data-science-types | , type information , for numpy , pandas | Data Visualization library

by predictive-analytics-lab Python Version: 0.2.23 License: Apache-2.0

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

kandi X-RAY | data-science-types Summary

data-science-types is a Python library typically used in Analytics, Data Visualization, Numpy, Pandas applications. data-science-types has no bugs, it has no vulnerabilities, it has build file available, it has a Permissive License and it has low support. You can install using 'pip install data-science-types' or download it from GitHub, PyPI.

Mypy stubs, i.e., type information, for numpy, pandas and matplotlib

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Quality

Security

License

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Support

data-science-types has a low active ecosystem.

It has 184 star(s) with 58 fork(s). There are 8 watchers for this library.

It had no major release in the last 12 months.

There are 33 open issues and 23 have been closed. On average issues are closed in 13 days. There are 6 open pull requests and 0 closed requests.

It has a neutral sentiment in the developer community.

The latest version of data-science-types is 0.2.23

Quality

data-science-types has no bugs reported.

Security

data-science-types has no vulnerabilities reported, and its dependent libraries have no vulnerabilities reported.

License

data-science-types is licensed under the Apache-2.0 License. This license is Permissive.

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

Reuse

data-science-types 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.

Top functions reviewed by kandi - BETA

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

This function is used to change the version number .
Substitute substitution .
Create a code template from a file .
Initialize the pattern .
Indent lines .

Get all kandi verified functions for this library.

data-science-types Key Features

No Key Features are available at this moment for data-science-types.

data-science-types Examples and Code Snippets

No Code Snippets are available at this moment for data-science-types.

Community Discussions

Trending Discussions on data-science-types

mypy cannot infer type of generator comprehension correctly

QUESTION

mypy cannot infer type of generator comprehension correctly

Asked 2020-Oct-05 at 11:46

I am using the stub files provided by data-science-types to have mypy be able to check my pandas related code. Sadly I get the following behaviour:

For

...

ANSWER

Answered 2020-Oct-04 at 00:40

You are confusing a generator with a sequence. A sequence is, by definition,

An iterable which supports efficient element access using integer indices via the __getitem__() special method and defines a __len__() method that returns the length of the sequence.

A generator supports neither, and it's not a kind of mapping, either, so you can't pass one to pd.concat.

Source https://stackoverflow.com/questions/64188880

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

Vulnerabilities

No vulnerabilities reported

Install data-science-types

You can install using 'pip install data-science-types' or download it from GitHub, PyPI.
You can use data-science-types 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

We always welcome contributions. All pull requests are subject to CI checks. We check for compliance with Mypy and that the file formatting conforms to our Black specification. You can install these dev dependencies via. This will also install NumPy, pandas, and Matplotlib to be able to run the tests.

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