updated docs from rst to markdown

Author: shankarpandala

AUTHORS.md

@@ -0,0 +1,11 @@
+---
+title: Credits
+---
+
+# Development Lead
+
+-   Shankar Rao Pandala \<<[email protected]>\>
+
+# Contributors
+
+-   Breno Batista da Silva \<<[email protected]>\>

AUTHORS.rst

@@ -0,0 +1,65 @@
+---
+title: History
+---
+
+# 0.2.11 (2022-02-06)
+
+-   Updated the default version to 3.9
+
+# 0.2.10 (2022-02-06)
+
+-   Fixed issue with older version of Scikit-learn
+-   Reduced dependencies sctrictly to few
+
+# 0.2.8 (2021-02-06)
+
+-   Removed StackingRegressor and CheckingClassifier.
+-   Added provided_models method.
+-   Added adjusted r-squared metric.
+-   Added cardinality check to split categorical columns into low and
+    high cardinality features.
+-   Added different transformation pipeline for low and high cardinality
+    features.
+-   Included all number dtypes as inputs.
+-   Fixed dependencies.
+-   Improved documentation.
+
+# 0.2.7 (2020-07-09)
+
+-   Removed catboost regressor and classifier
+
+# 0.2.6 (2020-01-22)
+
+-   Added xgboost, lightgbm, catboost regressors and classifiers
+
+# 0.2.5 (2020-01-20)
+
+-   Removed troublesome regressors from list of CLASSIFIERS
+
+# 0.2.4 (2020-01-19)
+
+-   Removed troublesome regressors from list of REGRESSORS
+-   Added feature to input custom metric for evaluation
+-   Added feature to return predictions as dataframe
+-   Added model training time for each model
+
+# 0.2.3 (2019-11-22)
+
+-   Removed TheilSenRegressor from list of REGRESSORS
+-   Removed GaussianProcessClassifier from list of CLASSIFIERS
+
+# 0.2.2 (2019-11-18)
+
+-   Fixed automatic deployment issue.
+
+# 0.2.1 (2019-11-18)
+
+-   Release of Regression feature.
+
+# 0.2.0 (2019-11-17)
+
+-   Release of Classification feature.
+
+# 0.1.0 (2019-11-16)
+
+-   First release on PyPI.

HISTORY.md

@@ -1,53 +1,36 @@
-============
-Lazy Predict
-============
+# Lazy Predict
 
+[![image](https://img.shields.io/pypi/v/lazypredict.svg)](https://pypi.python.org/pypi/lazypredict)
 
-.. image:: https://img.shields.io/pypi/v/lazypredict.svg
-        :target: https://pypi.python.org/pypi/lazypredict
+[![image](https://img.shields.io/travis/shankarpandala/lazypredict.svg)](https://travis-ci.org/shankarpandala/lazypredict)
 
-.. image:: https://img.shields.io/travis/shankarpandala/lazypredict.svg
-        :target: https://travis-ci.org/shankarpandala/lazypredict
+[![Documentation Status](https://readthedocs.org/projects/lazypredict/badge/?version=latest)](https://lazypredict.readthedocs.io/en/latest/?badge=latest)
 
-.. image:: https://readthedocs.org/projects/lazypredict/badge/?version=latest
-        :target: https://lazypredict.readthedocs.io/en/latest/?badge=latest
-        :alt: Documentation Status
+[![Downloads](https://pepy.tech/badge/lazypredict)](https://pepy.tech/project/lazypredict)
 
-.. image:: https://pepy.tech/badge/lazypredict
-     :target: https://pepy.tech/project/lazypredict
-     :alt: Downloads
+[![CodeFactor](https://www.codefactor.io/repository/github/shankarpandala/lazypredict/badge)](https://www.codefactor.io/repository/github/shankarpandala/lazypredict)
 
-.. image:: https://www.codefactor.io/repository/github/shankarpandala/lazypredict/badge
-   :target: https://www.codefactor.io/repository/github/shankarpandala/lazypredict
-   :alt: CodeFactor
+Lazy Predict helps build a lot of basic models without much code and
+helps understand which models works better without any parameter tuning.
 
-Lazy Predict helps build a lot of basic models without much code and helps understand which models works better without any parameter tuning.
+-   Free software: MIT license
+-   Documentation: <https://lazypredict.readthedocs.io>.
 
+# Installation
 
-* Free software: MIT license
-* Documentation: https://lazypredict.readthedocs.io.
-
-============
-Installation
-============
-
-To install Lazy Predict::
+To install Lazy Predict:
 
     pip install lazypredict
 
-=====
-Usage
-=====
+# Usage
 
-To use Lazy Predict in a project::
+To use Lazy Predict in a project:
 
     import lazypredict
 
-==============
-Classification
-==============
+# Classification
 
-Example ::
+Example :
 
     from lazypredict.Supervised import LazyClassifier
     from sklearn.datasets import load_breast_cancer
@@ -97,12 +80,10 @@ Example ::
     | ExtraTreeClassifier            |   0.922807 |            0.912168 |  0.912168 |   0.922462 |    0.0109999 |
     | CheckingClassifier             |   0.361404 |            0.5      |  0.5      |   0.191879 |    0.0170043 |
     | DummyClassifier                |   0.512281 |            0.489598 |  0.489598 |   0.518924 |    0.0119965 |
-    
-==========
-Regression
-==========
 
-Example ::
+# Regression
+
+Example :
 
     from lazypredict.Supervised import LazyRegressor
     from sklearn import datasets
@@ -170,8 +151,3 @@ Example ::
     | KernelRidge                   |             -11.50 |     -8.25 | 22.74 |       0.01 |
 
 
-.. warning::
-    Regression and Classification are replaced with LazyRegressor and LazyClassifier.
-    Regression and Classification classes will be removed in next release
-
-

HISTORY.rst

@@ -43,14 +43,14 @@
 # You can specify multiple suffix as a list of string:
 #
 # source_suffix = ['.rst', '.md']
-source_suffix = ".rst"
+source_suffix = ".md"
 
 # The master toctree document.
 master_doc = "index"
 
 # General information about the project.
 project = u"Lazy Predict"
-copyright = u"2020, Shankar Rao Pandala"
+copyright = u"2022, Shankar Rao Pandala"
 author = u"Shankar Rao Pandala"
 
 # The version info for the project you're documenting, acts as replacement

README.rst README.mdREADME.rst renamed to README.md

@@ -5,10 +5,10 @@
 
 from setuptools import setup, find_packages
 
-with open("README.rst") as readme_file:
+with open("README.md") as readme_file:
     readme = readme_file.read()
 
-with open("HISTORY.rst") as history_file:
+with open("HISTORY.md") as history_file:
     history = history_file.read()
 
 requirements = [requirement for requirement in open('requirements.txt')]
@@ -30,7 +30,13 @@
         "Intended Audience :: Developers",
         "License :: OSI Approved :: MIT License",
         "Natural Language :: English",
+        'Programming Language :: Python :: 3',
+        'Programming Language :: Python :: 3.5',
+        'Programming Language :: Python :: 3.6',
+        'Programming Language :: Python :: 3.7',
+        'Programming Language :: Python :: 3.8',
         "Programming Language :: Python :: 3.9",
+        "Programming Language :: Python :: 3.10",
     ],
     description="Lazy Predict help build a lot of basic models without much code and helps understand which models works better without any parameter tuning",
     long_description_content_type="text/markdown",

docs/conf.py

@@ -1,5 +1,5 @@
 [tox]
-envlist = py36, py37, py38, flake8
+envlist = py36, py37, py38, py39 flake8
 
 [travis]
 python =