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nltk | NLTK the Natural Language Toolkit | Natural Language Processing library

 by   nltk Python Version: 3.8.1 License: Apache-2.0

 by   nltk Python Version: 3.8.1 License: Apache-2.0

kandi X-RAY | nltk Summary

nltk is a Python library typically used in Artificial Intelligence, Natural Language Processing applications. nltk has no bugs, it has build file available, it has a Permissive License and it has medium support. However nltk has 4 vulnerabilities. You can install using 'pip install nltk' or download it from GitHub, PyPI.
NLTK -- the Natural Language Toolkit -- is a suite of open source Python modules, data sets, and tutorials supporting research and development in Natural Language Processing. NLTK requires Python version 3.7, 3.8, 3.9 or 3.10. For documentation, please visit nltk.org.
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Quality
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Security
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kandi-support Support

  • nltk has a medium active ecosystem.
  • It has 11409 star(s) with 2680 fork(s). There are 469 watchers for this library.
  • There were 2 major release(s) in the last 6 months.
  • There are 209 open issues and 1464 have been closed. On average issues are closed in 410 days. There are 12 open pull requests and 0 closed requests.
  • It has a neutral sentiment in the developer community.
  • The latest version of nltk is 3.8.1
nltk Support
Best in #Natural Language Processing
Average in #Natural Language Processing
nltk Support
Best in #Natural Language Processing
Average in #Natural Language Processing

quality kandi Quality

  • nltk has no bugs reported.
nltk Quality
Best in #Natural Language Processing
Average in #Natural Language Processing
nltk Quality
Best in #Natural Language Processing
Average in #Natural Language Processing

securitySecurity

  • nltk has 4 vulnerability issues reported (0 critical, 4 high, 0 medium, 0 low).
nltk Security
Best in #Natural Language Processing
Average in #Natural Language Processing
nltk Security
Best in #Natural Language Processing
Average in #Natural Language Processing

license License

  • nltk is licensed under the Apache-2.0 License. This license is Permissive.
  • Permissive licenses have the least restrictions, and you can use them in most projects.
nltk License
Best in #Natural Language Processing
Average in #Natural Language Processing
nltk License
Best in #Natural Language Processing
Average in #Natural Language Processing

buildReuse

  • nltk releases are not available. You will need to build from source code and install.
  • Deployable package is available in PyPI.
  • Build file is available. You can build the component from source.
  • Installation instructions are not available. Examples and code snippets are available.
nltk Reuse
Best in #Natural Language Processing
Average in #Natural Language Processing
nltk Reuse
Best in #Natural Language Processing
Average in #Natural Language Processing
Top functions reviewed by kandi - BETA

kandi has reviewed nltk and discovered the below as its top functions. This is intended to give you an instant insight into nltk implemented functionality, and help decide if they suit your requirements.

  • Train the model .
    • Process relation relations .
      • Generate node coordinates for node .
        • Perform a postag regression on the model .
          • Create a LU for the given function .
            • returns a list of words
              • Compute the BLEU score .
                • Train a hidden Markov model .
                  • Example demo .
                    • Find a jar file for the given name pattern .

                      Get all kandi verified functions for this library.

                      Get all kandi verified functions for this library.

                      nltk Key Features

                      NLTK Source

                      nltk Examples and Code Snippets

                      See all related Code Snippets

                      Community Discussions

                      Trending Discussions on nltk
                      • Pandas - Keyword count by Category
                      • Import numpy can't be resolved ERROR When I already have numpy installed
                      • How to Capitalize Locations in a List Python
                      • Manually install Open Multilingual Worldnet (NLTK)
                      • tokenize sentence into words python
                      • Convert words between part of speech, when wordnet doesn't do it
                      • How do I turn this oddly formatted looped print function into a data frame with similar output?
                      • Sagemaker Serverless Inference & custom container: Model archiver subprocess fails
                      • How to get a nested list by stemming the words inside the nested lists?
                      • No module named 'nltk.lm' in Google colaboratory
                      Trending Discussions on nltk

                      QUESTION

                      Pandas - Keyword count by Category

                      Asked 2022-Apr-04 at 13:41

                      I am trying to get a count of the most occurring words in my df, grouped by another Columns values:

                      I have a dataframe like so:

                      df=pd.DataFrame({'Category':['Red','Red','Blue','Yellow','Blue'],'Text':['this is very good ','good','dont like','stop','dont like']})
                      

                      enter image description here

                      This is the way that I have counted the keywords in the Text column:

                      from collections import Counter
                      
                      top_N = 100
                      
                      
                      stopwords = nltk.corpus.stopwords.words('english')
                      # # RegEx for stopwords
                      RE_stopwords = r'\b(?:{})\b'.format('|'.join(stopwords))
                      # replace '|'-->' ' and drop all stopwords
                      words = (df.Text
                                 .str.lower()
                                 .replace([r'\|', RE_stopwords], [' ', ''], regex=True)
                                 .str.cat(sep=' ')
                                 .split()
                      )
                      
                      # generate DF out of Counter
                      df_top_words = pd.DataFrame(Counter(words).most_common(top_N),
                                          columns=['Word', 'Frequency']).set_index('Word')
                      print(df_top_words)
                      
                      

                      Which produces this result:

                      However this just generates a list of all of the words in the data frame, what I am after is something along the lines of this:

                      ANSWER

                      Answered 2022-Apr-04 at 13:11

                      Your words statement finds the words that you care about (removing stopwords) in the text of the whole column. We can change that a bit to apply the replacement on each row instead:

                      df["Text"] = (
                          df["Text"]
                          .str.lower()
                          .replace([r'\|', RE_stopwords], [' ', ''], regex=True)
                          .str.strip()
                          # .str.cat(sep=' ')
                          .str.split()  # Previously .split()
                      )
                      

                      Resulting in:

                        Category          Text
                      0      Red        [good]
                      1      Red        [good]
                      2     Blue  [dont, like]
                      3   Yellow        [stop]
                      4     Blue  [dont, like]
                      

                      Now, we can use .explode and then .groupby and .size to expand each list element to its own row and then count how many times does a word appear in the text of each (original) row:

                      df.explode("Text").groupby(["Category", "Text"]).size()
                      

                      Resulting in:

                      Category  Text
                      Blue      dont    2
                                like    2
                      Red       good    2
                      Yellow    stop    1
                      

                      Now, this does not match your output sample because in that sample you're not applying the .replace step from the original words statement (now used to calculate the new value of the "Text" column). If you wanted that result, you just have to comment out that .replace line (but I guess that's the whole point of this question)

                      Source https://stackoverflow.com/questions/71737328

                      Community Discussions, Code Snippets contain sources that include Stack Exchange Network

                      Vulnerabilities

                      No vulnerabilities reported

                      Install nltk

                      You can install using 'pip install nltk' or download it from GitHub, PyPI.
                      You can use nltk like any standard Python library. You will need to make sure that you have a development environment consisting of a Python distribution including header files, a compiler, pip, and git installed. Make sure that your pip, setuptools, and wheel are up to date. When using pip it is generally recommended to install packages in a virtual environment to avoid changes to the system.

                      Support

                      Do you want to contribute to NLTK development? Great! Please read CONTRIBUTING.md for more details. See also how to contribute to NLTK.

                      Find more information at:

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                      Install
                      • pip install nltk

                      Clone
                      • https://github.com/nltk/nltk.git

                      • gh repo clone nltk/nltk

                      • git@github.com:nltk/nltk.git

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