updated looker studio visualization

create_bq_tables.ipynb

@@ -1,5 +1,13 @@
 {
  "cells": [
+  {
+   "cell_type": "markdown",
+   "id": "3686ebf2-4a43-4a9b-ab04-2937886327af",
+   "metadata": {},
+   "source": [
+    "# Create BigQuery Tables Using Data Stored in GCS"
+   ]
+  },
   {
    "cell_type": "markdown",
    "id": "5e5fe419-6a99-4aa5-a4b4-c14f0c8038ec",

geospatial.ipynb

@@ -119,6 +119,24 @@
     "spark.sparkContext.getConf().getAll()"
    ]
   },
+  {
+   "cell_type": "markdown",
+   "id": "d91bc31b-e600-4847-bbb2-467ba33390db",
+   "metadata": {},
+   "source": [
+    "# Build geovisualizations using BigQuery and Looker Studio\n",
+    "\n",
+    "This notebook updates and creates BigQuery tables to create geospatial data points by combining latitude and longitude of pickup and dropoff locations and mapping them to Chicago community area polygons. These tables would be used to create visualizations using Looker Studio which are linked at the end of the notebook."
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "id": "97debaa8-a9fe-43b5-9550-bf86ae241d65",
+   "metadata": {},
+   "source": [
+    "## Geospatial data creation and mapping on Chicago-wide datasets"
+   ]
+  },
   {
    "cell_type": "code",
    "execution_count": 12,
@@ -885,6 +903,14 @@
     "   ORDER BY j.year"
    ]
   },
+  {
+   "cell_type": "markdown",
+   "id": "9eddab54-8c90-49e3-a004-48e55d6cdfac",
+   "metadata": {},
+   "source": [
+    "## Geospatial data creation and mapping on Chicago Lyft Ride Program Area datasets"
+   ]
+  },
   {
    "cell_type": "code",
    "execution_count": 25,
@@ -1485,10 +1511,22 @@
     "ON j.pickup_area = c.area_num_1;"
    ]
   },
+  {
+   "cell_type": "markdown",
+   "id": "d32ee0ef-7b63-4f20-a2d3-e691f8bf8243",
+   "metadata": {},
+   "source": [
+    "## Links to geovisualizations created using Looker Studio\n",
+    "\n",
+    "[Chicago Rideshares Geo-Visualization](https://lookerstudio.google.com/s/v4f-6o8MV-M)\n",
+    "    \n",
+    "[Heatmap of Rides in the Program Area](https://lookerstudio.google.com/s/lut3O7_HRnc)"
+   ]
+  },
   {
    "cell_type": "code",
    "execution_count": null,
-   "id": "c9fb95a9-e2b0-471e-b76f-65b12cf3cf49",
+   "id": "f666f1fa-fc51-41f3-a46a-328076e752e2",
    "metadata": {},
    "outputs": [],
    "source": []