janeaustenr | An R Package for Jane Austen 's Complete Novels orange_book | Computer Vision library

by juliasilge R Version: v0.1.5 License: Non-SPDX

X-Ray Key Features Code Snippets Community Discussions(10)Vulnerabilities Install Support

kandi X-RAY | janeaustenr Summary

janeaustenr is a R library typically used in Artificial Intelligence, Computer Vision applications. janeaustenr has no bugs, it has no vulnerabilities and it has low support. However janeaustenr has a Non-SPDX License. You can download it from GitHub.

An R Package for Jane Austen's Complete Novels :orange_book:

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Support

janeaustenr has a low active ecosystem.

It has 86 star(s) with 22 fork(s). There are 7 watchers for this library.

It had no major release in the last 12 months.

There are 0 open issues and 1 have been closed. There are no pull requests.

It has a neutral sentiment in the developer community.

The latest version of janeaustenr is v0.1.5

Quality

janeaustenr has 0 bugs and 0 code smells.

Security

janeaustenr has no vulnerabilities reported, and its dependent libraries have no vulnerabilities reported.

janeaustenr code analysis shows 0 unresolved vulnerabilities.

There are 0 security hotspots that need review.

License

janeaustenr has a Non-SPDX License.

Non-SPDX licenses can be open source with a non SPDX compliant license, or non open source licenses, and you need to review them closely before use.

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janeaustenr releases are available to install and integrate.

Installation instructions, examples and code snippets are available.

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janeaustenr Key Features

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Community Discussions

Trending Discussions on janeaustenr

Two shiny widgets cannot be used at the same time to subset a dataframe

Tokenize vector of dataframe by word

Error in R term frequency analysis (TF-IDF)

Why tf-idf truncates words?

TidyText Clustering

Error in row_number() after group_by() and unnest_tokens()

Keep the word frequency and inverse for one type of documents

usage of bind tf_df in R

Calculate `tf-idf` for a data frame of documents

R tidytext Remove word if part of relevant bigrams, but keep if not

QUESTION

Two shiny widgets cannot be used at the same time to subset a dataframe

Asked 2022-Jan-10 at 11:13

I have the shiny app below in which I create a wordcloud. This wordcloud is based on the shiny widgets in the sidebar. The selectInput() subsets it by label, the Maximum Number of Words: is supposed to show the maximum count of words that will be displayed in the wordcloud and the Minimun Frequency the minimum frequency that a word needs to be displayed. Those widgets are reactive and are based on the df() function which creates the dataframe needed for the wordcloud. The proble is that when I subset using input$freq the dataframe has fewer rows than needed to subset with input$max as well so nothing is displayed.

...

ANSWER

Answered 2022-Jan-10 at 08:54

I'm not totally sure, but since you say

when the app is launched nothing is displayed

It could be related to this bug.

I created this solution.

This looks complicated, but it really isn't. Simply define the following function (wordcloud2a()), then use it where you'd normally use wordcloud2().

Source https://stackoverflow.com/questions/70646536

QUESTION

Tokenize vector of dataframe by word

Asked 2022-Jan-09 at 01:37

Im trying to tokenize by word the email column of df dataset but I get

...

ANSWER

Answered 2022-Jan-09 at 01:37

The 3rd argument to unnest_tokens is the input i.e the column in the dataframe which needs to be split. You have passed it as text but there is no text column in your data.

You can do -

Source https://stackoverflow.com/questions/70637652

QUESTION

Error in R term frequency analysis (TF-IDF)

Asked 2021-Nov-14 at 22:29

I tried to run the following code with the following data:

...

ANSWER

Answered 2021-Nov-14 at 22:29

It is possible that count from dplyr got masked from any other package loaded with having the same function count. So, use dplyr::count

Source https://stackoverflow.com/questions/69967685

QUESTION

Why tf-idf truncates words?

Asked 2021-Jun-01 at 17:24

I have a dataframe x that is:

...

ANSWER

Answered 2021-Jun-01 at 17:24

From your output, it appears that there is leading blank-space in the name. If it were just "dispoabl" with no leading/trailing blanks, I would expect

Source https://stackoverflow.com/questions/67793148

QUESTION

TidyText Clustering

Asked 2021-Feb-07 at 17:59

I want to cluster words that are similar using R and the tidytext package. I have created my tokens and would now like to convert it to a matrix in order to cluster it. I would like to try out a number of token techniques to see which provides the most compact clusters.

