stock-analysis | use interfaces for basic technical analysis | Business library

by stefmolin Python Version: 2nd_edition_patch_1 License: MIT

X-Ray Key Features Code Snippets Community Discussions(1)Vulnerabilities Install Support

kandi X-RAY | stock-analysis Summary

stock-analysis is a Python library typically used in Web Site, Business applications. stock-analysis has no bugs, it has no vulnerabilities, it has build file available, it has a Permissive License and it has low support. You can download it from GitHub.

Package for making elements of technical analysis of a stock easier. This package is meant to be a starting point for you to develop your own. As such, all the instructions for installing/setup will be assuming you will continue to develop on your end.

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Quality

Security

License

Reuse

Support

stock-analysis has a low active ecosystem.

It has 176 star(s) with 79 fork(s). There are 5 watchers for this library.

It had no major release in the last 6 months.

There are 0 open issues and 3 have been closed. On average issues are closed in 60 days. There are no pull requests.

It has a neutral sentiment in the developer community.

The latest version of stock-analysis is 2nd_edition_patch_1

Quality

stock-analysis has 0 bugs and 0 code smells.

Security

stock-analysis has no vulnerabilities reported, and its dependent libraries have no vulnerabilities reported.

stock-analysis code analysis shows 0 unresolved vulnerabilities.

There are 0 security hotspots that need review.

License

stock-analysis 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

stock-analysis 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.

Top functions reviewed by kandi - BETA

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

Wrapper function for window_calculation
Determine the layout of the subplots
Return a list of items
Get ticker data
Get data from Yahoo Finance
Returns the ticker with the given index
Calculates the alpha of a portfolio
Compute the portfolio return
Beta distribution
Decorator to convert label column names to strings
Sanitize label
Fill between two data points
Fill between two labels
Calculate moving average
Wrapper for _window_calculation
Compute the correlations between two DataFrames
Plot a histogram
Returns True if the portfolio returns False otherwise
Get bitcoin data for given currency_code
Return Sharpe ratio
Return a heatmap of the DataFrame
Plot daily prices
Calculate Exponential smoothing
Calculate the mean of a window
Compute a heatmap of the correlation matrix
Check if the portfolio is a bear market

Get all kandi verified functions for this library.

stock-analysis Key Features

No Key Features are available at this moment for stock-analysis.

stock-analysis Examples and Code Snippets

No Code Snippets are available at this moment for stock-analysis.

Community Discussions

Trending Discussions on stock-analysis

Python instance attribute assignment in class created using @dataclass

QUESTION

Python instance attribute assignment in class created using @dataclass

Asked 2020-Sep-28 at 14:24

I have just started using @dataclass decorator. This is my without dataclass implementation

...

ANSWER

Answered 2020-Sep-28 at 14:24

If you want to include data as a field, you can initialize it with field(init=False) to indicate that it's value is not an argument to __init__:

Source https://stackoverflow.com/questions/64086511

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

Vulnerabilities

No vulnerabilities reported

Install stock-analysis

You can download it from GitHub.
You can use stock-analysis 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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