Wheelodex » Projects » ministats

ministats

View on PyPI — Reverse Dependencies (0)

0.3.12 ministats-0.3.12-py2.py3-none-any.whl

Wheel Details

Project: ministats
Version: 0.3.12
Filename: ministats-0.3.12-py2.py3-none-any.whl
Download: [link]
Size: 32326
MD5: dc364cb3e7bc350d077d809627afb134
SHA256: 91ffb70bcc2ede92ee9e6a981a869bff9e59e5aee64f70e9d7b62d9d8c53a1a4
Uploaded: 2024-12-14 00:17:32 +0000

dist-info

METADATA · WHEEL · RECORD · top_level.txt

METADATA

Metadata-Version: 2.1
Name: ministats
Version: 0.3.12
Summary: Common statistical testing procedures used for STATS 101 topics. The code is intentionally simple to make it easy to forllow for beginners.
Author: Ivan Savov
Author-Email: ivan[at]minireference.com
Home-Page: https://github.com/minireference/ministats
License: MIT license
Keywords: ministats
Classifier: Development Status :: 2 - Pre-Alpha
Classifier: Intended Audience :: Developers
Classifier: License :: OSI Approved :: MIT License
Classifier: Natural Language :: English
Classifier: Programming Language :: Python :: 3
Classifier: Programming Language :: Python :: 3.8
Classifier: Programming Language :: Python :: 3.9
Classifier: Programming Language :: Python :: 3.10
Classifier: Programming Language :: Python :: 3.11
Classifier: Programming Language :: Python :: 3.12
Requires-Python: >=3.8
Requires-Dist: matplotlib (>=3.7)
Requires-Dist: numpy (>=1.24)
Requires-Dist: scipy (>=1.6)
Requires-Dist: pandas (>=2)
Requires-Dist: seaborn (>=0.13.2)
Requires-Dist: statsmodels (>=0.14.1)
Requires-Dist: bambi
Requires-Dist: arviz
Description-Content-Type: text/markdown
License-File: LICENSE
[Description omitted; length: 1967 characters]

WHEEL

Wheel-Version: 1.0
Generator: setuptools (74.0.0)
Root-Is-Purelib: true
Tag: py2-none-any
Tag: py3-none-any

RECORD

Path Digest Size
ministats/__init__.py sha256=i4kL1rHhQlDXwF73p_mm0UpE7BrDF8gpjVpkkTLFASY 2125
ministats/bayes.py sha256=Fwb86ag_eVrClpdWgJKw2F_jXTcvmrC77uYmrCl_GRc 11404
ministats/confidence_intervals.py sha256=7szGp9ag8_Az-3YBcowYa78rEXP4ndGwqlYDwwLgMjE 2919
ministats/estimators.py sha256=85mK-dGh9LMtrFWwpQxdjYPU79EWrFlKdQ4qwzfkVgs 1017
ministats/formulas.py sha256=f6d5vSI0j8eceDyBLIjcaWeRjL_bACzf-PRDwq2oEpI 1228
ministats/hypothesis_tests.py sha256=JnphLdPqrm2CGYFBDZe1Q-VpT8zyWCcscRkdIYhnUDc 10049
ministats/linear_models.py sha256=jRK7Buy6NKI9i_KO2ZsaZ8LuWBl9DjCZmXIhg31f56c 515
ministats/probs.py sha256=VOl_Nthe6pYy9kVyR3Ia3Lr7LR6OZ9X2IxJosjzNB68 2869
ministats/sampling.py sha256=5J2-wy8PSLgAahNdSIYp2ncFg5Fm8kd_26w-fAxGLg4 1686
ministats/simulations.py sha256=RQFCLCRY9Km_9a2YvphT0MlXKTltq-W79ZkygsqZxHg 4112
ministats/utils.py sha256=Bsa_N2QcdoYOhn-DjvJ7LOzML72A4W4HQ2sdVglH0kQ 2118
ministats/plots/__init__.py sha256=LTZroIW8VWnkLVtW-1CnHtnX19m_aOdT6NH3dj7QQt4 1049
ministats/plots/cut_material.py sha256=QJpwb-YrnujWaz7DGk-H9GYvAxMw0BFX65Zu2veh3AU 4155
ministats/plots/figures.py sha256=ypGhi2OShmzqzA50ehbb3izucqP9WXd9YWYd8-xMjZk 34919
ministats/plots/probability.py sha256=rA9WLkGIXM6N866S0YxmFpIAvW2UCCmbC9OFIl635YI 4925
ministats/plots/regression.py sha256=yE8nZrGCvVNNGtaKz71TyOI2n6raQvW3KH2BAnm_FYo 9462
ministats-0.3.12.dist-info/LICENSE sha256=8CSDh4u4NDLVDdF6cgPG59U3I_5A1tA0xI4mwpDs2fg 1069
ministats-0.3.12.dist-info/METADATA sha256=bXgvTWHRN-AncbKmJ7u72MdAy2nfKJF9fjx9Wzj7tS4 3108
ministats-0.3.12.dist-info/WHEEL sha256=WDDPHYzpiOIm6GP1C2_8y8W6q16ICddAgOHlhTje9Qc 109
ministats-0.3.12.dist-info/top_level.txt sha256=b5hhv2bgG8AbcOyNd7Y_SCL3NMk46UcAWxk3f7imZVs 10
ministats-0.3.12.dist-info/RECORD — —

top_level.txt

ministats