dowhy | Python library for causal inference | Machine Learning library

by microsoft Python Version: v0.7 License: MIT

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

kandi X-RAY | dowhy Summary

dowhy is a Python library typically used in Artificial Intelligence, Machine Learning applications. dowhy has no bugs, it has no vulnerabilities, it has build file available, it has a Permissive License and it has medium support. You can install using 'pip install dowhy' or download it from GitHub, PyPI.

DoWhy is a Python library for causal inference that supports explicit modeling and testing of causal assumptions. DoWhy is based on a unified language for causal inference, combining causal graphical models and potential outcomes frameworks.

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dowhy has a medium active ecosystem.

It has 3695 star(s) with 583 fork(s). There are 120 watchers for this library.

It had no major release in the last 12 months.

There are 42 open issues and 140 have been closed. On average issues are closed in 109 days. There are 5 open pull requests and 0 closed requests.

It has a neutral sentiment in the developer community.

The latest version of dowhy is v0.7

Quality

dowhy has 0 bugs and 0 code smells.

Security

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

dowhy code analysis shows 0 unresolved vulnerabilities.

There are 0 security hotspots that need review.

License

dowhy is licensed under the MIT License. This license is Permissive.

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

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dowhy releases are available to install and integrate.

Deployable package is available in PyPI.

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

dowhy saves you 2730 person hours of effort in developing the same functionality from scratch.

It has 8134 lines of code, 467 functions and 103 files.

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

Top functions reviewed by kandi - BETA

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

Include simulated variables .
Creates a linear dataset
Identifies an effect on the model .
Identify the outcome for the decision .
Runs the significance test .
Generate yy dataset
Simple test dataset
Test to see if the initial stability parameter has been set up .
Runs the causal estimator .
Performs a path search .

Get all kandi verified functions for this library.

dowhy Key Features

No Key Features are available at this moment for dowhy.

dowhy Examples and Code Snippets

DoWhy:: Causal Inference in observational data

Python

Lines of Code : 45

License : Strong Copyleft (CC BY-SA 4.0)

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causal_df = df.causal.do('tenure', 
                          method = 'weighting', 
                          variable_types = {'Churn': 'd', 'tenure': 'd', 'nr_login',  'c','avg_movies': 'c'},
                          outcome='Churn',co

Community Discussions

Trending Discussions on dowhy

DoWhy:: Causal Inference in observational data

QUESTION

DoWhy:: Causal Inference in observational data

Asked 2020-May-18 at 12:57

I am using the python package DoWhy to see if I have a causal relationship between tenure and churn based on;

...

ANSWER

Answered 2020-May-18 at 12:57

Let's take your questions one by one.

1. Is this the right way?

Yes, your code snippet is correct, assuming that you want to estimate the causal effect of tenure and Churn, by conditioning on nr_login and avg_movies.

However this method will output a dataframe containing the interventional values of the outcome Churn. That is, the values of the churn variable as if tenure had been changed independent of the specified common causes. If the treatment tenure was discrete, you could have done a simple plot to visualize the effect of different values of tenure. Something like:

Source https://stackoverflow.com/questions/61248565

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

Vulnerabilities

No vulnerabilities reported

Install dowhy

You can install using 'pip install dowhy' or download it from GitHub, PyPI.
You can use dowhy 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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