Merge 333136f into c3ff01d

.appveyor.yml

@@ -2,7 +2,7 @@ build: false
 
 environment:
   matrix:
-    - PYTHON_VERSION: 3.5
+    - PYTHON_VERSION: 3.6
       MINICONDA: C:\Miniconda3
 
 init:

.travis.yml

@@ -21,7 +21,7 @@ install:
 script:
     - bash ci/.travis_test.sh
 after_success:
-    - if [[ "${COVERAGE}" == "true" ]]; then coveralls; codecov; else echo "failed"; fi
+    - if [[ "$COVERAGE" == "true" ]]; then coveralls || echo "failed"; fi
 notifications:
     email:
       recipients:

README.md

@@ -6,7 +6,7 @@
 [![PyPI version](https://badge.fury.io/py/mlxtend.svg)](http://badge.fury.io/py/mlxtend)
 [![Coverage Status](https://coveralls.io/repos/rasbt/mlxtend/badge.svg?branch=master&service=github)](https://coveralls.io/github/rasbt/mlxtend?branch=master)
 ![Python 2.7](https://img.shields.io/badge/python-2.7-blue.svg)
-![Python 3.5](https://img.shields.io/badge/python-3.5-blue.svg)
+![Python 3.6](https://img.shields.io/badge/python-3.6-blue.svg)
 ![License](https://img.shields.io/badge/license-BSD-blue.svg)
 [![Join the chat at https://gitter.im/rasbt/mlxtend](https://badges.gitter.im/rasbt/mlxtend.svg)](https://gitter.im/rasbt/mlxtend?utm_source=badge&utm_medium=badge&utm_campaign=pr-badge&utm_content=badge)
 [![](https://zenodo.org/badge/doi/10.5281/zenodo.49235.svg)](https://zenodo.org/record/49235#.VwWISmNh23c)

docs/mkdocs.yml

@@ -32,6 +32,9 @@ pages:
 - Home: index.md
 - User Guide:
   - USER_GUIDE_INDEX.md
+  - frequent_patterns:
+    - user_guide/frequent_patterns/apriori.md
+    - user_guide/frequent_patterns/association_rules.md
   - classifier:
     - user_guide/classifier/EnsembleVoteClassifier.md
     - user_guide/classifier/StackingClassifier.md
@@ -84,8 +87,6 @@ pages:
     - user_guide/data/loadlocal_mnist.md
     - user_guide/data/wine_data.md
     - user_guide/data/three_blobs_data.md
-  - association:
-    - user_guide/association/apriori.md
   - file_io:
     - user_guide/file_io/find_filegroups.md
     - user_guide/file_io/find_files.md
@@ -114,6 +115,7 @@ pages:
     - user_guide/general_concepts/linear-gradient-derivative.md
     - user_guide/general_concepts/regularization-linear.md
 - API:
+  - api_subpackages/mlxtend.frequent_patterns.md
   - api_subpackages/mlxtend.classifier.md
   - api_subpackages/mlxtend.tf_classifier.md
   - api_subpackages/mlxtend.data.md

docs/sources/CHANGELOG.md

@@ -6,11 +6,29 @@ The CHANGELOG for the current development version is available at
 [https://github.com/rasbt/mlxtend/blob/master/docs/sources/CHANGELOG.md](https://github.com/rasbt/mlxtend/blob/master/docs/sources/CHANGELOG.md).
 
 
+### Version 0.6.1 (TBD)
 
-### Version 0.6.0 (TBD)
 
-The CHANGELOG for the current development version is available at
-[https://github.com/rasbt/mlxtend/blob/master/docs/sources/CHANGELOG.md](https://github.com/rasbt/mlxtend/blob/master/docs/sources/CHANGELOG.md).
+##### Downloads
+
+- [Source code (zip)](https://github.com/rasbt/mlxtend/archive/v0.6.1.zip)
+- [Source code (tar.gz)](https://github.com/rasbt/mlxtend/archive/v0.6.1.tar.gz)
+
+##### New Features
+
+- -
+
+##### Changes
+
+- -
+
+##### Bug Fixes
+
+- -
+
+
+### Version 0.6.0 (2017-03-18)
+
 
 ##### Downloads
 
@@ -19,15 +37,17 @@ The CHANGELOG for the current development version is available at
 
 ##### New Features
 
-- -
+- An `association_rules` function is implemented that allows to generate rules based on a list of frequent itemsets (via [Joshua Goerner](https://github.com/JoshuaGoerner)).
 
 ##### Changes
 
 - Adds a black `edgecolor` to plots via `plotting.plot_decision_regions` to make markers more distinguishable from the background in `matplotlib>=2.0`.
+- The `association` submodule was renamed to `frequent_patterns`.
 
 ##### Bug Fixes
 
-- -
+- The `DataFrame` index of `apriori` results are now unique and ordered.
+- Fixed typos in autompg and wine datasets (via [James Bourbeau](https://github.com/jrbourbeau)).
 
