CrystalBall | Predicting NBA games using statistics | Analytics library

by sidharthrajaram Python Version: Current License: No License

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

kandi X-RAY | CrystalBall Summary

CrystalBall is a Python library typically used in Analytics applications. CrystalBall has no bugs, it has no vulnerabilities and it has low support. However CrystalBall build file is not available. You can download it from GitHub.

Notes for the 2020-2021 Season:.

Support

Quality

Security

License

Reuse

Support

CrystalBall has a low active ecosystem.

It has 5 star(s) with 2 fork(s). There are 2 watchers for this library.

It had no major release in the last 6 months.

There are 0 open issues and 6 have been closed. On average issues are closed in 288 days. There are no pull requests.

It has a neutral sentiment in the developer community.

The latest version of CrystalBall is current.

Quality

CrystalBall has no bugs reported.

Security

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

License

CrystalBall 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

CrystalBall releases are not available. You will need to build from source code and install.

CrystalBall has no build file. You will be need to create the build yourself to build the component from source.

Top functions reviewed by kandi - BETA

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

Simulate a game
Get stats for a team
Get data for team stats
Compute team s team score
Returns a pandas DataFrame containing the team data
Simulate the simulation
Simulate the game
Clean dataframe
Calculate the metric
Plots a list of multiple teams
Returns a list of year numbers
Return the pure game metrics
Get x y coordinates from tuple
Generate training data
Get all teams stats
Calculate the weights for training
Test accuracy of the game
Calculates the performance of the team
Predict predictions for the given weights
Feature scaling factorization
Clean the dataframe
Get statistics for a team

Get all kandi verified functions for this library.

CrystalBall Key Features

No Key Features are available at this moment for CrystalBall.

CrystalBall Examples and Code Snippets

No Code Snippets are available at this moment for CrystalBall.

Community Discussions

Trending Discussions on CrystalBall

Scipy distributions on symfit?

QUESTION

Scipy distributions on symfit?

Asked 2020-Nov-25 at 11:08

I think the title is self explaining.

I really want to use several pdfs already implemented on scipy.stats as models for a symfit model, e.g., CrystalBall or Johnson functions. I have tried with a gaussian distribution with the following code:

...

ANSWER

Answered 2020-Nov-25 at 11:08

It is possible to do this using a CallableNumericalModel:

Source https://stackoverflow.com/questions/64931603

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

Vulnerabilities

No vulnerabilities reported

Install CrystalBall

You can download it from GitHub.
You can use CrystalBall 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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