Updated README.md, shortened the Py2 vs. Py3 section

Author: gumption

Python_for_Data_Science_all.html

@@ -2037,18 +2037,15 @@ <h3 id="A-note-on-Python-2-vs.-Python-3">A note on Python 2 vs. Python 3<a class
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 <p>There are 2 major versions of Python in widespread use: <a href="https://docs.python.org/2/">Python 2</a> and <a href="https://docs.python.org/3/">Python 3</a>. Python 3 has some features that are not backward compatible with Python 2, and some Python 2 libraries have not been updated to work with Python 3. I have been using Python 2, primarily because I use some of those Python 2[-only] libraries, but an increasing proportion of them are migrating to Python 3, and I anticipate shifting to Python 3 in the near future.</p>
-<p>For more on the topic, I recommend a very well documented IPython Notebook, which includes numerous helpful examples and links, by <a href="http://sebastianraschka.com/">Sebastian Raschka</a>, <a href="http://nbviewer.ipython.org/github/rasbt/python_reference/blob/master/tutorials/key_differences_between_python_2_and_3.ipynb">Key differences between Python 2.7.x and Python 3.x</a> ... or <a href="https://www.google.com/q=python%202%20vs%203">googling Python 2 vs 3</a>.</p>
-<p>I received an email request from a Python 3 programmer who suggested that a relatively minor change in this notebook would enable it to run with Python 2 or Python 3: importing the <code>print_function</code> from <a href="https://docs.python.org/2/library/__future__.html"><code>__future__</code></a>, and changing my <a href="https://docs.python.org/2/reference/simple_stmts.html#print"><code>print</code> statements (Python 2)</a> to <a href="https://docs.python.org/3/library/functions.html#print"><code>print</code> function calls (Python 3)</a>. Although a relatively minor conceptual change, it necessitates the changing of many cells to reflect the Python 3 <code>print</code> syntax.</p>
-<p>I find the arguments for <a href="https://www.python.org/dev/peps/pep-3105/">making <code>print</code> a function rather than statement</a> compelling - especially as it is more consistent with printing functionality in many other programming langugages - and so while I do not want to convert this notebook to a Python 3 notebook, I have implemented this change so that it can be used in either Python 2 or Python 3. However, while I have verified that it still works in Python 2, I have not tested it in Python 3.</p>
-<p>I also find the arguments for <a href="https://www.python.org/dev/peps/pep-0238/">changing the division operator</a> compelling, so will import that as well. Without this import in Python 2, <code>1 / 2</code> returns <code>0</code> (the integer portion of the quotient); with this import, <code>1 / 2</code> returns <code>0.5</code>, and if you want only the integer portion of the quotient (<em>floor division</em>), you can use <code>1 // 2</code> (which works the same way in Python 2 and Python 3).</p>
-<p>Note that if you don't understand some/any of the above discussion about Python 2 and Python 3, it should not affect your ability to understand the rest of this notebook.</p>
+<p>For more on the topic, I recommend a very well documented IPython Notebook, which includes numerous helpful examples and links, by <a href="http://sebastianraschka.com/">Sebastian Raschka</a>, <a href="http://nbviewer.ipython.org/github/rasbt/python_reference/blob/master/tutorials/key_differences_between_python_2_and_3.ipynb">Key differences between Python 2.7.x and Python 3.x</a>, the <a href="http://python-future.org/compatible_idioms.html">Cheat Sheet: Writing Python 2-3 compatible code</a> by Ed Schofield ... or <a href="https://www.google.com/q=python%202%20vs%203">googling Python 2 vs 3</a>.</p>
+<p><a href="https://twitter.com/ncoghlan_dev">Nick Coghlan</a>, a CPython core developer, sent me an email suggesting that relatively minor changes in this notebook would enable it to run with Python 2 <em>or</em> Python 3: importing the <code>print_function</code> from the <a href="https://docs.python.org/2/library/__future__.html"><strong><code>__future__</code></strong></a> module, and changing my <a href="https://docs.python.org/2/reference/simple_stmts.html#print"><code>print</code> <em>statements</em> (Python 2)</a> to <a href="https://docs.python.org/3/library/functions.html#print"><code>print</code> <em>function calls</em> (Python 3)</a>. Although a relatively minor conceptual change, it necessitated the changing of many individual cells to reflect the Python 3 <code>print</code> syntax. I also needed to replace a few functions that are no longer available in Python 3 with related functions that are available in both versions; I've added notes in nearby cells where the incompatible functions were removed explaining why they are related ... and no longer available.</p>
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-In&nbsp;[2]:
+In&nbsp;[1]:
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Python_for_Data_Science_all.ipynb

