xalpha | Fund Investment Management Backtesting Engine | Cryptocurrency library

 by   refraction-ray Python Version: 0.12.0 License: MIT

kandi X-RAY | xalpha Summary

kandi X-RAY | xalpha Summary

xalpha is a Python library typically used in Blockchain, Cryptocurrency applications. xalpha has no vulnerabilities, it has build file available, it has a Permissive License and it has medium support. However xalpha has 1 bugs. You can install using 'pip install xalpha' or download it from GitHub, PyPI.

Fund Investment Management Backtesting Engine
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            kandi-support Support

              xalpha has a medium active ecosystem.
              It has 1721 star(s) with 362 fork(s). There are 53 watchers for this library.
              There were 3 major release(s) in the last 12 months.
              There are 40 open issues and 114 have been closed. On average issues are closed in 38 days. There are no pull requests.
              It has a neutral sentiment in the developer community.
              The latest version of xalpha is 0.12.0

            kandi-Quality Quality

              xalpha has 1 bugs (0 blocker, 0 critical, 1 major, 0 minor) and 128 code smells.

            kandi-Security Security

              xalpha has no vulnerabilities reported, and its dependent libraries have no vulnerabilities reported.
              xalpha code analysis shows 0 unresolved vulnerabilities.
              There are 47 security hotspots that need review.

            kandi-License License

              xalpha is licensed under the MIT License. This license is Permissive.
              Permissive licenses have the least restrictions, and you can use them in most projects.

            kandi-Reuse Reuse

              xalpha releases are available to install and integrate.
              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.
              xalpha saves you 4098 person hours of effort in developing the same functionality from scratch.
              It has 8707 lines of code, 466 functions and 30 files.
              It has high code complexity. Code complexity directly impacts maintainability of the code.

            Top functions reviewed by kandi - BETA

            kandi has reviewed xalpha and discovered the below as its top functions. This is intended to give you an instant insight into xalpha implemented functionality, and help decide if they suit your requirements.
            • Fetches the latest price and returns it
            • Convert string to float
            • Return a datetime object
            • Fetches the price data for a given price
            • This method fetches the price for a given price
            • This method fetches the price for a given price
            • Convert string to float
            • Decorator to cache a function
            • Convert a datetime string to a datetime object
            • Get stockholdings
            • Get industry information
            • Get the position of the t1dict
            • Processing fees page
            • Decorator for reconnecting
            • Analyze the risk value
            • Generate the status for a given date
            • Get sz status
            • Returns a pandas dataframe with holdings
            • Return the netvalue as a line chart
            • Returns a list of shares
            • Retrieve data from BTJ
            • Return the SHHU data for a given share
            • Calculate the SharQU value for a given price
            • Calculate price
            • Get SH results
            • Set the module to use
            Get all kandi verified functions for this library.

            xalpha Key Features

            No Key Features are available at this moment for xalpha.

            xalpha Examples and Code Snippets

            No Code Snippets are available at this moment for xalpha.

            Community Discussions

            QUESTION

            R loop for linear regression lm(y~x) and save model output as a dataset
            Asked 2020-Jul-13 at 13:45

            I would like to make a regression loop lm(y~x) with a dataset with one y and several x, and run the regression for each x, and then also store the results (estimate, p-values) in a data.frame() so I don't have to copy them manually (especially as my real data set it much bigger). I think this should not be too difficult, but I struggle a lot to make it work and appreciate your help: Here is my sample data set:

            ...

            ANSWER

            Answered 2020-Jul-13 at 13:33

            One option would be to use lapply to perform a regression with each of the independent variables. Use tidy from broom library to store the results into a tidy format.

            Source https://stackoverflow.com/questions/62876417

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

            Vulnerabilities

            No vulnerabilities reported

            Install xalpha

            You can install using 'pip install xalpha' or download it from GitHub, PyPI.
            You can use xalpha 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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            Install
          • PyPI

            pip install xalpha

          • CLONE
          • HTTPS

            https://github.com/refraction-ray/xalpha.git

          • CLI

            gh repo clone refraction-ray/xalpha

          • sshUrl

            git@github.com:refraction-ray/xalpha.git

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