fixed execution counts

arrays_strings/group_ordered/group_ordered_challenge.ipynb

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+{
+ "cells": [
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "<small><i>This notebook was prepared by [wdonahoe](https://github.com/wdonahoe). Source and license info is on [GitHub](https://github.com/donnemartin/interactive-coding-challenges).</i></small>"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "# Challenge Notebook"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "## Problem: Implement a function that groups identical items based on their order in the list.\n",
+    "\n",
+    "* [Constraints](#Constraints)\n",
+    "* [Test Cases](#Test-Cases)\n",
+    "* [Algorithm](#Algorithm)\n",
+    "* [Code](#Code)\n",
+    "* [Unit Test](#Unit-Test)\n",
+    "* [Solution Notebook](#Solution-Notebook)"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "## Constraints\n",
+    "\n",
+    "* Can we use extra data structures?\n",
+    "    * Yes"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "## Test Cases\n",
+    "\n",
+    "* group_ordered([1,2,1,3,2])     ->     [1,1,2,2,3]\n",
+    "* group_ordered(['a','b','a')    ->     ['a','a','b']\n",
+    "* group_ordered([1,1,2,3,4,5,2,1]->     [1,1,1,2,2,3,4,5]\n",
+    "* group_ordered([])              ->     []\n",
+    "* group_ordered([1])             ->     [1]\n",
+    "* group_ordered(None)            ->     None"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "## Algorithm\n",
+    "\n",
+    "Refer to the [solution notebook](https://github.com/donnemartin/interactive-coding-challenges/templates/foo_solution.ipynb).  If you are stuck and need a hint, the solution notebook's algorithm discussion might be a good place to start."
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "## Code"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 1,
+   "metadata": {
+    "collapsed": false
+   },
+   "outputs": [],
+   "source": [
+    "def group_ordered(list_in):\n",
+    "    # TODO: Implement me\n",
+    "    pass"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "## Unit Test"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "**The following unit test is expected to fail until you solve the challenge.**"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 2,
+   "metadata": {
+    "collapsed": false
+   },
+   "outputs": [
+   ],
+   "source": [
+    "# %load test_group_ordered.py\n",
+    "from nose.tools import assert_equal\n",
+    "\n",
+    "class TestGroupOrdered(object):\n",
+    "\n",
+    "    def test_group_ordered(self,func):\n",
+    "\n",
+    "        assert_equal(func(None), None)\n",
+    "        assert_equal(func([]), [])\n",
+    "        assert_equal(func([1]), [1])\n",
+    "        assert_equal(func([1,2,1,3,2]),[1,1,2,2,3])\n",
+    "        assert_equal(func(['a','b','a']),['a','a','b'])\n",
+    "        assert_equal(func([1,1,2,3,4,5,2,1]),[1,1,1,2,2,3,4,5])\n",
+    "        assert_equal(func([1,2,3,4,3,4]),[1,2,3,3,4,4])\n",
+    "        print('Success: ' + func.__name__)\n",
+    "\n",
+    "def main():\n",
+    "    test = TestGroupOrdered()\n",
+    "    test.test_group_ordered(group_ordered)\n",
+    "    try:\n",
+    "        test.test_group_ordered(group_ordered_alt)\n",
+    "    except NameError:\n",
+    "        # Alternate solutions are only defined\n",
+    "        # in the solutions file\n",
+    "        pass\n",
+    "\n",
+    "if __name__ == '__main__':\n",
+    "    main()\n"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "## Solution Notebook\n",
+    "\n",
+    "Review the [solution notebook](https://github.com/donnemartin/interactive-coding-challenges/templates/foo_solution.ipynb) for a discussion on algorithms and code solutions."
+   ]
+  }
+ ],
+ "metadata": {
+  "kernelspec": {
+   "display_name": "Python 2",
+   "language": "python",
+   "name": "python2"
+  },
+  "language_info": {
+   "codemirror_mode": {
+    "name": "ipython",
+    "version": 2
+   },
+   "file_extension": ".py",
+   "mimetype": "text/x-python",
+   "name": "python",
+   "nbconvert_exporter": "python",
+   "pygments_lexer": "ipython2",
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