xbrl-parse | Get historical fundamental data time series in Pandas | Cryptocurrency library

by fernavid Python Version: Current License: MIT

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kandi X-RAY | xbrl-parse Summary

xbrl-parse is a Python library typically used in Blockchain, Cryptocurrency, Pandas applications. xbrl-parse has no bugs, it has no vulnerabilities, it has a Permissive License and it has low support. However xbrl-parse build file is not available. You can download it from GitHub.

Get historical fundamental data time series in Pandas Dataframes from SEC Edgar for any company. I couldn’t find this anywhere in an easy to use way. Other options were very complicated and didn’t work well across companies. Ask for historical data for a particular ticker and financial statement item, and it will return a Pandas DataFrame with all the series it was able to pull for that item. root will always be the entity as a whole, but you might get back multiple series if the company has divisions geographically, or different business segments.

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Support

xbrl-parse has a low active ecosystem.

It has 5 star(s) with 4 fork(s). There are 4 watchers for this library.

It had no major release in the last 6 months.

xbrl-parse has no issues reported. There are no pull requests.

It has a neutral sentiment in the developer community.

The latest version of xbrl-parse is current.

Quality

xbrl-parse has no bugs reported.

Security

xbrl-parse has no vulnerabilities reported, and its dependent libraries have no vulnerabilities reported.

License

xbrl-parse is licensed under the MIT License. This license is Permissive.

Permissive licenses have the least restrictions, and you can use them in most projects.

Reuse

xbrl-parse releases are not available. You will need to build from source code and install.

xbrl-parse has no build file. You will be need to create the build yourself to build the component from source.

Installation instructions are not available. Examples and code snippets are available.

Top functions reviewed by kandi - BETA

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

Extract a series from an index
Creates a list of Document objects
Return a list of datapoints
Get context period period
Returns the segment with the given context
Checks if the given start and end dates are in a quarter

Get all kandi verified functions for this library.

xbrl-parse Key Features

No Key Features are available at this moment for xbrl-parse.

xbrl-parse Examples and Code Snippets

No Code Snippets are available at this moment for xbrl-parse.

Community Discussions

Trending Discussions on xbrl-parse

How do I install xbrl_parser on the server from https://github.com/ONSBigData/parsing_company_accounts?

QUESTION

How do I install xbrl_parser on the server from https://github.com/ONSBigData/parsing_company_accounts?

Asked 2020-Jan-19 at 09:30

I am trying to Extracting Data from Companies House Electronic Records following the example provided in https://github.com/ONSBigData/parsing_company_accounts.

I run into issues with the installation of xbrl_parser on my server. When I run in terminal pip3 install xbrl_parser or pip install xbrl_parser I get an error.

...

ANSWER

Answered 2020-Jan-18 at 16:35

It's a bug in the distribution: the authors has forgotten to include file README.md into the distribution package.

Report the bug to their issue tracker.

Also you cannot install directly from Github: there is no setup.py in the repo.

Source https://stackoverflow.com/questions/59802483

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

Vulnerabilities

No vulnerabilities reported

Install xbrl-parse

You can download it from GitHub.
You can use xbrl-parse 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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