英文:
changing the output of text_tokens function in R
问题
关于使用corpus包和text_tokens()函数进行文本挖掘的问题。我想使用该函数进行词干处理和停用词删除。我有大量数据（近100万条评论）需要处理。但是我在处理text_tokens函数输出时遇到了问题。以下是我的数据和代码的基本示例：
library(tidyverse)library(corpus)library(stopwords)text <- data.frame(comment_id = 1:2,comment_content = c("Hallo mein Name ist aaron","Vielen Lieben Dank für das Video"))tmp <- text_tokens(text$comment_content,text_filter(stemmer = "de", drop = stopwords("german")))
我的问题是，我希望输出是一个data.frame，其中第一列是comment_id，第二列是word_token。我想要的输出应该如下所示：
df <- data.frame(comment_id = c(1,1,1,2,2,2),comment_tokens = c("hallo","nam","aaron","lieb","dank","video"))
我尝试了不同的do.calls（cbind/rbind），但它们没有给我想要的结果。那么我要找的是什么函数呢？是不是tidyverse中的map()函数？
提前感谢。
致敬，
Aaron
英文:
I have a question redarding text mining with the corpus package and the function text_tokens(). I want to use the function for stemming and deleting stop words. I have a huge amount of data (almost 1.000.000 comments) where I want to use it for. But I've problems with the output, the function text_tokens produces. So here is a basic example of my data and code:
library(tidyverse)library(corpus)library(stopwords)text <- data.frame(comment_id = 1:2,comment_content = c("Hallo mein Name ist aaron","Vielen Lieben Dank für das Video"))tmp <- text_tokens(text$comment_content,text_filter(stemmer = "de",drop = stopwords("german")))
My problem now is, that I want a data.frame as output with the comment_id in the first column and word_token in the column. So the output I would like to have looks as followed:
df <- data.frame(comment_id = c(1,1,1,2,2,2),comment_tokens = c("hallo","nam","aaron","lieb","dank","video"))
I tried different do.calls (cbind/rbind), but they don't give me the result I need. So what is the function I'm looking for, is it map() from the tidyverse?
Thank you in advance.
Cheers,
Aaron
答案1
得分: 1
这是使用purrr中的imap_dfr的一个选项：
library(corpus)library(dplyr)library(purrr)text <- data.frame(comment_id = 1:2,comment_content = c("Hallo mein Name ist aaron","Vielen Lieben Dank für das Video"))tmp <- text_tokens(text$comment_content,text_filter(stemmer = "de",drop = corpus::stopwords_de)) %>%purrr::imap_dfr(function(x, y) {tibble(comment_id = y,comment_tokens = x)})tmp#> # A tibble: 6 × 2#> comment_id comment_tokens#> <int> <chr>#> 1 1 hallo#> 2 1 nam#> 3 1 aaron#> 4 2 lieb#> 5 2 dank#> 6 2 video
或者，如果你更喜欢使用匿名函数：
tmp <- text_tokens(text$comment_content, text_filter(stemmer = "de",drop = corpus::stopwords_de)) %>%purrr::imap_dfr(~ tibble(comment_id = .y, comment_tokens = .x))
英文:
Here's an option using imap_dfr from purrr:
library(corpus)library(dplyr)library(purrr)text <- data.frame(comment_id = 1:2,comment_content = c("Hallo mein Name ist aaron","Vielen Lieben Dank für das Video"))tmp <- text_tokens(text$comment_content,text_filter(stemmer = "de",drop = corpus::stopwords_de)) %>%purrr::imap_dfr(function(x, y) {tibble(comment_id = y,comment_tokens = x)})tmp#> # A tibble: 6 × 2#> comment_id comment_tokens#> <int> <chr>#> 1 1 hallo#> 2 1 nam#> 3 1 aaron#> 4 2 lieb#> 5 2 dank#> 6 2 video
Or if you prefer using an anonymous function:
tmp <- text_tokens(text$comment_content, text_filter(stemmer = "de",drop = corpus::stopwords_de)) %>%purrr::imap_dfr(~ tibble(comment_id = .y, comment_tokens = .x))
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