r-如何在单个数据帧列中记录大字符串的拆分元素的存在/不存在

Question

我有一个数据框架，里面有一串又长又乱的家用设施。我想把字符串分解成独特的便利设施，在数据帧中为每个独特的便利条件创建一个新列，并在新列中记录字符串中单个便利设施的存在/不存在。使用嵌套的for循环，我找到了一种完成任务的方法。然而，我想知道的是，如何使用apply函数族或dplyr方法来避免循环，从而获得相同的结果。

可再现数据：

df <- data.frame(
id = 1:4,
amenities = c('{"Wireless Internet","Wheelchair accessible",Kitchen,Elevator,"Buzzer/wireless intercom",Heating}',
'{TV,"Cable TV",Internet,"Wireless Internet","Air conditioning",Kitchen,"Smoking allowed","Pets allowed"}',
'{"Buzzer/wireless intercom",Heating,"Family/kid friendly","Smoke detector",Carbon monoxide}',
'{Washer,Dryer,Essentials,Shampoo,Hangers,"Laptop friendly workspace"}'))

到目前为止，我所做的是：

amenities_clean <- gsub('[{}"]', '', df$amenities) # remove unwanted stuff 
amenities_split <- strsplit(amenities_clean, ",") # split rows into individual amenities
amenities_unique <- unique(unlist(strsplit(amenities_clean, ","))) # get a list of unique amenities 
df[amenities_unique] <- NA # set up the columns for each amenity

为了在新的列中记录字符串中是否存在单独的便利设施，我使用了str_detect和嵌套的for循环：

# record presence/absence of individual amenities in each new column:
library(stringr)
for(i in 1:ncol(df[amenities_unique])){
for(j in 1:nrow(df)){
df[amenities_unique][j,i] <- 
ifelse(str_detect(amenities_split[j], names(df[amenities_unique][i])), 1, 0)
}
}

虽然这会产生警告，但它们似乎无害，因为结果看起来不错：

df
id                                                                                                amenities Wireless Internet
1  1        {"Wireless Internet","Wheelchair accessible",Kitchen,Elevator,"Buzzer/wireless intercom",Heating}                 1
2  2 {TV,"Cable TV",Internet,"Wireless Internet","Air conditioning",Kitchen,"Smoking allowed","Pets allowed"}                 1
3  3              {"Buzzer/wireless intercom",Heating,"Family/kid friendly","Smoke detector",Carbon monoxide}                 0
4  4                                    {Washer,Dryer,Essentials,Shampoo,Hangers,"Laptop friendly workspace"}                 0
Wheelchair accessible Kitchen Elevator Buzzer/wireless intercom Heating TV Cable TV Internet Air conditioning Smoking allowed
1                     1       1        1                        1       1  0        0        1                0               0
2                     0       1        0                        0       0  1        1        1                1               1
3                     0       0        0                        1       1  0        0        0                0               0
4                     0       0        0                        0       0  0        0        0                0               0
Pets allowed Family/kid friendly Smoke detector Carbon monoxide Washer Dryer Essentials Shampoo Hangers Laptop friendly workspace
1            0                   0              0               0      0     0          0       0       0                         0
2            1                   0              0               0      0     0          0       0       0                         0
3            0                   1              1               1      0     0          0       0       0                         0
4            0                   0              0               0      1     1          1       1       1                         1

考虑到警告和嵌套循环的复杂性，如何使用apply函数族中的函数或使用dplyr来获得相同的结果？

Answer 1

清洁设施后，即可使用splitstackshape中的cSplit_e。

df$amenities_clean <- gsub('[{}"]', '', df$amenities) 
splitstackshape::cSplit_e(df, "amenities_clean", type = "character", fill = 0)

---

使用我们可以做的应用函数之一来解决它：

temp <- strsplit(df$amenities_clean, ",")
amenities_unique <- unique(unlist(temp))
cbind(df, t(sapply(temp, function(x) 
table(factor(x, levels = amenities_unique)))))

Answer 2

我相信这会提供您需要的输出：

library(tidyverse)
df %>%
mutate(amenities = str_replace_all(amenities, '["{}]', '')) %>% 
separate_rows(amenities, sep = ",") %>% 
pivot_wider(names_from = amenities, values_from = amenities, values_fn = list(amenities = is.character)) %>% 
mutate_all(replace_na, 0) 

结果是：

# A tibble: 4 x 22
id `Wireless Inter~ `Wheelchair acc~ Kitchen Elevator `Buzzer/wireles~ Heating    TV `Cable TV` Internet `Air conditioni~ `Smoking allowe~
<dbl>            <dbl>            <dbl>   <dbl>    <dbl>            <dbl>   <dbl> <dbl>      <dbl>    <dbl>            <dbl>            <dbl>
1     1                1                1       1        1                1       1     0          0        0                0                0
2     2                1                0       1        0                0       0     1          1        1                1                1
3     3                0                0       0        0                1       1     0          0        0                0                0
4     4                0                0       0        0                0       0     0          0        0                0                0
# ... with 10 more variables: `Pets allowed` <dbl>, `Family/kid friendly` <dbl>, `Smoke detector` <dbl>, `Carbon monoxide` <dbl>, Washer <dbl>,
#   Dryer <dbl>, Essentials <dbl>, Shampoo <dbl>, Hangers <dbl>, `Laptop friendly workspace` <dbl>