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jupyter | Jupyter metapackage for installation , docs and chat | Data Visualization library

 by   jupyter Python Version: Current License: BSD-3-Clause

 by   jupyter Python Version: Current License: BSD-3-Clause

kandi X-RAY | jupyter Summary

jupyter is a Python library typically used in Analytics, Data Visualization, Jupyter applications. jupyter has no bugs, it has no vulnerabilities, it has build file available, it has a Permissive License and it has high support. You can download it from GitHub.
Jupyter metapackage for installation and docs.
Support
Support
Quality
Quality
Security
Security
License
License
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Reuse

kandi-support Support

  • jupyter has a highly active ecosystem.
  • It has 13986 star(s) with 3612 fork(s). There are 659 watchers for this library.
  • It had no major release in the last 6 months.
  • There are 192 open issues and 190 have been closed. On average issues are closed in 88 days. There are 7 open pull requests and 0 closed requests.
  • It has a negative sentiment in the developer community.
  • The latest version of jupyter is current.
jupyter Support
Best in #Data Visualization
Average in #Data Visualization
jupyter Support
Best in #Data Visualization
Average in #Data Visualization

quality kandi Quality

  • jupyter has 0 bugs and 0 code smells.
jupyter Quality
Best in #Data Visualization
Average in #Data Visualization
jupyter Quality
Best in #Data Visualization
Average in #Data Visualization

securitySecurity

  • jupyter has no vulnerabilities reported, and its dependent libraries have no vulnerabilities reported.
  • jupyter code analysis shows 0 unresolved vulnerabilities.
  • There are 0 security hotspots that need review.
jupyter Security
Best in #Data Visualization
Average in #Data Visualization
jupyter Security
Best in #Data Visualization
Average in #Data Visualization

license License

  • jupyter is licensed under the BSD-3-Clause License. This license is Permissive.
  • Permissive licenses have the least restrictions, and you can use them in most projects.
jupyter License
Best in #Data Visualization
Average in #Data Visualization
jupyter License
Best in #Data Visualization
Average in #Data Visualization

buildReuse

  • jupyter releases are not available. You will need to build from source code and install.
  • Build file is available. You can build the component from source.
  • Installation instructions are not available. Examples and code snippets are available.
  • jupyter saves you 56 person hours of effort in developing the same functionality from scratch.
  • It has 213 lines of code, 3 functions and 5 files.
  • It has low code complexity. Code complexity directly impacts maintainability of the code.
jupyter Reuse
Best in #Data Visualization
Average in #Data Visualization
jupyter Reuse
Best in #Data Visualization
Average in #Data Visualization
Top functions reviewed by kandi - BETA

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

  • Run Sphinx docs .
    • Install Sphinx docs .
      • Register custom CSS files .

        Get all kandi verified functions for this library.

        Get all kandi verified functions for this library.

        jupyter Key Features

        Jupyter metapackage for installation, docs and chat

        jupyter Examples and Code Snippets

        See all related Code Snippets

        Community Discussions

        Trending Discussions on jupyter
        • Compute class weight function issue in 'sklearn' library when used in 'Keras' classification (Python 3.8, only in VS code)
        • How to Export Jupyter Notebook by VSCode in PDF format? (Windows 10)
        • How to undo/redo changes inside the selected cell in Jupyter notebook?
        • iPyKernel throwing "TypeError: object NoneType can't be used in 'await' expression"
        • "Attempting to perform BLAS operation using StreamExecutor without BLAS support" error occurs
        • Running cells with Python 3.10 requires ipykernel installed
        • ipykernel (Jupyter notebook/labs) cannot import name ''filefind" from traitlets.utils
        • lfortran in a jupyter notebook kills kernel
        • Pandas - How to Save A Styled Dataframe to Image
        • embedding jupyter notebook/ google colab in Django app
        Trending Discussions on jupyter

        QUESTION

        Compute class weight function issue in 'sklearn' library when used in 'Keras' classification (Python 3.8, only in VS code)

        Asked 2022-Mar-27 at 23:14

        The classifier script I wrote is working fine and recently added weight balancing to the fitting. Since I added the weight estimate function using 'sklearn' library I get the following error :

        compute_class_weight() takes 1 positional argument but 3 were given
        

        This error does not make sense per documentation. The script should have three inputs but not sure why it says expecting only one variable. Full error and code information is shown below. Apparently, this is failing only in VS code. I tested in the Jupyter notebook and working fine. So it seems an issue with VS code compiler. Any one notice? ( I am using Python 3.8 with other latest other libraries)

        from sklearn.utils import compute_class_weight
        
        train_classes = train_generator.classes
        
        class_weights = compute_class_weight(
                                                "balanced",
                                                np.unique(train_classes),
                                                train_classes                                                    
                                            )
        class_weights = dict(zip(np.unique(train_classes), class_weights)),
        class_weights
        

        In Jupyter Notebook,

        enter image description here

        enter image description here

        ANSWER

        Answered 2022-Mar-27 at 23:14

        After spending a lot of time, this is how I fixed it. I still don't know why but when the code is modified as follows, it works fine. I got the idea after seeing this solution for a similar but slightly different issue.

        class_weights = compute_class_weight(
                                                class_weight = "balanced",
                                                classes = np.unique(train_classes),
                                                y = train_classes                                                    
                                            )
        class_weights = dict(zip(np.unique(train_classes), class_weights))
        class_weights
        

        Source https://stackoverflow.com/questions/69783897

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

        Vulnerabilities

        No vulnerabilities reported

        Install jupyter

        You can download it from GitHub.
        You can use jupyter 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

        For any new features, suggestions and bugs create an issue on GitHub. If you have any questions check and ask questions on community page Stack Overflow .

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

        • gh repo clone jupyter/jupyter

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

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