From 8b75cced6935b56ef4c343cc341d44c605944275 Mon Sep 17 00:00:00 2001
From: Chris Leaman <ckleaman@gmail.com>
Date: Fri, 23 Nov 2018 09:52:14 +1100
Subject: [PATCH] Update notebook

---
 notebooks/01_exploration.ipynb | 1083 ++++++--------------------------
 1 file changed, 181 insertions(+), 902 deletions(-)

diff --git a/notebooks/01_exploration.ipynb b/notebooks/01_exploration.ipynb
index bc63cf3..81e42ab 100644
--- a/notebooks/01_exploration.ipynb
+++ b/notebooks/01_exploration.ipynb
@@ -10,11 +10,11 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 6,
+   "execution_count": 1,
    "metadata": {
     "ExecuteTime": {
-     "end_time": "2018-11-21T05:09:17.883914Z",
-     "start_time": "2018-11-21T05:09:16.981157Z"
+     "end_time": "2018-11-22T22:48:17.973982Z",
+     "start_time": "2018-11-22T22:48:17.825797Z"
     }
    },
    "outputs": [],
@@ -29,11 +29,10 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 61,
+   "execution_count": null,
    "metadata": {
     "ExecuteTime": {
-     "end_time": "2018-11-21T22:54:03.111350Z",
-     "start_time": "2018-11-21T22:54:03.091796Z"
+     "start_time": "2018-11-22T22:48:17.826Z"
     },
     "scrolled": true
    },
@@ -50,34 +49,24 @@
     "import plotly.plotly as py\n",
     "import plotly.tools as tls\n",
     "\n",
+    "import colorlover as cl\n",
+    "\n",
     "from ipywidgets import widgets, Output\n",
-    "from IPython.display import display, clear_output, Image"
+    "from IPython.display import display, clear_output, Image, HTML"
    ]
   },
   {
    "cell_type": "code",
-   "execution_count": 22,
+   "execution_count": null,
    "metadata": {
     "ExecuteTime": {
-     "end_time": "2018-11-21T05:26:30.254784Z",
-     "start_time": "2018-11-21T05:26:13.523566Z"
+     "start_time": "2018-11-22T22:48:17.829Z"
     },
     "pixiedust": {
      "displayParams": {}
     }
    },
-   "outputs": [
-    {
-     "name": "stderr",
-     "output_type": "stream",
-     "text": [
-      "C:\\Users\\z5189959\\AppData\\Local\\Continuum\\anaconda3\\lib\\site-packages\\numpy\\lib\\arraysetops.py:472: FutureWarning:\n",
-      "\n",
-      "elementwise comparison failed; returning scalar instead, but in the future will perform elementwise comparison\n",
-      "\n"
-     ]
-    }
-   ],
+   "outputs": [],
    "source": [
     "def df_from_csv(csv, index_col, data_folder='../data/interim'):\n",
     "    return pd.read_csv(os.path.join(data_folder,csv), index_col=index_col)\n",
@@ -111,216 +100,28 @@
    "execution_count": null,
    "metadata": {
     "ExecuteTime": {
-     "end_time": "2018-11-21T04:02:25.614132Z",
-     "start_time": "2018-11-21T04:02:25.609119Z"
+     "start_time": "2018-11-22T22:48:17.832Z"
     }
    },
    "outputs": [],
-   "source": []
+   "source": [
+    "tables = [Output() for x in range(len(impacts['forecasted']) + 1)]\n",
+    "tables"
+   ]
   },
   {
    "cell_type": "code",
-   "execution_count": 157,
+   "execution_count": null,
    "metadata": {
     "ExecuteTime": {
-     "end_time": "2018-11-22T01:22:23.730687Z",
-     "start_time": "2018-11-22T01:22:19.346920Z"
+     "start_time": "2018-11-22T22:48:17.835Z"
     },
     "code_folding": [
-     335,
-     430
+     408
     ],
     "scrolled": false
    },
-   "outputs": [
-    {
-     "data": {
-      "application/vnd.jupyter.widget-view+json": {
-       "model_id": "237c6a47bf2d418eb98f0ada3a9b00a2",
-       "version_major": 2,
-       "version_minor": 0
-      },
-      "text/html": [
-       "<p>Failed to display Jupyter Widget of type <code>VBox</code>.</p>\n",
-       "<p>\n",
-       "  If you're reading this message in the Jupyter Notebook or JupyterLab Notebook, it may mean\n",
-       "  that the widgets JavaScript is still loading. If this message persists, it\n",
-       "  likely means that the widgets JavaScript library is either not installed or\n",
-       "  not enabled. See the <a href=\"https://ipywidgets.readthedocs.io/en/stable/user_install.html\">Jupyter\n",
-       "  Widgets Documentation</a> for setup instructions.\n",
-       "</p>\n",
-       "<p>\n",
-       "  If you're reading this message in another frontend (for example, a static\n",
-       "  rendering on GitHub or <a href=\"https://nbviewer.jupyter.org/\">NBViewer</a>),\n",
-       "  it may mean that your frontend doesn't currently support widgets.\n",
-       "</p>\n"
-      ],
-      "text/plain": [
-       "VBox(children=(VBox(children=(HTML(value='<b>Filter by observed and predicted impacts:</b>'), HBox(children=(VBox(children=(HTML(value='Observed Impacts'), SelectMultiple(index=(0, 1), options=('swash', 'collision'), value=('swash', 'collision')))), VBox(children=(HTML(value='Forecasted: foreshore_slope_sto06'), SelectMultiple(index=(0, 1, 2), options=('collision', 'swash', 'overwash'), value=('collision', 'swash', 'overwash')))), VBox(children=(HTML(value='Forecasted: mean_slope_sto06'), SelectMultiple(index=(0, 1, 2), options=('collision', 'swash', 'overwash'), value=('collision', 'swash', 'overwash')))))))), VBox(children=(HTML(value='<b>Filter by site_id:</b>'), HBox(children=(Dropdown(description='site_id:   ', index=942, options=('AVOCAn0001', 'AVOCAn0002', 'AVOCAn0003', 'AVOCAn0004', 'AVOCAn0005', 'AVOCAn0006', 'AVOCAn0007', 'AVOCAn0008', 'AVOCAn0009', 'AVOCAs0002', 'AVOCAs0003', 'AVOCAs0004', 'AVOCAs0005', 'AVOCAs0006', 'AVOCAs0007', 'AVOCAs0008', 'BILG0001', 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'NAMB0015', 'NAMB0016', 'NAMB0017', 'NAMB0018', 'NAMB0019', 'NAMB0020', 'NAMB0021', 'NAMB0022', 'NAMB0023', 'NAMB0024', 'NAMB0025', 'NAMB0026', 'NAMB0027', 'NAMB0028', 'NAMB0029', 'NAMB0030', 'NAMB0031', 'NAMB0032', 'NAMB0033', 'NAMB0034', 'NAMB0035', 'NAMB0036', 'NAMB0037', 'NAMB0038', 'NAMB0039', 'NAMB0040', 'NAMB0041', 'NAMB0042', 'NAMB0043', 'NAMB0044', 'NAMB0045', 'NAMB0046', 'NAMB0047', 'NAMB0048', 'NAMB0049', 'NAMB0050', 'NAMB0051', 'NAMB0052', 'NAMB0053', 'NAMB0054', 'NAMB0055', 'NAMB0056', 'NAMB0057', 'NAMB0058', 'NAMB0059', 'NAMB0060', 'NAMB0061', 'NAMB0062', 'NAMB0063', 'NAMB0064', 'NAMB0065', 'NAMB0066', 'NAMB0067', 'NAMB0068', 'NAMB0069', 'NAMB0070', 'NAMB0071', 'NAMB0072', 'NAMB0073', 'NARRA0001', 'NARRA0002', 'NARRA0003', 'NARRA0004', 'NARRA0005', 'NARRA0006', 'NARRA0007', 'NARRA0008', 'NARRA0009', 'NARRA0010', 'NARRA0011', 'NARRA0012', 'NARRA0013', 'NARRA0014', 'NARRA0015', 'NARRA0016', 'NARRA0017', 'NARRA0018', 'NARRA0019', 'NARRA0020', 'NARRA0021', 'NARRA0022', 'NARRA0023', 'NARRA0024', 'NARRA0025', 'NARRA0026', 'NARRA0027', 'NARRA0028', 'NARRA0029', 'NARRA0030', 'NARRA0031', 'NARRA0032', 'NARRA0033', 'NARRA0034', 'NARRA0035', 'NARRA0036', 'NINEMn0001', 'NINEMn0002', 'NINEMn0003', 'NINEMn0004', 'NINEMn0005', 'NINEMn0006', 'NINEMn0007', 'NINEMn0008', 'NINEMn0009', 'NINEMn0010', 'NINEMn0011', 'NINEMn0012', 'NINEMn0013', 'NINEMn0014', 'NINEMn0015', 'NINEMn0016', 'NINEMn0017', 'NINEMn0018', 'NINEMn0019', 'NINEMn0020', 'NINEMn0021', 'NINEMn0022', 'NINEMn0023', 'NINEMn0024', 'NINEMn0025', 'NINEMn0026', 'NINEMn0027', 'NINEMn0028', 'NINEMn0029', 'NINEMn0030', 'NINEMn0031', 'NINEMn0032', 'NINEMn0033', 'NINEMn0034', 'NINEMn0035', 'NINEMn0036', 'NINEMn0037', 'NINEMn0038', 'NINEMn0039', 'NINEMn0040', 'NINEMn0041', 'NINEMn0042', 'NINEMn0043', 'NINEMn0044', 'NINEMn0045', 'NINEMn0046', 'NINEMn0047', 'NINEMn0048', 'NINEMn0049', 'NINEMn0050', 'NINEMn0051', 'NINEMn0052', 'NINEMn0053', 'NINEMn0054', 'NINEMs0001', 'NINEMs0002', 'NINEMs0003', 'NINEMs0004', 'NINEMs0005', 'NINEMs0006', 'NINEMs0007', 'NINEMs0008', 'NINEMs0009', 'NINEMs0010', 'NINEMs0011', 'NINEMs0012', 'NINEMs0013', 'NINEMs0014', 'NINEMs0015', 'NINEMs0016', 'NINEMs0017', 'NINEMs0018', 'NINEMs0019', 'NINEMs0020', 'NINEMs0021', 'NINEMs0022', 'NINEMs0023', 'NINEMs0024', 'NINEMs0025', 'NINEMs0026', 'NINEMs0027', 'NINEMs0028', 'NINEMs0029', 'NINEMs0030', 'NINEMs0031', 'NINEMs0032', 'NINEMs0033', 'NINEMs0034', 'NINEMs0035', 'NINEMs0036', 'NINEMs0037', 'NINEMs0038', 'NINEMs0039', 'NINEMs0040', 'NINEMs0041', 'NINEMs0042', 'NINEMs0043', 'NINEMs0044', 'NINEMs0045', 'NINEMs0046', 'NINEMs0047', 'NINEMs0048', 'NINEMs0049', 'NINEMs0050', 'NINEMs0051', 'NINEMs0052', 'NINEMs0053', 'NINEMs0054', 'NINEMs0055', 'NINEMs0056', 'NINEMs0057', 'NINEMs0058', 'NINEMs0059', 'NINEMs0060', 'NSHORE_n0001', 'NSHORE_n0002', 'NSHORE_n0003', 'NSHORE_n0004', 'NSHORE_n0005', 'NSHORE_n0006', 'NSHORE_n0007', 'NSHORE_n0008', 'NSHORE_n0009', 'NSHORE_n0010', 'NSHORE_n0011', 'NSHORE_n0012', 'NSHORE_n0013', 'NSHORE_n0014', 'NSHORE_n0015', 'NSHORE_n0016', 'NSHORE_n0017', 'NSHORE_n0018', 'NSHORE_n0019', 'NSHORE_n0020', 'NSHORE_n0021', 'NSHORE_n0022', 'NSHORE_n0023', 'NSHORE_n0024', 'NSHORE_n0025', 'NSHORE_n0026', 'NSHORE_n0027', 'NSHORE_n0028', 'NSHORE_n0029', 'NSHORE_n0030', 'NSHORE_n0031', 'NSHORE_n0032', 'NSHORE_n0033', 'NSHORE_n0034', 'NSHORE_n0035', 'NSHORE_n0036', 'NSHORE_n0037', 'NSHORE_n0038', 'NSHORE_n0039', 'NSHORE_n0040', 'NSHORE_n0041', 'NSHORE_n0042', 'NSHORE_n0043', 'NSHORE_n0044', 'NSHORE_n0045', 'NSHORE_n0046', 'NSHORE_n0047', 'NSHORE_n0048', 'NSHORE_n0049', 'NSHORE_n0050', 'NSHORE_n0051', 'NSHORE_n0052', 'NSHORE_n0053', 'NSHORE_n0054', 'NSHORE_n0055', 'NSHORE_n0056', 'NSHORE_n0057', 'NSHORE_n0058', 'NSHORE_n0059', 'NSHORE_n0060', 'NSHORE_n0061', 'NSHORE_n0062', 'NSHORE_n0063', 'NSHORE_n0064', 'NSHORE_n0065', 'NSHORE_n0066', 'NSHORE_n0067', 'NSHORE_n0068', 'NSHORE_n0069', 'NSHORE_n0070', 'NSHORE_n0071', 'NSHORE_n0072', 'NSHORE_n0073', 'NSHORE_n0074', 'NSHORE_n0075', 'NSHORE_n0076', 'NSHORE_n0077', 'NSHORE_n0078', 'NSHORE_n0079', 'NSHORE_n0080', 'NSHORE_n0081', 'NSHORE_n0082', 'NSHORE_s0001', 'NSHORE_s0002', 'NSHORE_s0003', 'NSHORE_s0004', 'NSHORE_s0005', 'NSHORE_s0006', 'NSHORE_s0007', 'NSHORE_s0008', 'NSHORE_s0009', 'NSHORE_s0010', 'NSHORE_s0011', 'NSHORE_s0012', 'NSHORE_s0013', 'NSHORE_s0014', 'NSHORE_s0015', 'NSHORE_s0016', 'NSHORE_s0017', 'NSHORE_s0018', 'NSHORE_s0019', 'NSHORE_s0020', 'NSHORE_s0021', 'NSHORE_s0022', 'NSHORE_s0023', 'NSHORE_s0024', 'NSHORE_s0025', 'NSHORE_s0026', 'NSHORE_s0027', 'NSHORE_s0028', 'NSHORE_s0029', 'NSHORE_s0030', 'NSHORE_s0031', 'NSHORE_s0032', 'NSHORE_s0033', 'NSHORE_s0034', 'NSHORE_s0035', 'NSHORE_s0036', 'NSHORE_s0037', 'NSHORE_s0038', 'NSHORE_s0039', 'NSHORE_s0040', 'NSHORE_s0041', 'NSHORE_s0042', 'NSHORE_s0043', 'NSHORE_s0044', 'OLDBAR0001', 'OLDBAR0002', 'OLDBAR0003', 'OLDBAR0004', 'OLDBAR0005', 'OLDBAR0006', 'OLDBAR0007', 'OLDBAR0008', 'OLDBAR0009', 'OLDBAR0010', 'OLDBAR0011', 'OLDBAR0012', 'OLDBAR0013', 'OLDBAR0014', 'OLDBAR0015', 'OLDBAR0016', 'OLDBAR0017', 'OLDBAR0018', 'OLDBAR0019', 'OLDBAR0020', 'OLDBAR0021', 'OLDBAR0022', 'OLDBAR0023', 'OLDBAR0024', 'OLDBAR0025', 'OLDBAR0026', 'OLDBAR0027', 'OLDBAR0028', 'OLDBAR0029', 'OLDBAR0030', 'OLDBAR0031', 'OLDBAR0032', 'OLDBAR0033', 'OLDBAR0034', 'OLDBAR0035', 'OLDBAR0036', 'ONEMILE0001', 'ONEMILE0002', 'ONEMILE0003', 'ONEMILE0004', 'ONEMILE0005', 'ONEMILE0006', 'ONEMILE0007', 'ONEMILE0008', 'ONEMILE0009', 'ONEMILE0010', 'ONEMILE0011', 'ONEMILE0012', 'ONEMILE0013', 'PEARLn0001', 'PEARLn0002', 'PEARLn0003', 'PEARLn0004', 'PEARLn0005', 'PEARLs0001', 'PEARLs0002', 'PEARLs0003', 'PEARLs0004', 'PEARLs0005', 'SCOT0001', 'SCOT0002', 'SCOT0003', 'SCOT0004', 'SCOT0005', 'SCOT0006', 'SCOT0007', 'SCOT0008', 'SCOT0009', 'SCOT0010', 'SCOT0011', 'SCOT0012', 'STOCNn0001', 'STOCNn0002', 'STOCNn0003', 'STOCNn0004', 'STOCNn0005', 'STOCNn0006', 'STOCNn0007', 'STOCNn0008', 'STOCNn0009', 'STOCNn0010', 'STOCNn0011', 'STOCNn0012', 'STOCNn0013', 'STOCNn0014', 'STOCNn0015', 'STOCNn0016', 'STOCNn0017', 'STOCNn0018', 'STOCNn0019', 'STOCNn0020', 'STOCNn0021', 'STOCNn0022', 'STOCNn0023', 'STOCNn0024', 'STOCNn0025', 'STOCNn0026', 'STOCNn0027', 'STOCNn0028', 'STOCNn0029', 'STOCNn0030', 'STOCNn0031', 'STOCNn0032', 'STOCNn0033', 'STOCNn0034', 'STOCNn0035', 'STOCNn0036', 'STOCNn0037', 'STOCNn0038', 'STOCNn0039', 'STOCNn0040', 'STOCNn0041', 'STOCNn0042', 'STOCNn0043', 'STOCNn0044', 'STOCNn0045', 'STOCNn0046', 'STOCNn0047', 'STOCNn0048', 'STOCNn0049', 'STOCNn0050', 'STOCNn0051', 'STOCNn0052', 'STOCNn0053', 'STOCNn0054', 'STOCNn0055', 'STOCNn0056', 'STOCNn0057', 'STOCNn0058', 'STOCNn0059', 'STOCNn0060', 'STOCNn0061', 'STOCNn0062', 'STOCNn0063', 'STOCNn0064', 'STOCNn0065', 'STOCNs0001', 'STOCNs0002', 'STOCNs0003', 'STOCNs0004', 'STOCNs0005', 'STOCNs0006', 'STOCNs0007', 'STOCNs0008', 'STOCNs0009', 'STOCNs0010', 'STOCNs0011', 'STOCNs0012', 'STOCNs0013', 'STOCNs0014', 'STOCNs0015', 'STOCNs0016', 'STOCNs0017', 'STOCNs0018', 'STOCNs0019', 'STOCNs0020', 'STOCNs0021', 'STOCNs0022', 'STOCNs0023', 'STOCNs0024', 'STOCNs0025', 'STOCNs0026', 'STOCNs0027', 'STOCNs0028', 'STOCNs0029', 'STOCNs0030', 'STOCNs0031', 'STOCNs0032', 'STOCNs0033', 'STOCNs0034', 'STOCNs0035', 'STOCNs0036', 'STOCNs0037', 'STOCNs0038', 'STOCNs0039', 'STOCNs0040', 'STOCNs0041', 'STOCNs0042', 'STOCNs0043', 'STOCNs0044', 'STOCNs0045', 'STOCNs0046', 'STOCNs0047', 'STOCNs0048', 'STOCNs0049', 'STOCNs0050', 'STOCNs0051', 'STOCNs0052', 'STOCNs0053', 'STOCNs0054', 'STOCNs0055', 'STOCNs0056', 'STOCNs0057', 'STOCNs0058', 'STOCNs0059', 'STOCNs0060', 'STOCNs0061', 'STOCNs0062', 'STOCNs0063', 'STOCNs0064', 'STOCNs0065', 'STOCNs0066', 'STOCNs0067', 'STOCNs0068', 'STOCNs0069', 'STOCNs0070', 'STOCNs0071', 'STOCNs0072', 'STOCNs0073', 'STOCNs0074', 'STOCNs0075', 'STOCNs0076', 'STOCNs0077', 'STOCNs0078', 'STOCNs0079', 'STOCNs0080', 'STOCNs0081', 'STOCNs0082', 'STOCNs0083', 'STOCNs0084', 'STOCNs0085', 'STOCNs0086', 'STOCNs0087', 'STOCNs0088', 'STOCNs0089', 'STOCNs0090', 'STOCNs0091', 'STOCNs0092', 'STOCNs0093', 'STOCNs0094', 'STOCNs0095', 'STOCNs0096', 'STOCNs0097', 'STOCNs0098', 'STOCNs0099', 'STOCNs0100', 'STOCNs0101', 'STOCNs0102', 'STOCNs0103', 'STOCNs0104', 'STOCNs0105', 'STOCNs0106', 'STOCNs0107', 'STOCNs0108', 'STOCNs0109', 'STOCNs0110', 'STOCNs0111', 'STOCNs0112', 'STOCNs0113', 'STOCNs0114', 'STOCNs0115', 'STOCNs0116', 'STOCNs0117', 'STOCNs0118', 'STOCNs0119', 'STOCNs0120', 'STOCNs0121', 'STOCNs0122', 'STOCNs0123', 'STOCNs0124', 'STOCNs0125', 'STOCNs0126', 'STOCNs0127', 'STOCNs0128', 'STOCNs0129', 'STOCNs0130', 'STOCNs0131', 'STOCNs0132', 'STOCNs0133', 'STOCNs0134', 'STOCNs0135', 'STOCNs0136', 'STOCNs0137', 'STOCNs0138', 'STOCNs0139', 'STOCNs0140', 'STOCNs0141', 'STOCNs0142', 'STOCNs0143', 'STOCNs0144', 'STOCNs0145', 'STOCNs0146', 'STOCNs0147', 'STOCNs0148', 'STOCNs0149', 'STOCNs0150', 'STOCNs0151', 'STOCNs0152', 'STOCNs0153', 'STOCNs0154', 'STOCNs0155', 'STOCNs0156', 'STOCNs0157', 'STOCNs0158', 'STOCNs0159', 'STOCNs0160', 'STOCNs0161', 'STOCNs0162', 'STOCNs0163', 'STOCNs0164', 'STOCNs0165', 'STOCNs0166', 'STOCNs0167', 'STOCNs0168', 'STOCNs0169', 'STOCNs0170', 'STOCNs0171', 'STOCNs0172', 'STOCNs0173', 'STOCNs0174', 'STOCNs0175', 'STOCNs0176', 'STOCNs0177', 'STOCNs0178', 'STOCNs0179', 'STOCNs0180', 'STOCNs0181', 'STOCNs0182', 'STOCNs0183', 'STOCNs0184', 'STOCNs0185', 'STOCNs0186', 'STOCNs0187', 'STOCNs0188', 'STOCNs0189', 'STOCNs0190', 'STOCNs0191', 'STOCNs0192', 'STOCNs0193', 'STOCNs0194', 'STOCNs0195', 'STOCNs0196', 'STOCNs0197', 'STOCNs0198', 'STOCNs0199', 'STOCNs0200', 'STOCNs0201', 'STOCNs0202', 'STOCNs0203', 'STOCNs0204', 'STOCNs0205', 'STOCNs0206', 'STOCNs0207', 'STOCNs0208', 'STOCNs0209', 'STOCS0001', 'STOCS0002', 'STOCS0003', 'STOCS0004', 'STOCS0005', 'STOCS0006', 'STOCS0007', 'STOCS0008', 'STOCS0009', 'STOCS0010', 'STOCS0011', 'STOCS0012', 'STOCS0013', 'STOCS0014', 'STOCS0015', 'STOCS0016', 'STOCS0017', 'STOCS0018', 'STOCS0019', 'STOCS0020', 'STOCS0021', 'STOCS0022', 'STOCS0023', 'STOCS0024', 'STOCS0025', 'STOCS0026', 'STOCS0027', 'STOCS0028', 'STOCS0029', 'STOCS0030', 'STOCS0031', 'STOCS0032', 'STOCS0033', 'STOCS0034', 'STOCS0035', 'STOCS0036', 'STOCS0037', 'STOCS0038', 'STOCS0039', 'STOCS0040', 'STOCS0041', 'STOCS0042', 'STOCS0043', 'STOCS0044', 'STOCS0045', 'STOCS0046', 'STUART0001', 'STUART0002', 'STUART0003', 'STUART0004', 'STUART0005', 'STUART0006', 'STUART0007', 'STUART0008', 'STUART0009', 'STUART0010', 'STUART0011', 'STUART0012', 'STUART0013', 'STUART0014', 'STUART0015', 'STUART0016', 'STUART0017', 'STUART0018', 'STUART0019', 'STUART0020', 'STUART0021', 'STUART0022', 'STUART0023', 'STUART0024', 'STUART0025', 'STUART0026', 'STUART0027', 'STUART0028', 'STUART0029', 'STUART0030', 'STUART0031', 'STUART0032', 'STUART0033', 'STUART0034', 'STUART0035', 'STUART0036', 'STUART0037', 'STUART0038', 'STUART0039', 'STUART0040', 'STUART0041', 'STUART0042', 'STUART0043', 'STUART0044', 'STUART0045', 'STUART0046', 'STUART0047', 'STUART0048', 'STUART0049', 'STUART0050', 'STUART0051', 'STUART0052', 'STUART0053', 'STUART0054', 'STUART0055', 'STUART0056', 'STUART0057', 'STUART0058', 'STUART0059', 'STUART0060', 'STUART0061', 'STUART0062', 'STUART0063', 'STUART0064', 'STUART0065', 'STUART0066', 'STUART0067', 'STUART0068', 'STUART0069', 'STUART0070', 'STUART0071', 'STUART0072', 'STUART0073', 'STUART0074', 'STUART0075', 'STUART0076', 'STUART0077', 'STUART0078', 'STUART0079', 'STUART0080', 'STUART0081', 'STUART0082', 'STUART0083', 'STUART0084', 'STUART0085', 'STUART0086', 'STUART0087', 'STUART0088', 'STUART0089', 'SWRO0001', 'SWRO0002', 'SWRO0003', 'SWRO0004', 'SWRO0005', 'SWRO0006', 'SWRO0007', 'SWRO0008', 'SWRO0009', 'SWRO0010', 'SWRO0011', 'SWRO0012', 'SWRO0013', 'SWRO0014', 'SWRO0015', 'SWRO0016', 'SWRO0017', 'SWRO0018', 'SWRO0019', 'SWRO0020', 'SWRO0021', 'SWRO0022', 'SWRO0023', 'SWRO0024', 'SWRO0025', 'SWRO0026', 'TREACH0001', 'TREACH0002', 'TREACH0003', 'TREACH0004', 'TREACH0005', 'TREACH0006', 'TREACH0007', 'TREACH0008', 'TREACH0009', 'TREACH0010', 'TREACH0011', 'TREACH0012', 'TREACH0013', 'TREACH0014', 'TREACH0015', 'TREACH0016', 'WAMBE0001', 'WAMBE0002', 'WAMBE0003', 'WAMBE0004', 'WAMBE0005', 'WAMBE0006', 'WAMBE0007', 'WAMBE0008', 'WAMBE0009', 'WAMBE0010', 'WAMBE0011', 'WAMBE0012', 'WAMBE0013', 'WAMBE0014', 'WAMBE0015', 'WAMBE0016', 'WAMBE0017', 'WAMBE0018', 'WAMBE0019', 'WAMBE0020', 'WAMBE0021', 'WAMBE0022', 'WAMBE0023', 'WAMBE0024', 'WAMBE0025', 'WAMBE0026', 'WAMBE0027'), value='NARRA0001'),)))), HBox(children=(FigureWidget({\n",
-       "    'data': [{'name': 'Pre Storm Profile',\n",
-       "              'type': 'scatter',\n",
-       "              'uid': '534bf20e-d5c0-49b0-8f3a-247fc1db8b29',\n",
-       "              'x': [0],\n",
-       "              'y': [0]},\n",
-       "             {'name': 'Post Storm Profile',\n",
-       "              'type': 'scatter',\n",
-       "              'uid': '4da21238-7eab-464a-94e3-374d731a3797',\n",
-       "              'x': [0],\n",
-       "              'y': [0]},\n",
-       "             {'marker': {'color': 'rgb(17, 157, 255)', 'size': 20},\n",
-       "              'mode': 'markers',\n",
-       "              'name': 'Pre-storm dune crest',\n",
-       "              'type': 'scatter',\n",
-       "              'uid': '1bcb6e22-4d7a-487d-a63f-23086513084e',\n",
-       "              'x': [0],\n",
-       "              'y': [0]},\n",
-       "             {'marker': {'color': 'rgb(231, 99, 250)', 'size': 20},\n",
-       "              'mode': 'markers',\n",
-       "              'name': 'Pre-storm dune toe',\n",
-       "              'type': 'scatter',\n",
-       "              'uid': '39507d76-af86-4685-812d-03a96960aac9',\n",
-       "              'x': [0],\n",
-       "              'y': [0]},\n",
-       "             {'name': 'Peak R_high: foreshore_slope_sto06',\n",
-       "              'type': 'scatter',\n",
-       "              'uid': '64fa5f96-580e-4188-a9f1-95a453763277',\n",
-       "              'x': [0],\n",
-       "              'y': [0]},\n",
-       "             {'name': 'Peak R_high: mean_slope_sto06',\n",
-       "              'type': 'scatter',\n",
-       "              'uid': '65603ac3-721e-428a-8dc3-c94a500fdeeb',\n",
-       "              'x': [0],\n",
-       "              'y': [0]}],\n",
-       "    'layout': {'height': 300,\n",
-       "               'legend': {'font': {'size': 10}},\n",
-       "               'margin': {'b': 50, 'l': 50, 'r': 20, 't': 50},\n",
-       "               'title': 'Bed Profiles',\n",
-       "               'xaxis': {'autorange': True,\n",
-       "                         'range': [0, 200],\n",
-       "                         'showgrid': True,\n",
-       "                         'showline': True,\n",
-       "                         'title': 'x (m)',\n",
-       "                         'zeroline': True},\n",
-       "               'yaxis': {'autorange': False,\n",
-       "                         'range': [-1, 20],\n",
-       "                         'showgrid': True,\n",
-       "                         'showline': True,\n",
-       "                         'title': 'z (m)',\n",
-       "                         'zeroline': True}}\n",
-       "}), FigureWidget({\n",
-       "    'data': [{'lat': array([-33.46381539, -33.46301835, -33.46221051, ..., -33.4279646 ,\n",
-       "                            -33.42732743, -33.42671036]),\n",
-       "              'lon': array([151.43639576, 151.43690633, 151.43738179, ..., 151.4501613 ,\n",
-       "                            151.45092222, 151.45170635]),\n",
-       "              'marker': {'size': 10},\n",
-       "              'mode': 'markers',\n",
-       "              'text': array(['AVOCAn0001', 'AVOCAn0002', 'AVOCAn0003', ..., 'WAMBE0025', 'WAMBE0026',\n",
-       "                             'WAMBE0027'], dtype='<U12'),\n",
-       "              'type': 'scattermapbox',\n",
-       "              'uid': '720a5f74-bc05-49b6-b51b-4e74cac7daa5'},\n",
-       "             {'lat': [0],\n",
-       "              'lon': [0],\n",
-       "              'marker': {'color': 'rgb(255, 0, 0)', 'opacity': 0.5, 'size': 20},\n",
-       "              'mode': 'markers',\n",
-       "              'text': array(['AVOCAn0001', 'AVOCAn0002', 'AVOCAn0003', ..., 'WAMBE0025', 'WAMBE0026',\n",
-       "                             'WAMBE0027'], dtype='<U12'),\n",
-       "              'type': 'scattermapbox',\n",
-       "              'uid': '0e82aed9-9e6d-4f64-943d-ca50e6ed969a'}],\n",
-       "    'layout': {'autosize': True,\n",
-       "               'height': 300,\n",
-       "               'hovermode': 'closest',\n",
-       "               'mapbox': {'accesstoken': ('pk.eyJ1IjoiY2hyaXNsZWFtYW4iLCJ' ... 'Hp5bCJ9.U2dwFg2c7RFjUNSayERUiw'),\n",
-       "                          'bearing': 0,\n",
-       "                          'center': {'lat': -33.7, 'lon': 151.3},\n",
-       "                          'pitch': 0,\n",
-       "                          'style': 'satellite-streets',\n",
-       "                          'zoom': 12},\n",
-       "               'margin': {'b': 50, 'l': 20, 'r': 20, 't': 50},\n",
-       "               'showlegend': False}\n",
-       "}))), FigureWidget({\n",
-       "    'data': [{'name': 'Hs0',\n",
-       "              'type': 'scatter',\n",
-       "              'uid': '3874e39b-7385-439e-9e76-081e7f561bce',\n",
-       "              'x': [0, 1],\n",
-       "              'xaxis': 'x',\n",
-       "              'y': [0, 1],\n",
-       "              'yaxis': 'y3'},\n",
-       "             {'name': 'Tp',\n",
-       "              'type': 'scatter',\n",
-       "              'uid': 'b5524288-8511-4637-8809-e250c19632cd',\n",
-       "              'x': [0, 1],\n",
-       "              'xaxis': 'x',\n",
-       "              'y': [0, 1],\n",
-       "              'yaxis': 'y4'},\n",
-       "             {'line': {'color': 'rgb(214, 117, 14)', 'dash': 'dot', 'width': 2},\n",
-       "              'name': 'Dune Crest',\n",
-       "              'type': 'scatter',\n",
-       "              'uid': '7d73e127-8d68-40fd-9706-ef36e2c44c7e',\n",
-       "              'x': [0, 3],\n",
-       "              'xaxis': 'x',\n",
-       "              'y': [0, 3],\n",
-       "              'yaxis': 'y'},\n",
-       "             {'line': {'color': 'rgb(142, 77, 8)', 'dash': 'dash', 'width': 2},\n",
-       "              'name': 'Dune Toe',\n",
-       "              'type': 'scatter',\n",
-       "              'uid': '310c278c-c789-4d86-b0bf-9e2fb13069df',\n",
-       "              'x': [0, 3],\n",
-       "              'xaxis': 'x',\n",
-       "              'y': [0, 3],\n",
-       "              'yaxis': 'y'},\n",
-       "             {'line': {'color': 'rgb(8,51,137)', 'dash': 'dot', 'width': 2},\n",
-       "              'name': 'Tide+Surge WL',\n",
-       "              'type': 'scatter',\n",
-       "              'uid': 'cf813ce8-08ab-4161-b061-a58831e1e791',\n",
-       "              'x': [0, 3],\n",
-       "              'xaxis': 'x',\n",
-       "              'y': [0, 3],\n",
-       "              'yaxis': 'y'},\n",
-       "             {'name': 'R_high: foreshore_slope_sto06',\n",
-       "              'type': 'scatter',\n",
-       "              'uid': '83f5fd55-57c0-46ce-8995-d8060c3efaca',\n",
-       "              'x': [0],\n",
-       "              'xaxis': 'x',\n",
-       "              'y': [0],\n",
-       "              'yaxis': 'y'},\n",
-       "             {'name': 'R_high: mean_slope_sto06',\n",
-       "              'type': 'scatter',\n",
-       "              'uid': 'e3cc6a4a-9b0c-4ddb-bb9b-c828ae070110',\n",
-       "              'x': [0],\n",
-       "              'xaxis': 'x',\n",
-       "              'y': [0],\n",
-       "              'yaxis': 'y'},\n",
-       "             {'name': 'Beta: foreshore_slope_sto06',\n",
-       "              'type': 'scatter',\n",
-       "              'uid': 'f0c515dd-1486-4183-8f68-5db67af509f0',\n",
-       "              'x': [0, 1],\n",
-       "              'xaxis': 'x',\n",
-       "              'y': [0, 1],\n",
-       "              'yaxis': 'y2'},\n",
-       "             {'name': 'Beta: mean_slope_sto06',\n",
-       "              'type': 'scatter',\n",
-       "              'uid': '4a2ab660-297c-44ab-9a59-2b1dc60cf2df',\n",
-       "              'x': [0, 1],\n",
-       "              'xaxis': 'x',\n",
-       "              'y': [0, 1],\n",
-       "              'yaxis': 'y2'}],\n",
-       "    'layout': {'height': 500,\n",
-       "               'margin': {'b': 50, 'l': 50, 'r': 20, 't': 20},\n",
-       "               'xaxis': {'anchor': 'y3', 'domain': [0.0, 1.0], 'title': 'datetime'},\n",
-       "               'yaxis': {'anchor': 'free', 'domain': [0.7333333333333333, 1.0], 'position': 0.0, 'title': 'z (mAHD)'},\n",
-       "               'yaxis2': {'anchor': 'free',\n",
-       "                          'domain': [0.36666666666666664, 0.6333333333333333],\n",
-       "                          'position': 0.0,\n",
-       "                          'title': 'beta (-)'},\n",
-       "               'yaxis3': {'anchor': 'x', 'domain': [0.0, 0.26666666666666666], 'title': 'Hs0 (m)'},\n",
-       "               'yaxis4': {'overlaying': 'y3', 'side': 'right', 'title': 'Tp (s)'}}\n",
-       "})))"
-      ]
-     },
-     "metadata": {},
-     "output_type": "display_data"
-    }
-   ],
+   "outputs": [],
    "source": [
     "# Create widgets for filtering by observed and forecasted impacts\n",
     "filter_title = widgets.HTML(\n",
@@ -362,20 +163,38 @@
     "    options=df_profiles.index.get_level_values(\n",
     "        'site_id').unique().sort_values().tolist()\n",
     ")\n",
-    "site_id_container = widgets.VBox(\n",
-    "    children=[site_id_title, widgets.HBox(children=[site_id_select])])\n",
+    "\n",
+    "site_id_impacts = widgets.HTML(\n",
+    "    value=\"\",\n",
+    ")\n",
+    "\n",
+    "site_id_container = widgets.HBox(children=[\n",
+    "    widgets.VBox(children=[site_id_title, widgets.HBox(children=[site_id_select])]),\n",
+    "    site_id_impacts\n",
+    "])\n",
+    "\n",
     "\n",
     "\n",
+    "\n",
+    "# Build colors for each of our forecasts\n",
+    "colors = list(reversed(cl.scales[str(max(len(impacts['forecasted']), 3))]['seq']['YlGnBu']))\n",
+    "\n",
     "# Add panel for pre/post storm profiles\n",
     "trace1 = go.Scatter(\n",
     "    x=[0],\n",
     "    y=[0],\n",
-    "    name='Pre Storm Profile'\n",
+    "    name='Pre Storm Profile',\n",
+    "    line=dict(\n",
+    "        color=('rgb(51,160,44)'),\n",
+    "        width=2)\n",
     ")\n",
     "trace2 = go.Scatter(\n",
     "    x=[0],\n",
     "    y=[0],\n",
-    "    name='Post Storm Profile'\n",
+    "    name='Post Storm Profile',\n",
+    "    line=dict(\n",
+    "        color=('rgb(255,127,0)'),\n",
+    "        width=2)\n",
     ")\n",
     "trace3 = go.Scatter(\n",
     "    x=[0],\n",
@@ -383,8 +202,12 @@
     "    name='Pre-storm dune crest',\n",
     "    mode='markers',\n",
     "    marker=dict(\n",
-    "        color='rgb(17, 157, 255)',\n",
-    "        size=20,\n",
+    "        color='rgba(255,255,255,0)',\n",
+    "        size=10,\n",
+    "        line=dict(\n",
+    "            color='rgba(106,61,154, 1)',\n",
+    "            width=2\n",
+    "        )\n",
     "    ),\n",
     ")\n",
     "trace4 = go.Scatter(\n",
@@ -393,17 +216,26 @@
     "    name='Pre-storm dune toe',\n",
     "    mode='markers',\n",
     "    marker=dict(\n",
-    "        color='rgb(231, 99, 250)',\n",
-    "        size=20,\n",
+    "        color='rgba(255,255,255,0)',\n",
+    "        size=10,\n",
+    "        line=dict(\n",
+    "            color='rgba(202,178,214,1)',\n",
+    "            width=2\n",
+    "        )\n",
     "    ),\n",
     ")\n",
     "\n",
     "forecast_traces = []\n",
-    "for forecast in impacts['forecasted']:\n",
+    "for forecast, color in zip(impacts['forecasted'], colors):\n",
     "    forecast_traces.append(go.Scatter(\n",
     "        x=[0],\n",
     "        y=[0],\n",
-    "        name='Peak R_high: {}'.format(forecast)\n",
+    "        name='Peak R_high: {}'.format(forecast),\n",
+    "        mode='lines',\n",
+    "        line=dict(\n",
+    "            color=color,\n",
+    "            width=4,)\n",
+    "\n",
     "    ))\n",
     "\n",
     "layout = go.Layout(\n",
@@ -482,12 +314,6 @@
     "g_map = go.FigureWidget(data=data, layout=layout)\n",
     "\n",
     "\n",
-    "\n",
-    "#################\n",
-    "# NEW\n",
-    "#################\n",
-    "\n",
-    "\n",
     "subplot = tls.make_subplots(3, 1, print_grid=False, shared_xaxes=True)\n",
     "g_timeseries = go.FigureWidget(subplot)\n",
     "\n",
@@ -516,61 +342,69 @@
     "# Add water levels\n",
     "g_timeseries.add_trace(\n",
     "    go.Scatter(\n",
-    "    x = [0,3],\n",
-    "    y = [0,3],\n",
-    "    name='Dune Crest',\n",
-    "    line = dict(\n",
-    "        color = ('rgb(214, 117, 14)'),\n",
-    "        width = 2,\n",
-    "        dash = 'dot')\n",
-    "), row=1, col=1)\n",
+    "        x=[0, 3],\n",
+    "        y=[0, 3],\n",
+    "        name='Dune Crest',\n",
+    "        mode='lines',\n",
+    "        line=dict(\n",
+    "            color=('rgb(214, 117, 14)'),\n",
+    "            width=2,\n",
+    "            dash='dot')\n",
+    "    ), row=1, col=1)\n",
     "\n",
     "\n",
     "g_timeseries.add_trace(\n",
     "    go.Scatter(\n",
-    "    x = [0,3],\n",
-    "    y = [0,3],\n",
-    "    name='Dune Toe',\n",
-    "    line = dict(\n",
-    "        color = ('rgb(142, 77, 8)'),\n",
-    "        width = 2,\n",
-    "        dash = 'dash')\n",
-    "), row=1, col=1)\n",
+    "        x=[0, 3],\n",
+    "        y=[0, 3],\n",
+    "        name='Dune Toe',\n",
+    "        mode='lines',\n",
+    "        line=dict(\n",
+    "            color=('rgb(142, 77, 8)'),\n",
+    "            width=2,\n",
+    "            dash='dash')\n",
+    "    ), row=1, col=1)\n",
     "\n",
     "g_timeseries.add_trace(\n",
     "    go.Scatter(\n",
-    "    x = [0,3],\n",
-    "    y = [0,3],\n",
-    "    name='Tide+Surge WL',\n",
-    "    line = dict(\n",
-    "        color = ('rgb(8,51,137)'),\n",
-    "        width = 2,\n",
-    "        dash = 'dot')\n",
-    "), row=1, col=1)\n",
-    "\n",
-    "for forecast in twls['forecasted']:\n",
+    "        x=[0, 3],\n",
+    "        y=[0, 3],\n",
+    "        name='Tide+Surge WL',\n",
+    "        line=dict(\n",
+    "            color=('rgb(8,51,137)'),\n",
+    "            width=2,\n",
+    "            dash='dot')\n",
+    "    ), row=1, col=1)\n",
+    "\n",
+    "for forecast, color in zip(twls['forecasted'], colors):\n",
     "    g_timeseries.add_trace(\n",
-    "    go.Scatter(\n",
-    "    x=[0],\n",
-    "    y=[0],\n",
-    "    name = 'R_high: {}'.format(forecast)), row=1, col=1)\n",
+    "        go.Scatter(\n",
+    "            x=[0],\n",
+    "            y=[0],\n",
+    "            name='R_high: {}'.format(forecast),\n",
+    "            line=dict(\n",
+    "                color=color,\n",
+    "                width=3)), row=1, col=1)\n",
     "\n",
     "\n",
     "# Add trace for each forecasted beta term\n",
-    "for n, forecast in enumerate(impacts['forecasted']):\n",
+    "for forecast, color in zip(impacts['forecasted'],colors):\n",
     "    g_timeseries.add_trace(\n",
     "        go.Scatter(\n",
-    "            x=[0,1],\n",
-    "            y=[0,1],\n",
-    "            name='Beta: {}'.format(forecast)),\n",
+    "            x=[0, 1],\n",
+    "            y=[0, 1],\n",
+    "            name='Beta: {}'.format(forecast),\n",
+    "                    line=dict(\n",
+    "                color=color,\n",
+    "                width=3)),\n",
     "        row=2,\n",
     "        col=1,\n",
     "    )\n",
-    "    \n",
+    "\n",
     "\n",
     "# Create axis for Tp on same plot as Hs\n",
-    "g_timeseries['layout']['yaxis4'] = {'overlaying': 'y3', 'side':'right'}\n",
-    "g_timeseries.data[1]['yaxis']='y4'\n",
+    "g_timeseries['layout']['yaxis4'] = {'overlaying': 'y3', 'side': 'right'}\n",
+    "g_timeseries.data[1]['yaxis'] = 'y4'\n",
     "\n",
     "# Add labels to each axis\n",
     "g_timeseries.layout['xaxis']['title'] = 'datetime'\n",
@@ -580,170 +414,36 @@
     "g_timeseries.layout['yaxis4']['title'] = 'Tp (s)'\n",
     "\n",
     "# Update figure size\n",
-    "g_timeseries['layout'].update(height=500)\n",
-    "g_timeseries['layout'].update(margin=dict(t=20,l=50,r=20,b=50))\n",
+    "g_timeseries['layout'].update(height=400, legend=dict(font={'size': 10}))\n",
+    "g_timeseries['layout'].update(margin=dict(t=20, l=50, r=20, b=100))\n",
     "\n",
-    "# g_timeseries['layout']['xaxis'] = {'title':'time'}\n",
     "\n",
-    "# #     g_timeseries.data[2+n]['yaxis'] = 'y4'\n",
     "\n",
-    "# g_timeseries['layout']['xaxis'] = {'title':'time'}\n",
+    "# Add panel for some tables\n",
+    "titles = ['observed'] + [forecast for forecast in impacts['forecasted']]\n",
+    "titles = [widgets.HTML(value=\"{}\".format(title)) for title in titles]\n",
     "\n",
-    "# g_timeseries['layout']['yaxis'] = {'title':'Hs0'}\n",
-    "# g_timeseries['layout']['yaxis2'] = {'title':'beta'}\n",
-    "# g_timeseries['layout']['yaxis4'] = {'anchor': 'x2', 'side':'right', 'title':'Tp (s)'}\n",
+    "def get_observed_impacts_table(site_id):\n",
+    "     display(impacts['observed'].query(\"site_id=='{}'\".format(site_id)).T)\n",
+    "\n",
+    "\n",
+    "def get_forecasted_impacts_table(site_id,forecast):\n",
+    "     display(impacts['forecasted'][forecast].query(\"site_id=='{}'\".format(site_id)).T)\n",
+    "\n",
+    "        \n",
+    "impacts_table_observed = widgets.interactive_output(get_observed_impacts_table, {'site_id': site_id_select})\n",
+    "forecasted_impacts_tables = []\n",
+    "for forecast, title in zip(impacts['forecasted'], titles[1:]):\n",
+    "    forecasted_impacts_tables.append(widgets.interactive_output(get_forecasted_impacts_table, {'site_id': site_id_select, 'forecast':title}))\n",
+    "\n",
+    "tables = [impacts_table_observed] + forecasted_impacts_tables\n",
+    "\n",
+    "title_tables=[widgets.VBox(children=[title,table]) for title,table in zip(titles,tables)]\n",
+    "        \n",
+    "tables_container= widgets.HBox(children=[*title_tables])\n",
     "\n",
-    "# # Add trace for each forecasted beta term\n",
-    "# for n, forecast in enumerate(impacts['forecasted']):\n",
-    "#     g_timeseries.add_trace(\n",
-    "#         go.Scatter(\n",
-    "#             x=[0,1],\n",
-    "#             y=[0,1],\n",
-    "#             name='Beta: {}'.format(forecast),\n",
-    "#             yaxis='y3'),\n",
-    "#         row=1,\n",
-    "#         col=1,\n",
-    "#     )\n",
-    "#     g_timeseries['layout'][2+n].update(yaxis='y3')\n",
     "\n",
-    "# g_timeseries['layout'].update(autosize=False, width=800, height=500, showlegend=False, hovermode='x')\n",
     "\n",
-    "# g_timeseries['yaxis2'] = dict(overlaying='y1', anchor='x1', side='right', title = 'Tp')\n",
-    "    \n",
-    "# g_timeseries['layout'].update(\n",
-    "#     title='Hydro/Morpho Parameters',\n",
-    "#     height=500,\n",
-    "# #     margin=dict(t=50, b=50, l=50, r=50),\n",
-    "#     xaxis=dict(\n",
-    "#         title='time',\n",
-    "#         domain=[0.0, 0.9],\n",
-    "#         zeroline=False,\n",
-    "#     ),\n",
-    "#     yaxis=dict(\n",
-    "#         title='Hs0 (m)',\n",
-    "#     ),\n",
-    "#     yaxis2=dict(\n",
-    "#         title='Tp (s)',\n",
-    "#         overlaying='y',\n",
-    "#         side='right',\n",
-    "#         anchor='x'\n",
-    "#     ),\n",
-    "#     yaxis3=dict(\n",
-    "#         title='beta (-)',\n",
-    "#         overlaying='y',\n",
-    "#         side='right',\n",
-    "#         position=0.97\n",
-    "#     ))\n",
-    "\n",
-    "\n",
-    "# # Add panel for time series\n",
-    "\n",
-    "# trace_Hs0 = go.Scatter(\n",
-    "#     x = [0,1],\n",
-    "#     y = [0,1],\n",
-    "#     name='Hs0'\n",
-    "# )\n",
-    "# trace_Tp = go.Scatter(\n",
-    "#     x = [0,2],\n",
-    "#     y = [0,2],\n",
-    "#     name='Tp',\n",
-    "#     yaxis='y2'\n",
-    "# )\n",
-    "\n",
-    "# forecast_traces = []\n",
-    "# for forecast in impacts['forecasted']:\n",
-    "#     forecast_traces.append(go.Scatter(\n",
-    "#         x = [0],\n",
-    "#         y = [0],\n",
-    "#         name = 'Beta: {}'.format(forecast),\n",
-    "#         yaxis='y3'\n",
-    "#     ))\n",
-    "\n",
-    "\n",
-    "# data=[trace_Hs0, trace_Tp] + forecast_traces\n",
-    "\n",
-    "# layout = go.Layout(\n",
-    "#     title = 'Hydro/Morpho Parameters',\n",
-    "#     height=200,\n",
-    "#     margin=dict(t=50,b=50,l=50,r=50),\n",
-    "#     xaxis=dict(\n",
-    "#         title='time',\n",
-    "#         domain=[0.0, 0.9],\n",
-    "#         zeroline=False,\n",
-    "#     ),\n",
-    "#     yaxis=dict(\n",
-    "#         title = 'Hs0 (m)',\n",
-    "#     ),\n",
-    "#     yaxis2=dict(\n",
-    "#         title='Tp (s)',\n",
-    "#         overlaying='y',\n",
-    "#         side='right'\n",
-    "#     ),\n",
-    "#     yaxis3=dict(\n",
-    "#         title='beta (-)',\n",
-    "#         overlaying='y',\n",
-    "#         side='right',\n",
-    "#         position=0.97\n",
-    "#     )\n",
-    "# )\n",
-    "\n",
-    "# g_params = go.FigureWidget(data=data, layout=layout)\n",
-    "\n",
-    "\n",
-    "# # Add panel for water level\n",
-    "# trace_dune_crest = go.Scatter(\n",
-    "#     x = [0,3],\n",
-    "#     y = [0,3],\n",
-    "#     name='Dune Crest',\n",
-    "#     line = dict(\n",
-    "#         color = ('rgb(214, 117, 14)'),\n",
-    "#         width = 2,\n",
-    "#         dash = 'dot')\n",
-    "# )\n",
-    "# trace_dune_toe = go.Scatter(\n",
-    "#     x = [0,3],\n",
-    "#     y = [0,3],\n",
-    "#     name='Dune Toe',\n",
-    "#     line = dict(\n",
-    "#         color = ('rgb(142, 77, 8)'),\n",
-    "#         width = 2,\n",
-    "#         dash = 'dash')\n",
-    "# )\n",
-    "# trace_tide = go.Scatter(\n",
-    "#     x = [0,4],\n",
-    "#     y = [0,4],\n",
-    "#     name='Tide+Surge WL',\n",
-    "#     line = dict(\n",
-    "#         color = ('rgb(8,51,137)'),\n",
-    "#         width = 2,\n",
-    "#         dash = 'dot')\n",
-    "# )\n",
-    "\n",
-    "# forecast_traces = []\n",
-    "# for forecast in twls['forecasted']:\n",
-    "#     forecast_traces.append(go.Scatter(\n",
-    "#         x = [0],\n",
-    "#         y = [0],\n",
-    "#         name = 'R_high: {}'.format(forecast),\n",
-    "#     ))\n",
-    "\n",
-    "# data=[trace_dune_crest, trace_dune_toe,trace_tide] + forecast_traces\n",
-    "\n",
-    "# layout = go.Layout(\n",
-    "#     title = 'Water Level & Dune Toe/Crest',\n",
-    "#     height=200,\n",
-    "#     margin=dict(t=50,b=50,l=50,r=50),\n",
-    "#     xaxis=dict(\n",
-    "#         title='time',\n",
-    "#         domain=[0.0, 0.95],\n",
-    "#         zeroline=False,\n",
-    "#     ),\n",
-    "#     yaxis=dict(\n",
-    "#         title = 'Water Level (m)',\n",
-    "#     ),\n",
-    "# )\n",
-    "\n",
-    "# g_twls = go.FigureWidget(data=data, layout=layout)\n",
     "\n",
     "\n",
     "def update_profile(change):\n",
@@ -812,14 +512,15 @@
     "        g_timeseries.data[1].y = Tps\n",
     "\n",
     "        # Update beta values\n",
-    "        idx_betas = [n for n, x in enumerate(g_timeseries.data) if 'Beta' in x.name]\n",
+    "        idx_betas = [n for n, x in enumerate(\n",
+    "            g_timeseries.data) if 'Beta' in x.name]\n",
     "        for i, forecast in zip(idx_betas, twls['forecasted']):\n",
-    "            df_twl = twls['forecasted'][forecast].query(\"site_id=='{}'\".format(site_id))\n",
+    "            df_twl = twls['forecasted'][forecast].query(\n",
+    "                \"site_id=='{}'\".format(site_id))\n",
     "            times = df_twl.index.get_level_values('datetime').tolist()\n",
     "            beta = df_twl.beta.tolist()\n",
     "            g_timeseries.data[i].x = times\n",
     "            g_timeseries.data[i].y = beta\n",
-    "        \n",
     "\n",
     "    # Update water levels plot\n",
     "    df_tide_site = df_tides.query(\"site_id=='{}'\".format(site_id))\n",
@@ -830,21 +531,35 @@
     "    with g_timeseries.batch_update():\n",
     "        g_timeseries.data[2].x = [min(times), max(times)]\n",
     "        g_timeseries.data[3].x = [min(times), max(times)]\n",
-    "        g_timeseries.data[4].x = df_tide_site.index.get_level_values('datetime')\n",
-    "        g_timeseries.data[2].y = dune_crest_z.tolist()[0], dune_crest_z.tolist()[0],\n",
-    "        g_timeseries.data[3].y = dune_toe_z.tolist()[0], dune_toe_z.tolist()[0],\n",
+    "        g_timeseries.data[4].x = df_tide_site.index.get_level_values(\n",
+    "            'datetime')\n",
+    "        g_timeseries.data[2].y = dune_crest_z.tolist()[0], dune_crest_z.tolist()[\n",
+    "            0],\n",
+    "        g_timeseries.data[3].y = dune_toe_z.tolist()[0], dune_toe_z.tolist()[\n",
+    "            0],\n",
     "        g_timeseries.data[4].y = df_tide_site.tide.tolist()\n",
     "\n",
     "        # Update rhigh values\n",
-    "        idx_betas = [n for n, x in enumerate(g_timeseries.data) if 'R_high' in x.name]\n",
-    "        for i, forecast in zip(idx_betas,twls['forecasted']):\n",
-    "            df_twl = twls['forecasted'][forecast].query(\"site_id=='{}'\".format(site_id))\n",
+    "        idx_betas = [n for n, x in enumerate(\n",
+    "            g_timeseries.data) if 'R_high' in x.name]\n",
+    "        for i, forecast in zip(idx_betas, twls['forecasted']):\n",
+    "            df_twl = twls['forecasted'][forecast].query(\n",
+    "                \"site_id=='{}'\".format(site_id))\n",
     "            times = df_twl.index.get_level_values('datetime').tolist()\n",
     "            R_high = df_twl.R_high.tolist()\n",
-    "            g_timeseries.data[5+n].x = times\n",
-    "            g_timeseries.data[5+n].y = R_high\n",
-    "\n",
+    "            g_timeseries.data[i].x = times\n",
+    "            g_timeseries.data[i].y = R_high\n",
     "\n",
+    "    # Update site id impacts\n",
+    "    observed_regime = impacts['observed'].query(\"site_id=='{}'\".format(site_id)).storm_regime.values[0]\n",
+    "    site_id_impacts.value = \"Observed: <b>{}</b><br>\".format(observed_regime)\n",
+    "    \n",
+    "    for forecast in impacts['forecasted']:\n",
+    "        regime = impacts['forecasted'][forecast].query(\"site_id=='{}'\".format(site_id)).storm_regime.values[0]\n",
+    "        site_id_impacts.value += '{}: <b>{}</b><br>'.format(forecast, regime)\n",
+    "    \n",
+    "    # Update our tables\n",
+    "    \n",
     "site_id_select.observe(update_profile, names=\"value\")\n",
     "\n",
     "\n",
@@ -867,478 +582,42 @@
     "for box in selectboxes:\n",
     "    box.observe(update_filter, names=\"value\")\n",
     "\n",
-    "# Display our widgets!ore forecast i\n",
-    "widgets.VBox([filter_container, site_id_container,\n",
-    "              widgets.HBox([g_profiles, g_map]), g_timeseries])\n",
-    "# widgets.VBox([filter_container,site_id_container,widgets.HBox([g_profiles,g_map]),g_twls,g_params])\n",
-    "\n",
+    "    \n",
     "\n",
-    "# For table\n",
-    "# out = Output()\n",
-    "# with out:\n",
-    "#     display(df_waves.head(3))\n",
     "\n",
-    "# widgets.VBox([filter_container,site_id_container, out])"
+    "# Display our widgets!\n",
+    "widgets.VBox([filter_container, site_id_container,\n",
+    "              widgets.HBox([g_profiles, g_map]), g_timeseries,  tables_container])\n",
+    "\n"
    ]
   },
   {
    "cell_type": "code",
-   "execution_count": 164,
+   "execution_count": null,
    "metadata": {
     "ExecuteTime": {
-     "end_time": "2018-11-22T01:26:00.955120Z",
-     "start_time": "2018-11-22T01:26:00.904958Z"
-    }
+     "start_time": "2018-11-22T22:48:17.837Z"
+    },
+    "scrolled": true
    },
-   "outputs": [
-    {
-     "data": {
-      "text/plain": [
-       "['2016-05-28 00:00:00',\n",
-       " '2016-05-28 01:00:00',\n",
-       " '2016-05-28 02:00:00',\n",
-       " '2016-05-28 03:00:00',\n",
-       " '2016-05-28 04:00:00',\n",
-       " '2016-05-28 05:00:00',\n",
-       " '2016-05-28 06:00:00',\n",
-       " '2016-05-28 07:00:00',\n",
-       " '2016-05-28 08:00:00',\n",
-       " '2016-05-28 09:00:00',\n",
-       " '2016-05-28 10:00:00',\n",
-       " '2016-05-28 11:00:00',\n",
-       " '2016-05-28 12:00:00',\n",
-       " '2016-05-28 13:00:00',\n",
-       " '2016-05-28 14:00:00',\n",
-       " '2016-05-28 15:00:00',\n",
-       " '2016-05-28 16:00:00',\n",
-       " '2016-05-28 17:00:00',\n",
-       " '2016-05-28 18:00:00',\n",
-       " '2016-05-28 19:00:00',\n",
-       " '2016-05-28 20:00:00',\n",
-       " '2016-05-28 21:00:00',\n",
-       " '2016-05-28 22:00:00',\n",
-       " '2016-05-28 23:00:00',\n",
-       " '2016-05-29 00:00:00',\n",
-       " '2016-05-29 01:00:00',\n",
-       " '2016-05-29 02:00:00',\n",
-       " '2016-05-29 03:00:00',\n",
-       " '2016-05-29 04:00:00',\n",
-       " '2016-05-29 05:00:00',\n",
-       " '2016-05-29 06:00:00',\n",
-       " '2016-05-29 07:00:00',\n",
-       " '2016-05-29 08:00:00',\n",
-       " '2016-05-29 09:00:00',\n",
-       " '2016-05-29 10:00:00',\n",
-       " '2016-05-29 11:00:00',\n",
-       " '2016-05-29 12:00:00',\n",
-       " '2016-05-29 13:00:00',\n",
-       " '2016-05-29 14:00:00',\n",
-       " '2016-05-29 15:00:00',\n",
-       " '2016-05-29 16:00:00',\n",
-       " '2016-05-29 17:00:00',\n",
-       " '2016-05-29 18:00:00',\n",
-       " '2016-05-29 19:00:00',\n",
-       " '2016-05-29 20:00:00',\n",
-       " '2016-05-29 21:00:00',\n",
-       " '2016-05-29 22:00:00',\n",
-       " '2016-05-29 23:00:00',\n",
-       " '2016-05-30 00:00:00',\n",
-       " '2016-05-30 01:00:00',\n",
-       " '2016-05-30 02:00:00',\n",
-       " '2016-05-30 03:00:00',\n",
-       " '2016-05-30 04:00:00',\n",
-       " '2016-05-30 05:00:00',\n",
-       " '2016-05-30 06:00:00',\n",
-       " '2016-05-30 07:00:00',\n",
-       " '2016-05-30 08:00:00',\n",
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-       " '2016-05-30 12:00:00',\n",
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-       " '2016-05-30 14:00:00',\n",
-       " '2016-05-30 15:00:00',\n",
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-       " '2016-05-30 17:00:00',\n",
-       " '2016-05-30 18:00:00',\n",
-       " '2016-05-30 19:00:00',\n",
-       " '2016-05-30 20:00:00',\n",
-       " '2016-05-30 21:00:00',\n",
-       " '2016-05-30 22:00:00',\n",
-       " '2016-05-30 23:00:00',\n",
-       " '2016-05-31 00:00:00',\n",
-       " '2016-05-31 01:00:00',\n",
-       " '2016-05-31 02:00:00',\n",
-       " '2016-05-31 03:00:00',\n",
-       " '2016-05-31 04:00:00',\n",
-       " '2016-05-31 05:00:00',\n",
-       " '2016-05-31 06:00:00',\n",
-       " '2016-05-31 07:00:00',\n",
-       " '2016-05-31 08:00:00',\n",
-       " '2016-05-31 09:00:00',\n",
-       " '2016-05-31 10:00:00',\n",
-       " '2016-05-31 11:00:00',\n",
-       " '2016-05-31 12:00:00',\n",
-       " '2016-05-31 13:00:00',\n",
-       " '2016-05-31 14:00:00',\n",
-       " '2016-05-31 15:00:00',\n",
-       " '2016-05-31 16:00:00',\n",
-       " '2016-05-31 17:00:00',\n",
-       " '2016-05-31 18:00:00',\n",
-       " '2016-05-31 19:00:00',\n",
-       " '2016-05-31 20:00:00',\n",
-       " '2016-05-31 21:00:00',\n",
-       " '2016-05-31 22:00:00',\n",
-       " '2016-05-31 23:00:00',\n",
-       " '2016-06-01 00:00:00',\n",
-       " '2016-06-01 01:00:00',\n",
-       " '2016-06-01 02:00:00',\n",
-       " '2016-06-01 03:00:00',\n",
-       " '2016-06-01 04:00:00',\n",
-       " '2016-06-01 05:00:00',\n",
-       " '2016-06-01 06:00:00',\n",
-       " '2016-06-01 07:00:00',\n",
-       " '2016-06-01 08:00:00',\n",
-       " '2016-06-01 09:00:00',\n",
-       " '2016-06-01 10:00:00',\n",
-       " '2016-06-01 11:00:00',\n",
-       " '2016-06-01 12:00:00',\n",
-       " '2016-06-01 13:00:00',\n",
-       " '2016-06-01 14:00:00',\n",
-       " '2016-06-01 15:00:00',\n",
-       " '2016-06-01 16:00:00',\n",
-       " '2016-06-01 17:00:00',\n",
-       " '2016-06-01 18:00:00',\n",
-       " '2016-06-01 19:00:00',\n",
-       " '2016-06-01 20:00:00',\n",
-       " '2016-06-01 21:00:00',\n",
-       " '2016-06-01 22:00:00',\n",
-       " '2016-06-01 23:00:00',\n",
-       " '2016-06-02 00:00:00',\n",
-       " '2016-06-02 01:00:00',\n",
-       " '2016-06-02 02:00:00',\n",
-       " '2016-06-02 03:00:00',\n",
-       " '2016-06-02 04:00:00',\n",
-       " '2016-06-02 05:00:00',\n",
-       " '2016-06-02 06:00:00',\n",
-       " '2016-06-02 07:00:00',\n",
-       " '2016-06-02 08:00:00',\n",
-       " '2016-06-02 09:00:00',\n",
-       " '2016-06-02 10:00:00',\n",
-       " '2016-06-02 11:00:00',\n",
-       " '2016-06-02 12:00:00',\n",
-       " '2016-06-02 13:00:00',\n",
-       " '2016-06-02 14:00:00',\n",
-       " '2016-06-02 15:00:00',\n",
-       " '2016-06-02 16:00:00',\n",
-       " '2016-06-02 17:00:00',\n",
-       " '2016-06-02 18:00:00',\n",
-       " '2016-06-02 19:00:00',\n",
-       " '2016-06-02 20:00:00',\n",
-       " '2016-06-02 21:00:00',\n",
-       " '2016-06-02 22:00:00',\n",
-       " '2016-06-02 23:00:00',\n",
-       " '2016-06-03 00:00:00',\n",
-       " '2016-06-03 01:00:00',\n",
-       " '2016-06-03 02:00:00',\n",
-       " '2016-06-03 03:00:00',\n",
-       " '2016-06-03 04:00:00',\n",
-       " '2016-06-03 05:00:00',\n",
-       " '2016-06-03 06:00:00',\n",
-       " '2016-06-03 07:00:00',\n",
-       " '2016-06-03 08:00:00',\n",
-       " '2016-06-03 09:00:00',\n",
-       " '2016-06-03 10:00:00',\n",
-       " '2016-06-03 11:00:00',\n",
-       " '2016-06-03 12:00:00',\n",
-       " '2016-06-03 13:00:00',\n",
-       " '2016-06-03 14:00:00',\n",
-       " '2016-06-03 15:00:00',\n",
-       " '2016-06-03 16:00:00',\n",
-       " '2016-06-03 17:00:00',\n",
-       " '2016-06-03 18:00:00',\n",
-       " '2016-06-03 19:00:00',\n",
-       " '2016-06-03 20:00:00',\n",
-       " '2016-06-03 21:00:00',\n",
-       " '2016-06-03 22:00:00',\n",
-       " '2016-06-03 23:00:00',\n",
-       " '2016-06-04 00:00:00',\n",
-       " '2016-06-04 01:00:00',\n",
-       " '2016-06-04 02:00:00',\n",
-       " '2016-06-04 03:00:00',\n",
-       " '2016-06-04 04:00:00',\n",
-       " '2016-06-04 05:00:00',\n",
-       " '2016-06-04 06:00:00',\n",
-       " '2016-06-04 07:00:00',\n",
-       " '2016-06-04 08:00:00',\n",
-       " '2016-06-04 09:00:00',\n",
-       " '2016-06-04 10:00:00',\n",
-       " '2016-06-04 11:00:00',\n",
-       " '2016-06-04 12:00:00',\n",
-       " '2016-06-04 13:00:00',\n",
-       " '2016-06-04 14:00:00',\n",
-       " '2016-06-04 15:00:00',\n",
-       " '2016-06-04 16:00:00',\n",
-       " '2016-06-04 17:00:00',\n",
-       " '2016-06-04 18:00:00',\n",
-       " '2016-06-04 19:00:00',\n",
-       " '2016-06-04 20:00:00',\n",
-       " '2016-06-04 21:00:00',\n",
-       " '2016-06-04 22:00:00',\n",
-       " '2016-06-04 23:00:00',\n",
-       " '2016-06-05 00:00:00',\n",
-       " '2016-06-05 01:00:00',\n",
-       " '2016-06-05 02:00:00',\n",
-       " '2016-06-05 03:00:00',\n",
-       " '2016-06-05 04:00:00',\n",
-       " '2016-06-05 05:00:00',\n",
-       " '2016-06-05 06:00:00',\n",
-       " '2016-06-05 07:00:00',\n",
-       " '2016-06-05 08:00:00',\n",
-       " '2016-06-05 09:00:00',\n",
-       " '2016-06-05 10:00:00',\n",
-       " '2016-06-05 11:00:00',\n",
-       " '2016-06-05 12:00:00',\n",
-       " '2016-06-05 13:00:00',\n",
-       " '2016-06-05 14:00:00',\n",
-       " '2016-06-05 15:00:00',\n",
-       " '2016-06-05 16:00:00',\n",
-       " '2016-06-05 17:00:00',\n",
-       " '2016-06-05 18:00:00',\n",
-       " '2016-06-05 19:00:00',\n",
-       " '2016-06-05 20:00:00',\n",
-       " '2016-06-05 21:00:00',\n",
-       " '2016-06-05 22:00:00',\n",
-       " '2016-06-05 23:00:00',\n",
-       " '2016-06-06 00:00:00',\n",
-       " '2016-06-06 01:00:00',\n",
-       " '2016-06-06 02:00:00',\n",
-       " '2016-06-06 03:00:00',\n",
-       " '2016-06-06 04:00:00',\n",
-       " '2016-06-06 05:00:00',\n",
-       " '2016-06-06 06:00:00',\n",
-       " '2016-06-06 07:00:00',\n",
-       " '2016-06-06 08:00:00',\n",
-       " '2016-06-06 09:00:00',\n",
-       " '2016-06-06 10:00:00',\n",
-       " '2016-06-06 11:00:00',\n",
-       " '2016-06-06 12:00:00',\n",
-       " '2016-06-06 13:00:00',\n",
-       " '2016-06-06 14:00:00',\n",
-       " '2016-06-06 15:00:00',\n",
-       " '2016-06-06 16:00:00',\n",
-       " '2016-06-06 17:00:00',\n",
-       " '2016-06-06 18:00:00',\n",
-       " '2016-06-06 19:00:00',\n",
-       " '2016-06-06 20:00:00',\n",
-       " '2016-06-06 21:00:00',\n",
-       " '2016-06-06 22:00:00',\n",
-       " '2016-06-06 23:00:00',\n",
-       " '2016-06-07 00:00:00',\n",
-       " '2016-06-07 01:00:00',\n",
-       " '2016-06-07 02:00:00',\n",
