cleaning up the homework directions

Author: pmaji

README.md

@@ -81,10 +81,10 @@ Below you'll find a brief outline of the content contained in the four sections
 
 ### Homework Exercises
 
-There is a homework exercise associated with these materials, for those interested. 
+There is a homework associated with these materials, for those interested. Given the open-ended nature of the homework, there is no answer key. That said, if you're working through it and would like some feedback, feel free to [reach out to me via Twitter](https://twitter.com/ByPaulJ).
 
-- [Here is the link](https://nbviewer.jupyter.org/github/pmaji/practical-python-data-viz-guide/blob/master/notebooks/participant_hw_nb.ipynb) to the easy-to-view notebook (participant version)
-- [Here is the link](https://github.com/pmaji/practical-python-data-viz-guide/blob/master/notebooks/participant_hw_nb.ipynb) to the GitHub-hosted version of the notebook (participant version)
+[Here is the link](https://nbviewer.jupyter.org/github/pmaji/practical-python-data-viz-guide/blob/master/notebooks/participant_hw_nb.ipynb) to the easy-to-view homework notebook 
+[Here is the link](https://github.com/pmaji/practical-python-data-viz-guide/blob/master/notebooks/participant_hw_nb.ipynb) to the GitHub-hosted version of the homework notebook
 
 ## Setup Instructions
 

notebooks/participant_hw_nb.ipynb

@@ -14,9 +14,9 @@
     "\n",
     "- With each of these questions below, you will be asked to do two things:\n",
     "    1. Construct a visualization to answer the question.\n",
-    "        - You'll be pre-allotted one cell in the notebook for this, but feel free to use as many as you'd like. As was shown in the lecture materials, a good visualization almost always requires iteration. Feel free to keep the remnants of your iterative creative procees in your notebooks; just ensure your final viz. for each question is clearly marked. \n",
+    "        - You'll be pre-allotted one code cell in the notebook for this, but feel free to use as many as you'd like. As was shown in the lecture materials, a good visualization almost always requires iteration. Feel free to keep the remnants of your iterative creative procees in your notebooks; just ensure your final viz. for each question is clearly marked. \n",
     "    2. Briefly explain (in no more than a paragraph) why you chose to visualize the data as you did. \n",
-    "        - If you are struggling to think of what to write, fall back on the lecture materials, particulary Section 1: Why We Visualize. Imagine that each of your visualizations was going to be presented to your team at a Process Confirm / Code Review; your paragraph should read like the explanation you would give in that context, detailing why your choices made for the most effective viz. Be sure to focus on how your visualization answers the question at hand, the crux of which is **in bold** although the entire question provides relevant information as to what is expected.\n",
+    "        - You'll be pre-allotted one markdown cell in the notebook for this, directly following the code cell. If you are struggling to think of what to write, fall back on the lecture materials, particulary Section 1: Why We Visualize. Imagine that each of your visualizations was going to be presented to your team at a Process Confirm / Code Review; your paragraph should read like the explanation you would give in that context, detailing why your choices made for the most effective viz. Be sure to focus on how your visualization answers the question at hand, the crux of which is **in bold** although the entire question provides relevant information as to what is expected.\n",
     "    \n",
     "We'll be using the [same data](https://nbviewer.jupyter.org/github/pmaji/practical-python-data-viz-guide/blob/master/notebooks/data_prep_nb.ipynb) we've been dealing with throughout the seminar: January and December 2017 FNMA originations. Remember, if you don't understand what some of the variables mean, all the information you need is in the `data_prep_nb.ipynb`, including links to relevant glossaries and data dictionnaries.  \n",
     "\n",
@@ -52,7 +52,7 @@
     {
      "data": {
       "text/plain": [
-       "'This notebook was last executed on 2019-08-09 13:07'"
+       "'This notebook was last executed on 2019-09-08 20:42'"
       ]
      },
      "execution_count": 2,
@@ -385,15 +385,6 @@
    "source": [
     "Explanation for why you chose this particular visualization goes here..."
    ]
-  },
-  {
-   "cell_type": "markdown",
-   "metadata": {},
-   "source": [
-    "## Bonus Question\n",
-    "\n",
-    "Maybe a bonus question... depending on what Xi thinks of this existing level of difficulty. "
-   ]
   }
  ],
  "metadata": {