move all imports to top

Author: xlt208

samples/04_gis_analysts_data_scientists/analyze_patterns_in_construction_permits_part2.ipynb

@@ -33,18 +33,38 @@
     "## Aggregate points"
    ]
   },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "from datetime import datetime as dt\n",
+    "\n",
+    "import pandas as pd\n",
+    "from arcgis.features.enrich_data import enrich_layer\n",
+    "from arcgis.features.summarize_data import aggregate_points\n",
+    "from arcgis.gis import GIS"
+   ]
+  },
   {
    "cell_type": "code",
    "execution_count": 2,
    "metadata": {},
    "outputs": [],
    "source": [
-    "from arcgis import GIS\n",
     "gis = GIS()\n",
     "# import warnings\n",
     "# warnings.filterwarnings(\"ignore\")"
    ]
   },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "metadata": {},
+   "outputs": [],
+   "source": []
+  },
   {
    "cell_type": "code",
    "execution_count": 3,
@@ -169,16 +189,6 @@
     "Next, you'll use this layer to aggregate permit points. By default, the parameters are set to use the ZIP Codes as the area layer, the permits as the layer to be aggregated, and the layer style to be based on permit count. These parameters are exactly what you want."
    ]
   },
-  {
-   "cell_type": "code",
-   "execution_count": 7,
-   "metadata": {},
-   "outputs": [],
-   "source": [
-    "from arcgis.features.summarize_data import aggregate_points\n",
-    "from datetime import datetime as dt"
-   ]
-  },
   {
    "cell_type": "code",
    "execution_count": 8,
@@ -279,15 +289,6 @@
     "The new layer looks like a point layer, but it's actually a polygon layer with a point symbology. Each point represents the number of permits per ZIP Code area. Larger points indicate ZIP Codes with more permits."
    ]
   },
-  {
-   "cell_type": "code",
-   "execution_count": 11,
-   "metadata": {},
-   "outputs": [],
-   "source": [
-    "import pandas as pd"
-   ]
-  },
   {
    "cell_type": "code",
    "execution_count": 16,
@@ -569,15 +570,6 @@
     "Are there demographic characteristics about the Clarksburg ZIP Code that contributed to its high growth? If so, are there other areas with those characteristics that may experience growth in the future? To answer these questions, you'll use the **Enrich Data** analysis tool. This tool adds demographic attributes of your choice to your data. Specifically, you'll add Tapestry information to each ZIP Code. <a href=\"https://doc.arcgis.com/en/esri-demographics/latest/regional-data/tapestry-segmentation.htm\">Tapestry</a> is a summary of many demographic and socioeconomic variables, including age groups and lifestyle choices. It'll teach you more about the types of people who live in your area of interest and help you better understand the reasons why growth happened where it did."
    ]
   },
-  {
-   "cell_type": "code",
-   "execution_count": 22,
-   "metadata": {},
-   "outputs": [],
-   "source": [
-    "from arcgis.features.enrich_data import enrich_layer"
-   ]
-  },
   {
    "cell_type": "markdown",
    "metadata": {},