 
 ### Version 0.5.1 (2017-02-14)

docs/sources/USER_GUIDE_INDEX.md

@@ -1,5 +1,9 @@
 # User Guide Index
 
+## `frequent_patterns`
+- [apriori](user_guide/frequent_patterns/apriori.md)
+- [association_rules](user_guide/frequent_patterns/association_rules.md)
+
 ## `classifier`
 - [EnsembleVoteClassifier](user_guide/classifier/EnsembleVoteClassifier.md)
 - [StackingClassifier](user_guide/classifier/StackingClassifier.md)
@@ -63,9 +67,6 @@
 - [wine_data](user_guide/data/wine_data.md)
 - [three_blobs_data](user_guide/data/three_blobs_data.md)
 
-## `association`
-- [apriori](user_guide/association/apriori.md)
-
 ## `file_io`
 - [find_filegroups](user_guide/file_io/find_filegroups.md)
 - [find_files](user_guide/file_io/find_files.md)

docs/sources/index.md

@@ -7,7 +7,7 @@
 
 
 ![Python 2.7](https://img.shields.io/badge/python-2.7-blue.svg)
-![Python 3.5](https://img.shields.io/badge/python-3.5-blue.svg)
+![Python 3.6](https://img.shields.io/badge/python-3.6-blue.svg)
 [![License](https://img.shields.io/badge/license-BSD-blue.svg)](./license)
 [![PyPI version](https://badge.fury.io/py/mlxtend.svg)](http://badge.fury.io/py/mlxtend)
 [![Join the chat at https://gitter.im/rasbt/mlxtend](https://badges.gitter.im/rasbt/mlxtend.svg)](https://gitter.im/rasbt/mlxtend?utm_source=badge&utm_medium=badge&utm_campaign=pr-badge&utm_content=badge)

docs/sources/user_guide/data/autompg_data.ipynb

@@ -80,7 +80,7 @@
      "text": [
       "Dimensions: 392 x 8\n",
       "\n",
-      "Header: ['cylinders', 'displacement', 'horsepower weight', 'acceleration', 'model year', 'origin', 'car name']\n",
+      "Header: ['cylinders', 'displacement', 'horsepower', 'weight', 'acceleration', 'model year', 'origin', 'car name']\n",
       "1st row [  8.00000000e+00   3.07000000e+02   1.30000000e+02   3.50400000e+03\n",
       "   1.20000000e+01   7.00000000e+01   1.00000000e+00              nan]\n"
      ]
@@ -92,8 +92,8 @@
     "\n",
     "print('Dimensions: %s x %s' % (X.shape[0], X.shape[1]))\n",
     "print('\\nHeader: %s' % ['cylinders', 'displacement', \n",
-    "                           'horsepower weight', 'acceleration',\n",
-    "                           'model year', 'origin', 'car name'])\n",
+    "                        'horsepower', 'weight', 'acceleration',\n",
+    "                        'model year', 'origin', 'car name'])\n",
     "print('1st row', X[0])"
    ]
   },
@@ -213,7 +213,7 @@
    "name": "python",
    "nbconvert_exporter": "python",
    "pygments_lexer": "ipython3",
-   "version": "3.5.2"
+   "version": "3.6.0"
   }
  },
  "nbformat": 4,

docs/sources/user_guide/data/wine_data.ipynb

@@ -103,7 +103,7 @@
      "text": [
       "Dimensions: 178 x 13\n",
       "\n",
-      "Header: ['sepal length', 'sepal width', 'petal length', 'petal width']\n",
+      "Header: ['alcohol', 'malic acid', 'ash', 'ash alcalinity', 'magnesium', 'total phenols', 'flavanoids', 'nonflavanoid phenols', 'proanthocyanins', 'color intensity', 'hue', 'OD280/OD315 of diluted wines', 'proline']\n",
       "1st row [  1.42300000e+01   1.71000000e+00   2.43000000e+00   1.56000000e+01\n",
       "   1.27000000e+02   2.80000000e+00   3.06000000e+00   2.80000000e-01\n",
       "   2.29000000e+00   5.64000000e+00   1.04000000e+00   3.92000000e+00\n",
@@ -116,8 +116,11 @@
     "X, y = wine_data()\n",
     "\n",
     "print('Dimensions: %s x %s' % (X.shape[0], X.shape[1]))\n",
-    "print('\\nHeader: %s' % ['sepal length', 'sepal width',\n",
-    "                        'petal length', 'petal width'])\n",
+    "print('\\nHeader: %s' % ['alcohol', 'malic acid', 'ash', 'ash alcalinity',\n",
+    "                        'magnesium', 'total phenols', 'flavanoids',\n",
+    "                        'nonflavanoid phenols', 'proanthocyanins',\n",
+    "                        'color intensity', 'hue', 'OD280/OD315 of diluted wines',\n",
+    "                        'proline'])\n",
     "print('1st row', X[0])"
    ]
   },
@@ -228,7 +231,7 @@
    "name": "python",
    "nbconvert_exporter": "python",
    "pygments_lexer": "ipython3",
-   "version": "3.5.2"
+   "version": "3.6.0"
   }
  },
  "nbformat": 4,