@@ -1,7 +1,7 @@
 {
  "metadata": {
   "name": "",
-  "signature": "sha256:bcca0950b7dac5cf922034044015c39bca27062f58925c71f26294b7f0bfd371"
+  "signature": "sha256:f066be0cc350e6372bbdb872eb18175b0f4453d758f4206d4d337a6a9f7e6fde"
  },
  "nbformat": 3,
  "nbformat_minor": 0,
@@ -350,15 +350,9 @@
      "source": [
       "There are 2 major versions of Python in widespread use: [Python 2](https://docs.python.org/2/) and [Python 3](https://docs.python.org/3/). Python 3 has some features that are not backward compatible with Python 2, and some Python 2 libraries have not been updated to work with Python 3. I have been using Python 2, primarily because I use some of those Python 2[-only] libraries, but an increasing proportion of them are migrating to Python 3, and I anticipate shifting to Python 3 in the near future.\n",
       "\n",
-      "For more on the topic, I recommend a very well documented IPython Notebook, which includes numerous helpful examples and links, by [Sebastian Raschka](http://sebastianraschka.com/), [Key differences between Python 2.7.x and Python 3.x](http://nbviewer.ipython.org/github/rasbt/python_reference/blob/master/tutorials/key_differences_between_python_2_and_3.ipynb) ... or [googling Python 2 vs 3](https://www.google.com/q=python%202%20vs%203).\n",
+      "For more on the topic, I recommend a very well documented IPython Notebook, which includes numerous helpful examples and links, by [Sebastian Raschka](http://sebastianraschka.com/), [Key differences between Python 2.7.x and Python 3.x](http://nbviewer.ipython.org/github/rasbt/python_reference/blob/master/tutorials/key_differences_between_python_2_and_3.ipynb), the [Cheat Sheet: Writing Python 2-3 compatible code](http://python-future.org/compatible_idioms.html) by Ed Schofield ... or [googling Python 2 vs 3](https://www.google.com/q=python%202%20vs%203).\n",
       "\n",
-      "I received an email request from a Python 3 programmer who suggested that a relatively minor change in this notebook would enable it to run with Python 2 or Python 3: importing the `print_function` from [`__future__`](https://docs.python.org/2/library/__future__.html), and changing my [`print` statements (Python 2)](https://docs.python.org/2/reference/simple_stmts.html#print) to [`print` function calls (Python 3)](https://docs.python.org/3/library/functions.html#print). Although a relatively minor conceptual change, it necessitates the changing of many cells to reflect the Python 3 `print` syntax.\n",
-      "\n",
-      "I find the arguments for [making `print` a function rather than statement](https://www.python.org/dev/peps/pep-3105/) compelling - especially as it is more consistent with printing functionality in many other programming langugages - and so while I do not want to convert this notebook to a Python 3 notebook, I have implemented this change so that it can be used in either Python 2 or Python 3. However, while I have verified that it still works in Python 2, I have not tested it in Python 3.\n",
-      "\n",
-      "I also find the arguments for [changing the division operator](https://www.python.org/dev/peps/pep-0238/) compelling, so will import that as well. Without this import in Python 2, `1 / 2` returns `0` (the integer portion of the quotient); with this import, `1 / 2` returns `0.5`, and if you want only the integer portion of the quotient (*floor division*), you can use `1 // 2` (which works the same way in Python 2 and Python 3).\n",
-      "\n",
-      "Note that if you don't understand some/any of the above discussion about Python 2 and Python 3, it should not affect your ability to understand the rest of this notebook."
+      "[Nick Coghlan](https://twitter.com/ncoghlan_dev), a CPython core developer, sent me an email suggesting that relatively minor changes in this notebook would enable it to run with Python 2 *or* Python 3: importing the `print_function` from the  [**`__future__`**](https://docs.python.org/2/library/__future__.html) module, and changing my [`print` *statements* (Python 2)](https://docs.python.org/2/reference/simple_stmts.html#print) to [`print` *function calls* (Python 3)](https://docs.python.org/3/library/functions.html#print). Although a relatively minor conceptual change, it necessitated the changing of many individual cells to reflect the Python 3 `print` syntax. I also needed to replace a few functions that are no longer available in Python 3 with related functions that are available in both versions; I've added notes in nearby cells where the incompatible functions were removed explaining why they are related ... and no longer available."
      ]
     },
     {
@@ -370,7 +364,7 @@
      "language": "python",
      "metadata": {},
      "outputs": [],
-     "prompt_number": 2
+     "prompt_number": 1
     },
     {
      "cell_type": "heading",

README.md

@@ -4,12 +4,12 @@ This short primer on [Python](http://www.python.org/) is designed to provide a r
 
 The primer is spread across a collection of [IPython Notebooks](http://ipython.org/notebook.html), and the easiest way to use the primer is to [install IPython Notebook](http://ipython.org/install.html) on your computer. You can also [install Python](https://www.python.org/downloads/), and manually copy and paste the pieces of sample code into the Python interpreter, as the primer only makes use of the Python standard libraries.
 
