 a 10樱桃0 2
当我检查循环的过程时,我也发现第一个循环加了芒果3次我不明白为什么它不能一次性添加遗漏的值。总体输出如下:
$ $ $ $ $ $ $ $ $ $ $ [$ 1]]
名称年龄水果计数标签
1 a 10橙色1 1
2 a 10樱桃1 1
3 a 10苹果1 2
4 a 10芒果0 1
5 a 10芒果0 1
6 a 10芒果0 1
[[2]]
名称年龄水果计数标记
1 b 33苹果1 2
2 b 33芒果1 2
3 b 33樱桃0 1
4 b 33橙色0 1
[[3]]
名称年龄水果计数标签
1 c 58樱桃1 1
2 c 58苹果1 1
3 c 58橙色0 1
4 c 58 mango 0 1
有人帮我,提供简单的方法或其他方法?我应该使用sqldf函数来添加0值吗?这是一个简单的方法来解决我的问题?解决方案
解决方案
显示问题的标记'dplyr'rel =tag> dplyr 和 tidyr 。我们可以使用 complete
展开数据框,并将填充值指定为0到 count
。
请注意,我将列表名从 list
更改为 fruit_list
,因为它是在R中使用保留字来命名对象是一种不好的做法。另请注意,当我创建示例数据框时,我设置了 stringsAsFactors = FALSE
,因为我不想创建因子列。最后,我使用 lapply
来代替for循环来遍历列表元素。
library(dplyr)
library(tidyr)
fruit_list2< - lapply fruit_list,function(x){
x2 < - x%>%
complete(name,age,fruit = default,tag = c(1,2),fill = list(count = 0) )%>%
select(name,age,fruit,count,tag)%>%
arrange(tag,fruit)%>%
as.data.frame( )
return(x2)
})
fruit_list2
#[[1]]
#年龄水果计数标签
#1 a 10苹果0 1
#2 a 10樱桃1 1
#3 a 10芒果0 1
#4 a 10橙色1 1
#5 a 10苹果1 2
#6 a 10樱桃0 2
#7 a 10芒果0 2
#8 a 10橙色0 2
#
#[[2]]
#名称年龄水果计数标记
#1 b 33苹果0 1
#2 b 33樱桃0 1
#3 b 33芒果0 1
#4 b 33橙色0 1
#5 b 33苹果1 2
#6 b 33樱桃0 2
#7 b 33芒果1 2
#8 b 33橙色0 2
#
#[[3]]
#年龄水果计数标签
# 1 c 58苹果1 1
#2 c 58樱桃1 1
#3 c 58芒果0 1
#4 c 58橙色0 1
#5 c 58苹果0 2
#6 c 58樱桃0 2
#7 c 58芒果0 2
#8 c 58橙色0 2
DATA
vector1 < -
data.frame(
name=a,
age= 10,
fruit= c(orange,cherry,apple) ,
count= c(1,1,1),
tag= c(1,1,2),
stringsAsFactors = FALSE
)
vector2 < -
data.frame(
name=b,
age= 33,
fruit= c(apple,芒果),
count= c(1,1),
tag= c(2,2),
stringsAsFactors = FALSE
)
vector3 < -
data.frame(
name=c,
age= 58,
fruit= c(cherry,apple),
count= c(1,1),
tag c(1,1),
stringsAsFactors = FALSE
)
fruit_list< - list(vector1,vector2,vector3)
default< - c(cherry,orange,apple,mango)
This is my sample dataset:
vector1 <-
data.frame(
"name" = "a",
"age" = 10,
"fruit" = c("orange", "cherry", "apple"),
"count" = c(1, 1, 1),
"tag" = c(1, 1, 2)
)
vector2 <-
data.frame(
"name" = "b",
"age" = 33,
"fruit" = c("apple", "mango"),
"count" = c(1, 1),
"tag" = c(2, 2)
)
vector3 <-
data.frame(
"name" = "c",
"age" = 58,
"fruit" = c("cherry", "apple"),
"count" = c(1, 1),
"tag" = c(1, 1)
)
list <- list(vector1, vector2, vector3)
print(list)
This is my test:
default <- c("cherry",
"orange",
"apple",
"mango")
for (num in 1:length(list)) {
#print(list[[num]])
list[[num]] <- rbind(
list[[num]],
data.frame(
"name" = list[[num]]$name,
"age" = list[[num]]$age,
"fruit" = setdiff(default, list[[num]]$fruit),#add missed value
"count" = 0,
"tag" = 1 #not found solutions
)
)
print(paste0("--------------", num, "--------"))
print(list)
}
#print(list)
I'm trying to find which fruit miss in the data frame and the fruit is based on the value of the tag.For example, in the first data frame, there are tags 1 and 2.If the value of tag 1 does not have the default fruit such as apple and banana, the missed default fruit will be added to 0 to the data frame.The expectation format likes the following:
