组数据由R中

Question

图案框架我有数百个行的R数据帧作为

word  Freq 
seed   4 
seeds  3 
contract  2 
contracting 2 
river  1 

我想组由图案数据，表示种子+种籽，看起来像

word  Freq 
seed  7 
contract 4 
river  1 

Answer 1

一种选择是通过基于'word'中最小字符数提取子字符串来创建一个分组变量'gr'，用'word'sp来做这一个，我们可以得到每个组的子字符串单词，然后通过'单词'获得'Freq'的sum。

library(dplyr) 
df1 %>% 
    group_by(gr= substr(word, 1, min(nchar(word)))) %>% 
    group_by(word= substr(word, 1, min(nchar(word)))) %>% 
    summarise(Freq= sum(Freq)) 
    word Freq 
#  (chr) (int) 
#1 contract  4 
#2 river  1 
#3  seed  7 

Answer 2

也可以用交叉连接，这比上面的方法有点安全。

library(dplyr) 
library(stringi) 

df %>% 
    merge(df %>% select(short_word = word)) %>% 
    filter(short_word %>% 
      stri_detect_regex(word, .)) %>% 
    group_by(word) %>% 
    slice(short_word %>% stri_length %>% which.min) %>% 
    group_by(short_word) %>% 
    summarise(Freq= sum(Freq)) 

Answer 3

这可能是另一种方法。在SnowballC包中，有一个功能可以清理单词并获得单词干（即wordStem()）。使用它，你可以跳过字符串操作，我想。一旦你完成了这个过程，你所做的就是获得词频的总和。

library(SnowballC) 
library(dplyr) 

mydf <- read.table(text = "word  Freq 
seed   4 
seeds  3 
contract  2 
contracting 2 
river  1", header = T) 

mutate(mydf, word = wordStem(word)) %>% 
group_by(word) %>% 
summarise(total = sum(Freq)) 

#  word total 
#  (chr) (int) 
#1 contract  4 
#2 river  1 
#3  seed  7 

Answer 4

尝试使用adist来匹配条件up。

dat$grp <- seq(nrow(dat)) 

# generate a matrix comparing the vector of words to themselves 
tmp <- adist(dat$word, dat$word, partial=TRUE) 
diag(tmp) <- Inf 
dat$grp[col(tmp)[tmp==0]] <- row(tmp)[tmp==0] 

final <- aggregate(Freq ~ grp, data=dat, sum) 
final$word <- dat$word[match(final$grp, dat$grp)] 

# grp Freq  word 
#1 1 7  seed 
#2 3 4 contract 
#3 5 1 river 

使用的数据：

dat <- data.frame(word=c("seed","seeds","contract","contracting","river"),Freq=c(4,3,2,2,1))