Update complete_poc_to_production_exercise_set.ipynb

Author: yurchisin

optimization301/PoC_to_Production_Exercise/complete_poc_to_production_exercise_set.ipynb

@@ -57,6 +57,46 @@
     "import plotly.graph_objects as go"
    ]
   },
+  {
+   "cell_type": "markdown",
+   "id": "3c038388",
+   "metadata": {},
+   "source": [
+    "## Set a path to the data used\n",
+    "**If you downloaded the notebook/data and are running this locally**, make sure the data is in the same directory as the notebook and run the cell below, or update it to the correct path."
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "id": "7a89d263",
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "# Run this cell if you're working locally on your machine.\n",
+    "# Change the path if needed.\n",
+    "path = ''"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "id": "f31bd577",
+   "metadata": {},
+   "source": [
+    "**If you are running this in Colab** run this cell below to set the path to read the data from the GitHub repository."
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "id": "f0fd6095",
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "# Run this cell if you are using Colab.\n",
+    "path = 'https://raw.githubusercontent.com/Gurobi/modeling-examples/refs/heads/master/optimization301/PoC_to_Production_Exercise/ex1_orders.csv'"
+   ]
+  },
   {
    "cell_type": "markdown",
    "id": "9b1d2eb8-8875-4eec-8fca-001285136186",
@@ -70,15 +110,15 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 2,
+   "execution_count": null,
    "id": "96e1ee44-cd58-4593-bbe9-539cefbefb40",
    "metadata": {},
    "outputs": [],
    "source": [
     "def ex1():\n",
     "    # Load the data\n",
-    "    orders = pd.read_csv('ex1_orders.csv')\n",
-    "    vehicles = pd.read_csv('ex1_vehicles.csv')\n",
+    "    orders = pd.read_csv(path+'ex1_orders.csv')\n",
+    "    vehicles = pd.read_csv(path+'ex1_vehicles.csv')\n",
     "    num_orders = len(orders)\n",
     "    num_vehicles = len(vehicles)\n",
     "    # Build the model\n",
@@ -173,15 +213,15 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 5,
+   "execution_count": null,
    "id": "2e2c281e-3c4d-4d73-a8f6-38945522163a",
    "metadata": {},
    "outputs": [],
    "source": [
     "def ex2():\n",
-    "    dcs_df = pd.read_csv('ex2_dcs.csv')\n",
-    "    cust_df = pd.read_csv('ex2_customers.csv')\n",
-    "    lanes_df = pd.read_csv('ex2_lanes.csv')\n",
+    "    dcs_df = pd.read_csv(path+'ex2_dcs.csv')\n",
+    "    cust_df = pd.read_csv(path+'ex2_customers.csv')\n",
+    "    lanes_df = pd.read_csv(path+'ex2_lanes.csv')\n",
     "    # Built some objects for convenience and speed\n",
     "    dc = dcs_df['dc_id'].tolist()\n",
     "    cust = cust_df['cust_id'].tolist()\n",
@@ -245,7 +285,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 7,
+   "execution_count": null,
    "id": "3feef743-1f31-4fe5-a6fc-d6e75cb1d6a7",
    "metadata": {
     "editable": true,
@@ -257,8 +297,8 @@
    "outputs": [],
    "source": [
     "def plot_ex2():\n",
-    "    dcs = pd.read_csv('ex2_dcs.csv')\n",
-    "    customers = pd.read_csv('ex2_customers.csv')\n",
+    "    dcs = pd.read_csv(path+'ex2_dcs.csv')\n",
+    "    customers = pd.read_csv(path+'ex2_customers.csv')\n",
     "    fig = go.Figure()\n",
     "    # Customers\n",
     "    fig.add_trace(go.Scattermap(\n",
@@ -1514,15 +1554,15 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 10,
+   "execution_count": null,
    "id": "704e66ff-cab2-439e-869a-63fcf76e4c19",
    "metadata": {},
    "outputs": [],
    "source": [
     "def ex5():\n",
-    "    dcs_df = pd.read_csv('ex2_dcs.csv')\n",
-    "    cust_df = pd.read_csv('ex2_customers.csv')\n",
-    "    lanes_df = pd.read_csv('ex2_lanes.csv')\n",
+    "    dcs_df = pd.read_csv(path+'ex2_dcs.csv')\n",
+    "    cust_df = pd.read_csv(path+'ex2_customers.csv')\n",
+    "    lanes_df = pd.read_csv(path+'ex2_lanes.csv')\n",
     "\n",
     "    # Built some objects for convenience and speed\n",
     "    dc = dcs_df['dc_id'].tolist()\n",
@@ -1845,9 +1885,9 @@
  ],
  "metadata": {
   "kernelspec": {
-   "display_name": "opti",
+   "display_name": "Python 3",
    "language": "python",
-   "name": "opti"
+   "name": "python3"
   },
   "language_info": {
    "codemirror_mode": {
@@ -1859,7 +1899,7 @@
    "name": "python",
    "nbconvert_exporter": "python",
    "pygments_lexer": "ipython3",
-   "version": "3.11.13"
+   "version": "3.13.5"
   }
  },
  "nbformat": 4,