[[1]]
name age fruit count tag
1 a 10 orange 1 1
2 a 10 cherry 1 1
3 a 10 apple 1 2
4 a 10 mango 0 1
5 a 10 apple 0 1
6 a 10 mango 0 2
7 a 10 orange 0 2
8 a 10 cherry 0 2
When I check the process of the loop, I also find that the first loop adds mango 3 times and I don't find the reason why it cannot add the missed value at one time.The overall output likes the following:
[[1]]
name age fruit count tag
1 a 10 orange 1 1
2 a 10 cherry 1 1
3 a 10 apple 1 2
4 a 10 mango 0 1
5 a 10 mango 0 1
6 a 10 mango 0 1
[[2]]
name age fruit count tag
1 b 33 apple 1 2
2 b 33 mango 1 2
3 b 33 cherry 0 1
4 b 33 orange 0 1
[[3]]
name age fruit count tag
1 c 58 cherry 1 1
2 c 58 apple 1 1
3 c 58 orange 0 1
4 c 58 mango 0 1
Does anyone help me and provides simple methods or other ways? Should I use the sqldf function to add 0 value?Is this a simple way to solve my problems?
A solution using dplyr and tidyr. We can use complete
to expand the data frame and specify the fill values as 0 to count
.
Notice that I changed your list name from list
to fruit_list
because it is a bad practice to use reserved words in R to name an object. Also notice that when I created the example data frame I set stringsAsFactors = FALSE
because I don't want to create factor columns. Finally, I used lapply
instead of for-loop to loop through the list elements.
library(dplyr)
library(tidyr)
fruit_list2 <- lapply(fruit_list, function(x){
x2 <- x %>%
complete(name, age, fruit = default, tag = c(1, 2), fill = list(count = 0)) %>%
select(name, age, fruit, count, tag) %>%
arrange(tag, fruit) %>%
as.data.frame()
return(x2)
})
fruit_list2
# [[1]]
# name age fruit count tag
# 1 a 10 apple 0 1
# 2 a 10 cherry 1 1
# 3 a 10 mango 0 1
# 4 a 10 orange 1 1
# 5 a 10 apple 1 2
# 6 a 10 cherry 0 2
# 7 a 10 mango 0 2
# 8 a 10 orange 0 2
#
# [[2]]
# name age fruit count tag
# 1 b 33 apple 0 1
# 2 b 33 cherry 0 1
# 3 b 33 mango 0 1
# 4 b 33 orange 0 1
# 5 b 33 apple 1 2
# 6 b 33 cherry 0 2
# 7 b 33 mango 1 2
# 8 b 33 orange 0 2
#
# [[3]]
# name age fruit count tag
# 1 c 58 apple 1 1
# 2 c 58 cherry 1 1
# 3 c 58 mango 0 1
# 4 c 58 orange 0 1
# 5 c 58 apple 0 2
# 6 c 58 cherry 0 2
# 7 c 58 mango 0 2
# 8 c 58 orange 0 2
DATA
vector1 <-
data.frame(
"name" = "a",
"age" = 10,
"fruit" = c("orange", "cherry", "apple"),
"count" = c(1, 1, 1),
"tag" = c(1, 1, 2),
stringsAsFactors = FALSE
)
vector2 <-
data.frame(
"name" = "b",
"age" = 33,
"fruit" = c("apple", "mango"),
"count" = c(1, 1),
"tag" = c(2, 2),
stringsAsFactors = FALSE
)
vector3 <-
data.frame(
"name" = "c",
"age" = 58,
"fruit" = c("cherry", "apple"),
"count" = c(1, 1),
"tag" = c(1, 1),
stringsAsFactors = FALSE
)
fruit_list <- list(vector1, vector2, vector3)
default <- c("cherry", "orange", "apple", "mango")
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