1 files changed, 55 insertions, 12 deletions
diff --git a/python/notebooks/Single Names Monitoring.ipynb b/python/notebooks/Single Names Monitoring.ipynb
index 62a1383a..17e0c40d 100644
--- a/python/notebooks/Single Names Monitoring.ipynb
+++ b/python/notebooks/Single Names Monitoring.ipynb
@@ -3,7 +3,11 @@
   {
    "cell_type": "code",
    "execution_count": null,
-   "metadata": {},
+   "metadata": {
+    "jupyter": {
+     "source_hidden": true
+    }
+   },
    "outputs": [],
    "source": [
     "import pandas as pd\n",
@@ -11,7 +15,7 @@
     "from analytics.basket_index import MarkitBasketIndex\n",
     "import matplotlib.pyplot as plt\n",
     "\n",
-    "from db import dbengine\n",
+    "from utils.db import dbengine\n",
     "from ipywidgets import widgets\n",
     "engine = dbengine('serenitasdb')"
    ]
@@ -19,7 +23,11 @@
   {
    "cell_type": "code",
    "execution_count": null,
-   "metadata": {},
+   "metadata": {
+    "jupyter": {
+     "source_hidden": true
+    }
+   },
    "outputs": [],
    "source": [
     "w = widgets.Dropdown(\n",
@@ -34,17 +42,25 @@
   {
    "cell_type": "code",
    "execution_count": null,
-   "metadata": {},
+   "metadata": {
+    "jupyter": {
+     "source_hidden": true
+    }
+   },
    "outputs": [],
    "source": [
-    "w_1 = widgets.IntSlider(value=31, min=22, max=31, description = 'Series')\n",
+    "w_1 = widgets.IntSlider(value=32, min=22, max=32, description = 'Series')\n",
     "w_1"
    ]
   },
   {
    "cell_type": "code",
    "execution_count": null,
-   "metadata": {},
+   "metadata": {
+    "jupyter": {
+     "source_hidden": true
+    }
+   },
    "outputs": [],
    "source": [
     "value_date = (pd.datetime.today() - pd.offsets.BDay(2)).date()\n",
@@ -76,7 +92,11 @@
   {
    "cell_type": "code",
    "execution_count": null,
-   "metadata": {},
+   "metadata": {
+    "jupyter": {
+     "source_hidden": true
+    }
+   },
    "outputs": [],
    "source": [
     "#Additions\n",
@@ -86,7 +106,11 @@
   {
    "cell_type": "code",
    "execution_count": null,
-   "metadata": {},
+   "metadata": {
+    "jupyter": {
+     "source_hidden": true
+    }
+   },
    "outputs": [],
    "source": [
     "date_range = pd.bdate_range(value_date - 52 * pd.offsets.Week(), value_date, freq='5B')\n",
@@ -103,7 +127,11 @@
   {
    "cell_type": "code",
    "execution_count": null,
-   "metadata": {},
+   "metadata": {
+    "jupyter": {
+     "source_hidden": true
+    }
+   },
    "outputs": [],
    "source": [
     "#Top 20 highest cumulative\n",
@@ -119,7 +147,22 @@
   {
    "cell_type": "code",
    "execution_count": null,
-   "metadata": {},
+   "metadata": {
+    "jupyter": {
+     "source_hidden": true
+    }
+   },
+   "outputs": [],
+   "source": []
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "metadata": {
+    "jupyter": {
+     "source_hidden": true
+    }
+   },
    "outputs": [],
    "source": []
   }
@@ -140,9 +183,9 @@
    "name": "python",
    "nbconvert_exporter": "python",
    "pygments_lexer": "ipython3",
-   "version": "3.7.0"
+   "version": "3.7.3"
   }
  },
  "nbformat": 4,
- "nbformat_minor": 2
+ "nbformat_minor": 4
 }