quantdata | nextgenereation data solution / 下一代数据解决方案 | Data Visualization library

by QUANTAXIS Python Version: Current License: No License

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

kandi X-RAY | quantdata Summary

quantdata is a Python library typically used in Analytics, Data Visualization applications. quantdata has no bugs, it has no vulnerabilities, it has build file available and it has low support. You can download it from GitHub.

nextgenereation data solution / 下一代数据解决方案

Support

Quality

Security

License

Reuse

Support

quantdata has a low active ecosystem.

It has 19 star(s) with 16 fork(s). There are 23 watchers for this library.

It had no major release in the last 6 months.

quantdata has no issues reported. There are no pull requests.

It has a neutral sentiment in the developer community.

The latest version of quantdata is current.

Quality

quantdata has 0 bugs and 0 code smells.

Security

quantdata has no vulnerabilities reported, and its dependent libraries have no vulnerabilities reported.

quantdata code analysis shows 0 unresolved vulnerabilities.

There are 0 security hotspots that need review.

License

quantdata does not have a standard license declared.

Check the repository for any license declaration and review the terms closely.

Without a license, all rights are reserved, and you cannot use the library in your applications.

Reuse

quantdata 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.

quantdata saves you 191 person hours of effort in developing the same functionality from scratch.

It has 470 lines of code, 41 functions and 22 files.

It has low code complexity. Code complexity directly impacts maintainability of the code.

Top functions reviewed by kandi - BETA

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

Fetch data
Transform a DataFrame into a new one
Returns number of seconds
Process the given data into a DataEntity
Parse ticker
Process the origin data
Process mapping
Resolves dependencies
Convert pandas dataframe to pandas dataframe
Returns the common dataframe

Get all kandi verified functions for this library.

quantdata Key Features

No Key Features are available at this moment for quantdata.

quantdata Examples and Code Snippets

No Code Snippets are available at this moment for quantdata.

Community Discussions

Trending Discussions on quantdata

How to split array with 1 column into multiple columns (numpy array)

QUESTION

How to split array with 1 column into multiple columns (numpy array)

Asked 2019-Nov-21 at 16:36

I currently have a .txt file that has been loaded into python as a list, and then placed into a np array as a single column with n number of rows depending on the file size. The file has rows trimmed off the top and bottom to clean it up. Relevant code is shown below:

...

ANSWER

Answered 2019-Nov-21 at 16:36

All fixed. I did split the txt file incorrectly, Using line.split() solved the issue. pandas was also necessary, as this was not the best application for np. Thanks everyone for the feedback.

Source https://stackoverflow.com/questions/58964668

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

Vulnerabilities

No vulnerabilities reported

Install quantdata

You can download it from GitHub.
You can use quantdata 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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