r语言 - 如果两列之间的组合在组配对中至少有一个"Y"值，则在新列中创建标志值？

Question

假设我有一个看起来像这样的数据集

ID| Street   | street type| Crime|
1  Main       ST            N
2  Main       ST            Y
3  Pleasant   AVE           Y
4  Pleasant   AVE           Y
5  Harris     BLVD          N
6  Lincoln    Road          Y
7  Lincoln    Road          Y
8  Lincoln    Road          Y
9  Breezy     Ave           Y 
10  Breezy     Ave           N
11  Rose       ST            N    
12  Rose       ST            N    
13  Rose       ST            N    

我想要这样的东西注意在列"Street"之间建立一个组和";Crime"。如果至少有一个&;y &;出现在"犯罪"中;为同一组的所有部分分配一个Y。

ID| Street   | street type| Crime|Flag
1  Main       ST            N    Y
2  Main       ST            Y    Y
3  Pleasant   AVE           Y    Y
4  Pleasant   AVE           Y    Y
5  Harris     BLVD          N    N
6  Lincoln    Road          Y    Y
7  Lincoln    Road          Y    Y
8  Lincoln    Road          Y    Y
9  Breezy     Ave           Y    Y
10  Breezy     Ave           N    Y
11  Rose       ST            N    N
12  Rose       ST            N    N
13  Rose       ST            N    N

Answer 1

tryany

df %>%
group_by(Street) %>%
mutate(Flag = as.character(any(Crime == "Y"))) %>%
mutate(Flag = recode(Flag, "TRUE" = "Y", "FALSE" = "N"))
Street   Crime Flag 
<chr>    <chr> <chr>
1 Main     N     Y    
2 Main     Y     Y    
3 Pleasant Y     Y    
4 Pleasant Y     Y    
5 Harris   N     N 

Answer 2

library(dplyr)
df %>% 
group_by(Street) %>% 
mutate(Crime = if_else(any(Crime == "Y"),"Y","N"))
# A tibble: 13 x 4
# Groups:   Street [6]
ID Street   street_type Crime
<int> <chr>    <chr>       <chr>
1     1 Main     ST          Y    
2     2 Main     ST          Y    
3     3 Pleasant AVE         Y    
4     4 Pleasant AVE         Y    
5     5 Harris   BLVD        N    
6     6 Lincoln  Road        Y    
7     7 Lincoln  Road        Y    
8     8 Lincoln  Road        Y    
9     9 Breezy   Ave         Y    
10    10 Breezy   Ave         Y    
11    11 Rose     ST          N    
12    12 Rose     ST          N    
13    13 Rose     ST          N 

——数据

structure(list(ID = 1:13, Street = c("Main", "Main", "Pleasant", 
"Pleasant", "Harris", "Lincoln", "Lincoln", "Lincoln", "Breezy", 
"Breezy", "Rose", "Rose", "Rose"), street_type = c("ST", "ST", 
"AVE", "AVE", "BLVD", "Road", "Road", "Road", "Ave", "Ave", "ST", 
"ST", "ST"), Crime = c("N", "Y", "Y", "Y", "N", "Y", "Y", "Y", 
"Y", "N", "N", "N", "N")), class = "data.frame", row.names = c(NA, 
-13L))

Answer 3

或者使用max，因为Y大于N:

df %>%
group_by(Street) %>%
mutate(Flag = max(Crime))

这是这里最短的一个，并保持你原来的数据结构:

ID Street   street_type Crime Flag 
<int> <chr>    <chr>       <chr> <chr>
1     1 Main     ST          N     Y    
2     2 Main     ST          Y     Y    
3     3 Pleasant AVE         Y     Y    
4     4 Pleasant AVE         Y     Y    
5     5 Harris   BLVD        N     N    
6     6 Lincoln  Road        Y     Y    
7     7 Lincoln  Road        Y     Y    
8     8 Lincoln  Road        Y     Y    
9     9 Breezy   Ave         Y     Y    
10    10 Breezy   Ave         N     Y    
11    11 Rose     ST          N     N    
12    12 Rose     ST          N     N    
13    13 Rose     ST          N     N   

Answer 4

这是一个基本R选项-

df$Flag <- 'N'
df$Flag[df$Street %in% unique(df$Street[df$Crime == 'Y'])] <- 'Y'
df
#   ID   Street street_type Crime Flag
#1   1     Main          ST     N    Y
#2   2     Main          ST     Y    Y
#3   3 Pleasant         AVE     Y    Y
#4   4 Pleasant         AVE     Y    Y
#5   5   Harris        BLVD     N    N
#6   6  Lincoln        Road     Y    Y
#7   7  Lincoln        Road     Y    Y
#8   8  Lincoln        Road     Y    Y
#9   9   Breezy         Ave     Y    Y
#10 10   Breezy         Ave     N    Y
#11 11     Rose          ST     N    N
#12 12     Rose          ST     N    N
#13 13     Rose          ST     N    N

初始化Flag列为'N'。将Flag列更改为'Y',Street的值与'Y'的值相同。

Answer 5

在base R中使用transform

transform(df1, Flag = c("N", "Y")[1 + Street %in% Street[Crime == "Y"]])
ID   Street street_type Crime Flag
1   1     Main          ST     N    Y
2   2     Main          ST     Y    Y
3   3 Pleasant         AVE     Y    Y
4   4 Pleasant         AVE     Y    Y
5   5   Harris        BLVD     N    N
6   6  Lincoln        Road     Y    Y
7   7  Lincoln        Road     Y    Y
8   8  Lincoln        Road     Y    Y
9   9   Breezy         Ave     Y    Y
10 10   Breezy         Ave     N    Y
11 11     Rose          ST     N    N
12 12     Rose          ST     N    N
13 13     Rose          ST     N    N