Question

我正在处理尺寸为</ p>的集合

dim(data)
[1] 419612      2

第二栏看起来或多或少像这样：

> unique(data[1:50,"topics"])
[1] {"dom":2.0,"moda":3.0,"rodzina":1.55,"praca":1.42,"finanse":1.96,"edukacja":1.67,"sport":1.96,"muzyka":1.52,"kuchnia":1.8,"plotka":1.8,"zdrowie":1.12,"kibic":1.8,"uroda":2.32,"gra":2.94,"motoryzacja":1.33,"kultura":1.42,"film":3.14,"podróż":1.9,"technologia":1.31}
[2] {"rodzina":2.99,"kultura":4.46,"muzyka":4.5}                                                                                                                                                                                                                            
[3] {"dom":1.93,"rodzina":5.37,"zwierzęta":3.0,"praca":4.3,"finanse":2.11,"sport":2.1,"muzyka":2.99,"nieruchomość":2.8,"kuchnia":6.4,"plotka":2.1,"zdrowie":3.79,"gra":4.25,"motoryzacja":2.57,"kultura":3.13,"film":4.4,"podróż":3.21}                                     
[4] {"plotka":9.5,"uroda":10.06,"kultura":15.67,"muzyka":29.97}                                                                                                                                                                                                             
[5] {"dom":2.99,"rodzina":2.5,"edukacja":3.85,"sport":1.17,"muzyka":1.23,"nieruchomość":2.95,"kuchnia":1.42,"wnętrze":1.33,"kibic":1.17,"ogród":1.33,"motoryzacja":1.17,"film":1.17,"podróż":1.57}                                                                          
[6] {"kuchnia":4.38,"plotka":1.33,"rodzina":1.61,"film":1.33}                                                                                                                                                                                                               
37530 Levels: {"biznes":1.0} ... {"zwierzęta":9.96,"podróż":9.97}

对于每一行，我想从topics列中选择:符号后等级最高的单词。我尝试使用dplyr包中的mutate函数，看起来它不起作用。使用stringi包制作的字符的操作，这些包是stringr的更快版本。我的代码和此操作的结果如下。任何人都知道为什么我在这个操作后的每一行都得到相同的值，以及如何在不使用for循环的情况下获得所需的结果？

> data2 <- data %>%
+   mutate( xx = topics %>%
+             stri_extract_all_regex(pattern = "[a-zA-Z0-9óśćłźżęą\\.\\s]+") %>% 
+             unlist %>% 
+             data.frame( topic = .[seq(1,length(.), by=2)], 
+                         waga = .[seq(2,length(.), by=2)] )  %>% 
+             select( topic, waga) %>% arrange( desc( waga)) %>%
+             unique() %>%
+             .[1,1]
+             )
> table(data2$xx)[ which(table(data2$xx) > 1) ]
kuchnia 
 419612

我添加了一个行号nr，这是一个行号，然后我对该列进行了愚蠢的group_by和summarise d而不是mutate和得到了我想要的......但我并不为我的代码感到骄傲。还有其他想法吗？

daneBC1 <- data %>% 
  group_by( nr)  %>%
  summarise( bc1 = topics %>%
               stri_extract_all_regex(pattern = "[a-zA-Z0-9óśćłźżęą\\.\\s]+") %>% 
               unlist %>% 
               data.frame( topic = .[seq(1,length(.), by=2)], 
                           waga = .[seq(2,length(.), by=2)] )  %>% 
               select( topic, waga) %>% arrange( desc( waga)) %>%
               unique() %>%
               .[1,1] )



daneBC1$bc1 %>% table

        dom    edukacja        film     finanse         gra       kibic     kuchnia     kultura 
     119802       79487       55569       38134       30425       21757       16371       12356 
       moda motoryzacja      muzyka      plotka      podróż       praca     rodzina       sport 
      11103        7264        6357        4855        3520        3005        2317        2183 
technologia       uroda     zdrowie 
       1441        1055         740

示例数据

library(archivist)
data <- loadFromGithubRepo( "97f74c5a10f510cce39eafb0d9a1a9e8", 
user="MarcinKosinski", repo="Museum", value = TRUE )

Answer 1

您的mutate()功能未被＆＃34;矢量化＆＃34;。 Mutate一次不对一行进行操作，它作为向量在整个列上运行。您的unlist和.[1,1]提取正在获取所有行的值，并向下折叠为一个向量和一个值。

您可以使用

创建矢量化转换函数

extr <- Vectorize(. %>%
         stri_extract_all_regex(pattern = "[a-zA-Z0-9óśćłźżęą\\.\\s]+") %>% 
         unlist %>% 
         data.frame( topic = .[seq(1,length(.), by=2)], 
                     waga = .[seq(2,length(.), by=2)] )  %>% 
         select( topic, waga) %>% arrange( desc( waga)) %>%
         unique() %>%
         .[1,1])

然后将其与

一起使用

data %>% mutate( xx = extr(topics))

虽然我同意其他人的意见，因为你有JSON数据，最好用JSON解析器正确解析这些数据，而不是试图用正则表达式重新发明轮子。

R中dplyr包中mutate函数的奇怪行为

1 个答案: