hcuppy | Python implementation of the tools from H-CUP

 by   yubin-park Python Version: 0.0.7 License: Apache-2.0

X-RayKey FeaturesCode SnippetsCommunity Discussions(1)VulnerabilitiesInstallSupport

kandi X-RAY | hcuppy Summary

kandi X-RAY | hcuppy Summary

hcuppy is a Python library. hcuppy has no bugs, it has no vulnerabilities, it has build file available, it has a Permissive License and it has low support. You can install using 'pip install hcuppy' or download it from GitHub, PyPI.

A Python package for H-CUP Tools and Software. The modules implemented in this package are as follows:. NOTE that this package does not support for ICD-9.
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              hcuppy has a low active ecosystem.
              It has 17 star(s) with 6 fork(s). There are 2 watchers for this library.
              OutlinedDot
              It had no major release in the last 12 months.
              There are 2 open issues and 0 have been closed. On average issues are closed in 172 days. There are no pull requests.
              It has a neutral sentiment in the developer community.
              The latest version of hcuppy is 0.0.7

            kandi-Quality Quality

              hcuppy has 0 bugs and 10 code smells.

            kandi-Security Security

              hcuppy has no vulnerabilities reported, and its dependent libraries have no vulnerabilities reported.
              hcuppy code analysis shows 0 unresolved vulnerabilities.
              There are 0 security hotspots that need review.

            kandi-License License

              hcuppy 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.

            kandi-Reuse Reuse

              hcuppy 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.
              It has 540 lines of code, 40 functions and 18 files.
              It has medium code complexity. Code complexity directly impacts maintainability of the code.

            Top functions reviewed by kandi - BETA

            kandi has reviewed hcuppy and discovered the below as its top functions. This is intended to give you an instant insight into hcuppy implemented functionality, and help decide if they suit your requirements.
            • Download CPT files
            • Expand a CPT
            • Ask license
            • Replace quotes in a row
            • Read a csv file into a dictionary
            • Read csv file
            • Read a csv file
            • Read a csv file
            • Read cpt file and return dict
            Get all kandi verified functions for this library.

            hcuppy Key Features

            No Key Features are available at this moment for hcuppy.

            hcuppy Examples and Code Snippets

            No Code Snippets are available at this moment for hcuppy.

            Community Discussions

            Trending Discussions on hcuppy

            Pandas to risk adjust surgery data - how to pass a list for 20,000 patients?

            QUESTION

            Pandas to risk adjust surgery data - how to pass a list for 20,000 patients?
            Asked 2020-Oct-21 at 17:28

            I am a surgeon trying to use hcuppy to risk adjust surgical operation data. I have a pandas dataframe - 500k records and 56 columns. Calling the adjustment module (elixhauser) expects a list of diagnostic codes and returns a weighted result for risk adjustment related to the diagnostic code.

            eg

            ...

            ANSWER

            Answered 2020-Oct-21 at 17:28

            Because ee.get_elixhauser is not a method that receives a whole data frame or array as an input parameter but does receive a scalar value, you will need to run method across every element of the data frame. Therefore, consider DataFrame.applymap assuming all data frame elements are the same type. Also, to avoid issues with assigning by slices due to iloc, use copy() before calling method.

            Source https://stackoverflow.com/questions/64433435

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

            Vulnerabilities

            No vulnerabilities reported

            Install hcuppy

            You can install using 'pip install hcuppy' or download it from GitHub, PyPI.
            You can use hcuppy 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 .
            Find more information at:

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            Install
          • PyPI

            pip install hcuppy

            • CLONE
          • HTTPS

            https://github.com/yubin-park/hcuppy.git

          • CLI

            gh repo clone yubin-park/hcuppy

          • sshUrl

            git@github.com:yubin-park/hcuppy.git

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