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Top 23 Python Statistic Projects
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Project mention: Must-Know 2025 Developer’s Roadmap and Key Programming Trends | dev.to | 2025-02-05
Python’s Growth in Data Work and AI: Python continues to lead because of its easy-to-read style and the huge number of libraries available for tasks from data work to artificial intelligence. Tools like TensorFlow and PyTorch make it a must-have. Whether you’re experienced or just starting, Python’s clear style makes it a good choice for diving into machine learning. Actionable Tip: If you’re new to Python, try projects that combine data with everyday problems. For example, build a simple recommendation system using Pandas and scikit-learn.
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CodeRabbit
CodeRabbit: AI Code Reviews for Developers. Revolutionize your code reviews with AI. CodeRabbit offers PR summaries, code walkthroughs, 1-click suggestions, and AST-based analysis. Boost productivity and code quality across all major languages with each PR.
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ydata-profiling
1 Line of code data quality profiling & exploratory data analysis for Pandas and Spark DataFrames.
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statsmodels is the closest thing in python to R. statsmodels has mixed model support, but mgcv apparently requires more. It is well above my paygrade, but this seems relevant: https://github.com/statsmodels/statsmodels/issues/8029 (i.e. no out of the box support, you might be able to build an approximation on your own).
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boltons
🔩 Like builtins, but boltons. 250+ constructs, recipes, and snippets which extend (and rely on nothing but) the Python standard library. Nothing like Michael Bolton.
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Nutrient
Nutrient - The #1 PDF SDK Library. Bad PDFs = bad UX. Slow load times, broken annotations, clunky UX frustrates users. Nutrient’s PDF SDKs gives seamless document experiences, fast rendering, annotations, real-time collaboration, 100+ features. Used by 10K+ devs, serving ~half a billion users worldwide. Explore the SDK for free.
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uncertainty-baselines
High-quality implementations of standard and SOTA methods on a variety of tasks.
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causal-learn
Causal Discovery in Python. It also includes (conditional) independence tests and score functions.
Project mention: Survey: Integrating Large Language Models in Causal Discovery: A Statistical Causal Approach | dev.to | 2024-05-24 -
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hierarchicalforecast
Probabilistic Hierarchical forecasting 👑 with statistical and econometric methods.
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pytensor
PyTensor allows you to define, optimize, and efficiently evaluate mathematical expressions involving multi-dimensional arrays.
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Contributions-Importer-For-Github
This tool helps users to import contributions to GitHub from private git repositories, or from public repositories that are not hosted in GitHub.
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SaaSHub
SaaSHub - Software Alternatives and Reviews. SaaSHub helps you find the best software and product alternatives
Python Statistics discussion
Python Statistics related posts
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Tea Tasting: Python package for statistical analysis of A/B tests
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tea-tasting VS confidence - a user suggested alternative
2 projects | 16 Aug 2024 -
The Truth About Linear Regression
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Show HN: Aurora – Problem solving focused statistical and ML software toolkit
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How to Build a Logistic Regression Model: A Spam-filter Tutorial
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Frouros: An open-source Python library for drift detection in machine learning
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Ask HN: How to Do a GitHub Wrapped?
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A note from our sponsor - SaaSHub
www.saashub.com | 15 Feb 2025
Index
What are some of the best open-source Statistic projects in Python? This list will help you:
# | Project | Stars |
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1 | scikit-learn | 61,000 |
2 | ydata-profiling | 12,720 |
3 | statsmodels | 10,422 |
4 | imbalanced-learn | 6,915 |
5 | boltons | 6,561 |
6 | Tautulli | 5,785 |
7 | statsforecast | 4,137 |
8 | github-stats | 3,048 |
9 | sweetviz | 2,980 |
10 | eiten | 2,889 |
11 | uncertainty-baselines | 1,480 |
12 | pycm | 1,461 |
13 | geomstats | 1,295 |
14 | causal-learn | 1,273 |
15 | maloja | 1,263 |
16 | hierarchicalforecast | 617 |
17 | sportsipy | 505 |
18 | popmon | 498 |
19 | meteostat-python | 465 |
20 | pypinfo | 427 |
21 | pytensor | 417 |
22 | fitter | 381 |
23 | Contributions-Importer-For-Github | 363 |