My code is as follows (taken from the docs of widyr package). I just cant make the next step. Can anyone help?

...

ANSWER

Answered 2021-Feb-07 at 17:59

You can create an appropriate matrix for this via casting from tidytext. There are several functions to cast_, such as cast_sparse().

Let's use four example books, and cluster the chapters within the books:

Source https://stackoverflow.com/questions/66030942

QUESTION

Error in row_number() after group_by() and unnest_tokens()

Asked 2020-Aug-27 at 11:02

I am trying to mutate row numbers after tokenizing within a group_by block and get an error: Error: Can't recycle input of size 73422 to size 37055. Run rlang::last_error() to see where the error occurred.

...

ANSWER

Answered 2020-Aug-27 at 11:02

Just move your group_by to after the unnest_tokens statement. Like this:

Source https://stackoverflow.com/questions/63613073

QUESTION

Keep the word frequency and inverse for one type of documents

Asked 2020-Aug-17 at 14:52

Code example to keep the term and inverse frequency:

...

ANSWER

Answered 2020-Aug-17 at 14:52

If I understand the question correctly, you want to get a tf-idf per word across your three different documents - in other words, an output data.frame that is unique by word.

The problem is that you cannot do this with tf-idf, because the "idf" part multiplies the term frequency by the log of the inverse document frequency. When you combine the three documents, then every term occurs in your single combined document, meaning it has a document frequency of 1, equal to the number of documents. So the tf-idf for every word of a combined document is zero. I've shown this below.

tf-idf is different for the same words within documents. That's why the tidytext example shows each word by book, not once for the whole corpus.

Here's how to do this in quanteda by document:

Source https://stackoverflow.com/questions/63449628

QUESTION

usage of bind tf_df in R

Asked 2020-Jun-25 at 01:20

    library(janeaustenr)
    library(tidytext)
    library(tidyverse)
    library(tm)
    library(corpus)

   text <- removeNumbers(sensesensibility)

text <- data.frame(text)

tidy_text <- text %>% unnest_tokens(bigram,text,token='ngrams',n=2)


tidy_text %>%count(bigram,sort =TRUE)
             
             
tidy_text <-tidy_text %>% separate(bigram,c('word1','word2'),sep =' ')

tidy_text_filtered <- tidy_text %>% 
                      filter(!word1 %in% stop_words$word)%>%
                      filter(!word2 %in% stop_words$word)
                   


trigram_count <- tidy_text_filtered%>% count(word1,word2, sort= TRUE)
                

united <- trigram_count%>%unite(bigram,word1,word2,sep=' ')%>%
          filter(n >1)

united <- united %>% bind_tf_idf(bigram,n)

...

ANSWER

Answered 2020-Jun-24 at 22:46

The bind_tf_idf includes three argument 'term', 'document' and 'n'. We can create the 'document' column

Source https://stackoverflow.com/questions/62564722

QUESTION

Calculate `tf-idf` for a data frame of documents

Asked 2020-Mar-25 at 20:01

The following code

...

ANSWER

Answered 2020-Mar-25 at 20:01

There are two things you needed to change:

since you did not set stringsAsFactors = FALSE when constructing the data.frame, you need to convert text to character first.
You do not have a column named book, which means you have to select some other column as document. Since you put a column named class into your example, I assume you want to calculate the tf-idf over this column.

Here is the code:

Source https://stackoverflow.com/questions/60855101

QUESTION

R tidytext Remove word if part of relevant bigrams, but keep if not

Asked 2020-Mar-17 at 13:56

By using unnest_token, I want to create a tidy text tibble which combines two different tokens: single words and bigrams. The reasoning behind is that sometimes single words are the more reasonable unit to study and sometime it is rather higher-order n-grams.

If two words show up as a "sensible" bigram, I want to store the bigram and not store the individual words. If the same words show up in a different context (i.e. not as bigram), then I want to save them as single words.

In the stupid example below "of the" is an important bigram. Thus, I want to remove single words "of" and "the" if they actually appear as "of the" in the text. But if "of" and "the" show up in other combinations, I would like to keep them as single words.

...

ANSWER

Answered 2020-Mar-17 at 13:17

You could do this by replacing the bigrams you're intrested in with a compound in text, before tokenisation (i.e. unnest_tokens):

Source https://stackoverflow.com/questions/60721175

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