Analyze donnemartin/data-science-ipython-notebooks
data-science-ipython-notebooks
Data science Python notebooks: Deep learning (TensorFlow, Theano, Caffe, Keras), scikit-learn, Kaggle, big data (Spark, Hadoop MapReduce, HDFS), matplotlib, pandas, NumPy, SciPy, Python essentials, AWS, and various command lines.Overview
Summary of the overall repo health
Adoption
Metrics on how many people know and interact with the repo
Stars
26,303
Open Issues
36
Forks
7,689
Top 1% by stars on GitHub
Contribution
Top Contributors
Top 10 contributors to the repo and their shares
Commits Properties
Metrics showing the quality of commits distribution
Bus Factor
Serious Ratio
Bus factor is less than 10
Diversity
Geo Distribution
Top locations by number of contributors and commits
Org Distribution
Top organizations contributing to the repo
Governance
Community governance docs check
Description |
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Website |
Code of Conduct |
Contributing.md |
Issue Template |
PR Template |
License |
README |
Less than half checks (3/8)