PandasSchema | validation library for Pandas data frames using user

by multimeric Python Version: 0.3.5 License: GPL-3.0

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

kandi X-RAY | PandasSchema Summary

PandasSchema is a Python library typically used in Data Science, Pandas applications. PandasSchema has no bugs, it has no vulnerabilities, it has build file available, it has a Strong Copyleft License and it has low support. You can download it from GitHub.

A validation library for Pandas data frames using user-friendly schemas

Support

Quality

Security

License

Reuse

Support

PandasSchema has a low active ecosystem.

It has 184 star(s) with 36 fork(s). There are 6 watchers for this library.

It had no major release in the last 12 months.

There are 26 open issues and 21 have been closed. On average issues are closed in 186 days. There are 11 open pull requests and 0 closed requests.

It has a neutral sentiment in the developer community.

The latest version of PandasSchema is 0.3.5

Quality

PandasSchema has 0 bugs and 0 code smells.

Security

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

PandasSchema code analysis shows 0 unresolved vulnerabilities.

There are 0 security hotspots that need review.

License

PandasSchema is licensed under the GPL-3.0 License. This license is Strong Copyleft.

Strong Copyleft licenses enforce sharing, and you can use them when creating open source projects.

Reuse

PandasSchema releases are available to install and integrate.

Build file is available. You can build the component from source.

It has 1177 lines of code, 149 functions and 19 files.

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

Top functions reviewed by kandi - BETA

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

Validate the schema
Get the column names

Get all kandi verified functions for this library.

PandasSchema Key Features

No Key Features are available at this moment for PandasSchema.

PandasSchema Examples and Code Snippets

No Code Snippets are available at this moment for PandasSchema.

Community Discussions

Trending Discussions on PandasSchema

Python coulmns validation using pandas schema

QUESTION

Python coulmns validation using pandas schema

Asked 2020-Oct-02 at 07:37

I am trying to validate my DataFrame coulmns using PandasSchema.I am stuck at validating some columns such as columns like :

1.ip_address- should contain ip address in following format 1.1.1.1 or it should be null if any other value it should raise an error. 2.initial_date- format yyyy-mm-dd h:m:s or mm-dd-yyyy h:m:s etc. 3.customertype should be in['type1','type2','type3'] anything else raise an error. 4.customer satisfied= yes/no or blank 5.customerid should not be longer than 5 chracter eg- cus01,cus02 6.time should be in %:%: format or h:m:s format anything else raise an exception.

...

ANSWER

Answered 2020-Sep-30 at 10:51

I've just looked at the documentation for PandasShema and most if not all you are looking for it out of the box functionality. Take a look at:

As a quick attempt to solve your issue, something along the lines of this should work:

Source https://stackoverflow.com/questions/64130610

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

Vulnerabilities

No vulnerabilities reported

Install PandasSchema

You can download it from GitHub.
You can use PandasSchema 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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