Virtual Data Mindset v1.3 Python Demo

.gitignore

@@ -0,0 +1,2 @@
+.ipynb_checkpoints/
+.DS_Store

README.md

@@ -3,10 +3,18 @@ A notebook to be used as a python demo in the Data Mindset.
 
 This repo populates the Binder here: [![Binder](https://mybinder.org/badge_logo.svg)](https://mybinder.org/v2/gh/DecodedCo/quandl-python-demo/master)
 
+Note that there are two versions of this demo. 
+
+## v1.2
 Intended use is running the code, then running `data.tail()` and then `data.plot()` in the two empty cells provided.
 
+## v1.3
+Intended use is running the code once through to see the outputs, then run it again for a different Zillow data
+key on Quandl and critiquing the lack of annotation around the methodology used for the FB Prophet model.
+
 ## Prep before delivery:
   1. Run everything in the notebook to make sure it works
   2. Restart kernel and clear all output
   3. Run the first cell and then delete it
-  4. If running through Binder, and not locally, then make sure the Binder kernel is running and active 2 minutes before the demo.
+  4. If running through Binder, and not locally, then make sure the Binder kernel is running and active 2 minutes 
+  before the demo.

.ipynb_checkpoints/quandl-api-demo-checkpoint.ipynb → quandl-api-demo-v-1-2.ipynb

@@ -6,7 +6,7 @@
    "metadata": {},
    "outputs": [],
    "source": [
-    "#PRIOR TO DELIVERY, RUN THIS CELL AND THEN DELETE IT (esc, D, D)\n",
+    "# Configure plotting functions - delete cell before demo (ESC + D + D)\n",
     "%matplotlib inline"
    ]
   },
@@ -16,24 +16,40 @@
    "metadata": {},
    "outputs": [],
    "source": [
+    "# Configure libraries\n",
     "import quandl\n",
-    "quandl.ApiConfig.api_key = \"Byjzu4U8rmR1iEhZnp7V\"\n",
-    "data = quandl.get(\"LPPM/PALL\")"
+    "\n",
+    "# Configure Quandl access\n",
+    "quandl.ApiConfig.api_key = \"Byjzu4U8rmR1iEhZnp7V\""
    ]
   },
   {
    "cell_type": "code",
    "execution_count": null,
    "metadata": {},
    "outputs": [],
-   "source": []
+   "source": [
+    "# Get Data\n",
+    "data = quandl.get(\"FRED/GDP\") # Chelsea, NYC, real estate inventory"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "# Examine data"
+   ]
   },
   {
    "cell_type": "code",
    "execution_count": null,
    "metadata": {},
    "outputs": [],
-   "source": []
+   "source": [
+    "# Plot Data"
+   ]
   }
  ],
  "metadata": {
@@ -52,7 +68,7 @@
    "name": "python",
    "nbconvert_exporter": "python",
    "pygments_lexer": "ipython3",
-   "version": "3.7.0"
+   "version": "3.8.5"
   },
   "varInspector": {
    "cols": {