-       " '2016-06-07 03:00:00',\n",
-       " '2016-06-07 04:00:00',\n",
-       " '2016-06-07 05:00:00',\n",
-       " '2016-06-07 06:00:00',\n",
-       " '2016-06-07 07:00:00',\n",
-       " '2016-06-07 08:00:00',\n",
-       " '2016-06-07 09:00:00',\n",
-       " '2016-06-07 10:00:00',\n",
-       " '2016-06-07 11:00:00',\n",
-       " '2016-06-07 12:00:00',\n",
-       " '2016-06-07 13:00:00',\n",
-       " '2016-06-07 14:00:00',\n",
-       " '2016-06-07 15:00:00',\n",
-       " '2016-06-07 16:00:00',\n",
-       " '2016-06-07 17:00:00',\n",
-       " '2016-06-07 18:00:00',\n",
-       " '2016-06-07 19:00:00',\n",
-       " '2016-06-07 20:00:00',\n",
-       " '2016-06-07 21:00:00',\n",
-       " '2016-06-07 22:00:00',\n",
-       " '2016-06-07 23:00:00',\n",
-       " '2016-06-08 00:00:00',\n",
-       " '2016-06-08 01:00:00',\n",
-       " '2016-06-08 02:00:00',\n",
-       " '2016-06-08 03:00:00',\n",
-       " '2016-06-08 04:00:00',\n",
-       " '2016-06-08 05:00:00',\n",
-       " '2016-06-08 06:00:00',\n",
-       " '2016-06-08 07:00:00',\n",
-       " '2016-06-08 08:00:00',\n",
-       " '2016-06-08 09:00:00',\n",
-       " '2016-06-08 10:00:00',\n",
-       " '2016-06-08 11:00:00',\n",
-       " '2016-06-08 12:00:00',\n",
-       " '2016-06-08 13:00:00',\n",
-       " '2016-06-08 14:00:00',\n",
-       " '2016-06-08 15:00:00',\n",
-       " '2016-06-08 16:00:00',\n",
-       " '2016-06-08 17:00:00',\n",
-       " '2016-06-08 18:00:00',\n",
-       " '2016-06-08 19:00:00',\n",
-       " '2016-06-08 20:00:00',\n",
-       " '2016-06-08 21:00:00',\n",
-       " '2016-06-08 22:00:00',\n",
-       " '2016-06-08 23:00:00',\n",
-       " '2016-06-09 00:00:00',\n",
-       " '2016-06-09 01:00:00',\n",
-       " '2016-06-09 02:00:00',\n",
-       " '2016-06-09 03:00:00',\n",
-       " '2016-06-09 04:00:00',\n",
-       " '2016-06-09 05:00:00',\n",
-       " '2016-06-09 06:00:00',\n",
-       " '2016-06-09 07:00:00',\n",
-       " '2016-06-09 08:00:00',\n",
-       " '2016-06-09 09:00:00',\n",
-       " '2016-06-09 10:00:00',\n",
-       " '2016-06-09 11:00:00',\n",
-       " '2016-06-09 12:00:00',\n",
-       " '2016-06-09 13:00:00',\n",
-       " '2016-06-09 14:00:00',\n",
-       " '2016-06-09 15:00:00',\n",
-       " '2016-06-09 16:00:00',\n",
-       " '2016-06-09 17:00:00',\n",
-       " '2016-06-09 18:00:00',\n",
-       " '2016-06-09 19:00:00',\n",
-       " '2016-06-09 20:00:00',\n",
-       " '2016-06-09 21:00:00',\n",
-       " '2016-06-09 22:00:00',\n",
-       " '2016-06-09 23:00:00',\n",
-       " '2016-06-10 00:00:00',\n",
-       " '2016-06-10 01:00:00',\n",
-       " '2016-06-10 02:00:00',\n",
-       " '2016-06-10 03:00:00',\n",
-       " '2016-06-10 04:00:00',\n",
-       " '2016-06-10 05:00:00',\n",
-       " '2016-06-10 06:00:00',\n",
-       " '2016-06-10 07:00:00',\n",
-       " '2016-06-10 08:00:00',\n",
-       " '2016-06-10 09:00:00',\n",
-       " '2016-06-10 10:00:00',\n",
-       " '2016-06-10 11:00:00',\n",
-       " '2016-06-10 12:00:00',\n",
-       " '2016-06-10 13:00:00',\n",
-       " '2016-06-10 14:00:00',\n",
-       " '2016-06-10 15:00:00',\n",
-       " '2016-06-10 16:00:00',\n",
-       " '2016-06-10 17:00:00',\n",
-       " '2016-06-10 18:00:00',\n",
-       " '2016-06-10 19:00:00',\n",
-       " '2016-06-10 20:00:00',\n",
-       " '2016-06-10 21:00:00',\n",
-       " '2016-06-10 22:00:00',\n",
-       " '2016-06-10 23:00:00',\n",
-       " '2016-06-11 00:00:00',\n",
-       " '2016-06-11 01:00:00',\n",
-       " '2016-06-11 02:00:00',\n",
-       " '2016-06-11 03:00:00',\n",
-       " '2016-06-11 04:00:00',\n",
-       " '2016-06-11 05:00:00',\n",
-       " '2016-06-11 06:00:00',\n",
-       " '2016-06-11 07:00:00',\n",
-       " '2016-06-11 08:00:00',\n",
-       " '2016-06-11 09:00:00',\n",
-       " '2016-06-11 10:00:00',\n",
-       " '2016-06-11 11:00:00',\n",
-       " '2016-06-11 12:00:00',\n",
-       " '2016-06-11 13:00:00',\n",
-       " '2016-06-11 14:00:00',\n",
-       " '2016-06-11 15:00:00',\n",
-       " '2016-06-11 16:00:00',\n",
-       " '2016-06-11 17:00:00',\n",
-       " '2016-06-11 18:00:00',\n",
-       " '2016-06-11 19:00:00',\n",
-       " '2016-06-11 20:00:00',\n",
-       " '2016-06-11 21:00:00',\n",
-       " '2016-06-11 22:00:00',\n",
-       " '2016-06-11 23:00:00',\n",
-       " '2016-06-12 00:00:00',\n",
-       " '2016-06-12 01:00:00',\n",
-       " '2016-06-12 02:00:00',\n",
-       " '2016-06-12 03:00:00',\n",
-       " '2016-06-12 04:00:00',\n",
-       " '2016-06-12 05:00:00',\n",
-       " '2016-06-12 06:00:00',\n",
-       " '2016-06-12 07:00:00',\n",
-       " '2016-06-12 08:00:00',\n",
-       " '2016-06-12 09:00:00',\n",
-       " '2016-06-12 10:00:00',\n",
-       " '2016-06-12 11:00:00',\n",
-       " '2016-06-12 12:00:00',\n",
-       " '2016-06-12 13:00:00',\n",
-       " '2016-06-12 14:00:00',\n",
-       " '2016-06-12 15:00:00',\n",
-       " '2016-06-12 16:00:00',\n",
-       " '2016-06-12 17:00:00',\n",
-       " '2016-06-12 18:00:00',\n",
-       " '2016-06-12 19:00:00',\n",
-       " '2016-06-12 20:00:00',\n",
-       " '2016-06-12 21:00:00',\n",
-       " '2016-06-12 22:00:00',\n",
-       " '2016-06-12 23:00:00',\n",
-       " '2016-06-13 00:00:00',\n",
-       " '2016-06-13 01:00:00',\n",
-       " '2016-06-13 02:00:00',\n",
-       " '2016-06-13 03:00:00',\n",
-       " '2016-06-13 04:00:00',\n",
-       " '2016-06-13 05:00:00',\n",
-       " '2016-06-13 06:00:00',\n",
-       " '2016-06-13 07:00:00',\n",
-       " '2016-06-13 08:00:00',\n",
-       " '2016-06-13 09:00:00',\n",
-       " '2016-06-13 10:00:00',\n",
-       " '2016-06-13 11:00:00',\n",
-       " '2016-06-13 12:00:00',\n",
-       " '2016-06-13 13:00:00',\n",
-       " '2016-06-13 14:00:00',\n",
-       " '2016-06-13 15:00:00',\n",
-       " '2016-06-13 16:00:00',\n",
-       " '2016-06-13 17:00:00',\n",
-       " '2016-06-13 18:00:00',\n",
-       " '2016-06-13 19:00:00',\n",
-       " '2016-06-13 20:00:00',\n",
-       " '2016-06-13 21:00:00',\n",
-       " '2016-06-13 22:00:00',\n",
-       " '2016-06-13 23:00:00',\n",
-       " '2016-06-14 00:00:00',\n",
-       " '2016-06-14 01:00:00',\n",
-       " '2016-06-14 02:00:00',\n",
-       " '2016-06-14 03:00:00',\n",
-       " '2016-06-14 04:00:00',\n",
-       " '2016-06-14 05:00:00',\n",
-       " '2016-06-14 06:00:00',\n",
-       " '2016-06-14 07:00:00',\n",
-       " '2016-06-14 08:00:00',\n",
-       " '2016-06-14 09:00:00',\n",
-       " '2016-06-14 10:00:00',\n",
-       " '2016-06-14 11:00:00',\n",
-       " '2016-06-14 12:00:00',\n",
-       " '2016-06-14 13:00:00',\n",
-       " '2016-06-14 14:00:00',\n",
-       " '2016-06-14 15:00:00',\n",
-       " '2016-06-14 16:00:00',\n",
-       " '2016-06-14 17:00:00',\n",
-       " '2016-06-14 18:00:00',\n",
-       " '2016-06-14 19:00:00',\n",
-       " '2016-06-14 20:00:00',\n",
-       " '2016-06-14 21:00:00',\n",
-       " '2016-06-14 22:00:00',\n",
-       " '2016-06-14 23:00:00',\n",
-       " '2016-06-15 00:00:00']"
-      ]
-     },
-     "execution_count": 164,
-     "metadata": {},
-     "output_type": "execute_result"
+   "outputs": [],
+   "source": [
+    "titles[0].observe"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "metadata": {
+    "ExecuteTime": {
+     "start_time": "2018-11-22T22:48:17.840Z"
     }
-   ],
+   },
+   "outputs": [],
    "source": [
-    "g_timeseries.data\n",
-    "df_twl = twls['forecasted']['foreshore_slope_sto06'].query(\"site_id=='{}'\".format('NARRA0018'))\n",
-    "times = df_twl.index.get_level_values('datetime').tolist()\n",
-    "times"
+    "# impacts['observed'].query(\"site_id=='{}'\".format(\"NARRA0018\")).T\n",
+    "impacts['forecasted']['foreshore_slope_sto06'].query(\"site_id=='{}'\".format(\"NARRA0018\")).T\n",
+    "\n"
    ]
   }
  ],