-There are three versions of the primer. Two versions contain the entire primer in a single notebook:
+There are three versions of the primer. Two versions are compatible with Python 2 or Python 3), and contain the entire primer in a single notebook:
 
 * Single IPython Notebook: [Python_for_Data_Science_all.ipynb](Python_for_Data_Science_all.ipynb)
 * Single web page (HTML): [Python_for_Data_Science_all.html](Python_for_Data_Science_all.html)
 
-The other version divides the primer into 5 separate notebooks:
+The other version divides the primer into 5 separate notebooks (Python 2 only):
 
 * [Introduction](1_Introduction.ipynb)
 * [Data Science: Basic Concepts](2_Data_Science_Basic_Concepts.ipynb)
@@ -29,11 +29,17 @@ There are also 2 data files, based on the [mushroom dataset](https://archive.ics
 
 ## Change Log
 
+2015-02-23
+
+* Added attribution for suggested changes to accommodate Python 3 to [Nick Coghlan](https://twitter.com/ncoghlan_dev)
+
 2015-02-22
 
 * Added `from __future__ import print_function, division` for Python 3 compatibility
-* Updated `simple_ml.py` to also use Python 3 `print_function` and `division`
-* Changed "call by reference" to "call by sharing"
+* Updated `simple_ml.py` and `SimpleDecisionTree.py` to also use Python 3 `print_function` and `division`
+* Replaced `xrange()` (Python 2 only) with `range()` (Python 2 or 3)
+* Replaced `dict.iteritems()` (Python 2 only) with `dict.items()` (Python 2 or 3)
+* Changed ["call by reference"](https://en.wikipedia.org/wiki/Evaluation_strategy#Call_by_reference) to ["call by sharing"](https://en.wikipedia.org/wiki/Evaluation_strategy#Call_by_sharing)
 * Added `isinstance()` (and reference to duck typing) to section on `type()`
 * Added variable for `delimiter` rather than hard-coding `'|'` character
 * Cleaned up various cells

SimpleDecisionTree.py

@@ -1,3 +1,5 @@
+from __future__ import print_function, division
+
 ''' A class to implement a simple decision tree (based on ID3)
 '''
 
@@ -38,22 +40,22 @@ def _create(self, instances, candidate_attribute_indexes, target_attribute_index
         # If the dataset is empty or the candidate attributes list is empty, return the default value. 
         if not instances or not candidate_attribute_indexes:
             if trace:
-                print '{}Using default class {}'.format('< ' * trace, default_class)
+                print('{}Using default class {}'.format('< ' * trace, default_class))
             return default_class
 
         # If all the instances have the same class label, return that class label
         elif len(class_labels_and_counts) == 1:
             class_label = class_labels_and_counts.most_common(1)[0][0]
             if trace:
-                print '{}All {} instances have label {}'.format('< ' * trace, len(instances), class_label)
+                print('{}All {} instances have label {}'.format('< ' * trace, len(instances), class_label))
             return class_label
         else:
             default_class = simple_ml.majority_value(instances, target_attribute_index)
 
             # Choose the next best attribute index to best classify the instances
             best_index = simple_ml.choose_best_attribute_index(instances, candidate_attribute_indexes, target_attribute_index)
             if trace:
-                print '{}Creating tree node for attribute index {}'.format('> ' * trace, best_index)
+                print('{}Creating tree node for attribute index {}'.format('> ' * trace, best_index))
 
             # Create a new decision tree node with the best attribute index and an empty dictionary object (for now)
             tree = {best_index:{}}
@@ -66,13 +68,13 @@ def _create(self, instances, candidate_attribute_indexes, target_attribute_index
 
             for attribute_value in partitions:
                 if trace:
-                    print '{}Creating subtree for value {} ({}, {}, {}, {})'.format(
+                    print('{}Creating subtree for value {} ({}, {}, {}, {})'.format(
                         '> ' * trace,
                         attribute_value, 
                         len(partitions[attribute_value]), 
                         len(remaining_candidate_attribute_indexes), 
                         target_attribute_index, 
-                        default_class)
+                        default_class))
 
                 # Create a subtree for each value of the the best attribute
                 subtree = self._create(
@@ -99,8 +101,8 @@ def _classify(self, tree, instance, default_class=None):
             return default_class
         if not isinstance(tree, dict):
             return tree
-        attribute_index = tree.keys()[0]
-        attribute_values = tree.values()[0]
+        attribute_index = list(tree.keys())[0]
+        attribute_values = list(tree.values())[0]
         instance_attribute_value = instance[attribute_index]
         if instance_attribute_value not in attribute_values:
             return default_class
@@ -115,7 +117,7 @@ def evaluate_accuracy(self, instances, default_class=None):
         predicted_labels = self.classify_list(instances, default_class)
         actual_labels = [x[0] for x in instances]
         counts = Counter([x == y for x, y in zip(predicted_labels, actual_labels)])
-        return counts[True], counts[False], float(counts[True]) / len(instances)
+        return counts[True], counts[False], counts[True] / len(instances)
 
 
     def pprint(self):