del temp_df

gumdropsteve · Mar 23, 2020 · d304742 · d304742
1 parent 3e2f3b3
commit d304742
Showing 1 changed file with 44 additions and 47 deletions.
diff --git a/taxi_dashboard.ipynb b/taxi_dashboard.ipynb
@@ -14,7 +14,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 1,
+   "execution_count": 3,
    "metadata": {},
    "outputs": [
     {
@@ -1258,20 +1258,7 @@
       "text/html": [
        "\n",
        "<link rel=\"stylesheet\" href=\"https://code.jquery.com/ui/1.10.4/themes/smoothness/jquery-ui.css\">\n",
-       "<style>div.bk-hbox {\n",
-       "    display: flex;\n",
-       "    justify-content: center;\n",
-       "}\n",
-       "\n",
-       "div.bk-hbox div.bk-plot {\n",
-       "    padding: 8px;\n",
-       "}\n",
-       "\n",
-       "div.bk-hbox div.bk-data-table {\n",
-       "    padding: 20px;\n",
-       "}\n",
-       "\n",
-       "div.hololayout {\n",
+       "<style>div.hololayout {\n",
        "  display: flex;\n",
        "  align-items: center;\n",
        "  margin: 0;\n",
@@ -1364,6 +1351,19 @@
        "  margin-left: 0.5em;\n",
        "  margin-right: 0.5em;\n",
        "}\n",
+       "\n",
+       "div.bk-hbox {\n",
+       "    display: flex;\n",
+       "    justify-content: center;\n",
+       "}\n",
+       "\n",
+       "div.bk-hbox div.bk-plot {\n",
+       "    padding: 8px;\n",
+       "}\n",
+       "\n",
+       "div.bk-hbox div.bk-data-table {\n",
+       "    padding: 20px;\n",
+       "}\n",
        "</style>\n",
        "\n",
        "\n",
@@ -2300,10 +2300,10 @@
     {
      "data": {
       "text/plain": [
-       "'/home/jupyter-winston/turbo-telegram/data/nyc_taxi_*'"
+       "'/jupyterhub-homes/winston@blazingdb.com/turbo-telegram/data/nyc_taxi_*'"
       ]
      },
-     "execution_count": 1,
+     "execution_count": 3,
      "metadata": {},
      "output_type": "execute_result"
     }
@@ -2348,15 +2348,15 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 2,
+   "execution_count": 4,
    "metadata": {},
    "outputs": [
     {
      "name": "stdout",
      "output_type": "stream",
      "text": [
-      "CPU times: user 1.46 s, sys: 394 ms, total: 1.85 s\n",
-      "Wall time: 981 ms\n"
+      "CPU times: user 1.48 s, sys: 378 ms, total: 1.86 s\n",
+      "Wall time: 2.57 s\n"
      ]
     },
     {
@@ -2490,7 +2490,7 @@
        "1911985         25.5    0.5      0.5         1.2           0.0           0.3  "
       ]
      },
-     "execution_count": 2,
+     "execution_count": 4,
      "metadata": {},
      "output_type": "execute_result"
     }
@@ -2500,7 +2500,8 @@
     "# create base table\n",
     "col_types = ['int', 'date64', 'date64', 'int', 'float64', 'float64', 'float64', 'int', 'str', 'float64', \n",
     "             'float64', 'int', 'float64', 'float64', 'float64', 'float64', 'float64', 'float64', 'float64']\n",
-    "bc.create_table('big_taxi', '/home/jupyter-winston/turbo-telegram/data/nyc_taxi*.csv', dtype=col_types, header=0)\n",
+    "bc.create_table('big_taxi', path, dtype=col_types, header=0)\n",
+    "\n",
     "# what's it look like? \n",
     "bc.sql('select * from big_taxi').tail(3)"
    ]
@@ -2514,7 +2515,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 3,
+   "execution_count": 18,
    "metadata": {},
    "outputs": [],
    "source": [
@@ -2536,17 +2537,11 @@
     "    # return sorted tuple (works best w/ widgets)\n",
     "    return tuple(unique)\n",
     "\n",
-    "# make temp dataframe from time query + passenger_count \n",
-    "temp_df = bc.sql(time_table.replace('SELECT', 'SELECT passenger_count,'))\n",
-    "\n",
     "# tag day, month, year & passenger count values for widgets\n",
-    "dy_vals = unique_sorted_values(temp_df.days)\n",
-    "mo_vals = unique_sorted_values(temp_df.months)\n",
-    "yr_vals = unique_sorted_values(temp_df.years)\n",
-    "rider_vals = unique_sorted_values(temp_df.passenger_count)\n",
-    "\n",
-    "# forget temp df\n",
-    "del temp_df\n",
+    "dy_vals = unique_sorted_values(bc.sql('select dayofmonth(tpep_pickup_datetime) days from big_taxi').days)\n",
+    "mo_vals = unique_sorted_values(bc.sql('select month(tpep_pickup_datetime) months from big_taxi').months)\n",
+    "yr_vals = unique_sorted_values(bc.sql('select year(tpep_pickup_datetime) years from big_taxi').years)\n",
+    "rider_vals = unique_sorted_values(bc.sql('select passenger_count from big_taxi').passenger_count)\n",
     "\n",
     "# dropdown days\n",
     "dropdown_day = widgets.SelectMultiple(value=dy_vals, options=dy_vals, description='Days of Month')\n",
@@ -2588,8 +2583,10 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 4,
-   "metadata": {},
+   "execution_count": 7,
+   "metadata": {
+    "scrolled": true
+   },
    "outputs": [],
    "source": [
     "# build outputs (each will have it's own tab)\n",
@@ -2609,7 +2606,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 5,
+   "execution_count": 8,
    "metadata": {},
    "outputs": [],
    "source": [
@@ -2762,7 +2759,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 6,
+   "execution_count": 9,
    "metadata": {},
    "outputs": [],
    "source": [
@@ -2842,7 +2839,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 7,
+   "execution_count": 10,
    "metadata": {},
    "outputs": [],
    "source": [
@@ -2874,13 +2871,13 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 8,
+   "execution_count": 11,
    "metadata": {},
    "outputs": [
     {
      "data": {
       "application/vnd.jupyter.widget-view+json": {
-       "model_id": "9d6b70a7c8b3461ab1b63e488d7da8bf",
+       "model_id": "5c7aeef9d03f43c4bc446964f2263a5d",
        "version_major": 2,
        "version_minor": 0
       },
@@ -2894,7 +2891,7 @@
     {
      "data": {
       "application/vnd.jupyter.widget-view+json": {
-       "model_id": "f260a8b095bc42fba9a5ae3d3e13e265",
+       "model_id": "fe6bdfce7d0144b5bbe45fc497b50db1",
        "version_major": 2,
        "version_minor": 0
       },
@@ -2912,13 +2909,13 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 9,
+   "execution_count": 12,
    "metadata": {},
    "outputs": [
     {
      "data": {
       "application/vnd.jupyter.widget-view+json": {
-       "model_id": "be30379be50043cebb22061fbef0f1fa",
+       "model_id": "17830fd6ea3f4d38bc4a34a04ef35bdc",
        "version_major": 2,
        "version_minor": 0
       },
@@ -2937,9 +2934,9 @@
  ],
  "metadata": {
   "kernelspec": {
-   "display_name": "Python 3",
+   "display_name": "RAPIDS Stable",
    "language": "python",
-   "name": "python3"
+   "name": "rapids-stable"
   },
   "language_info": {
    "codemirror_mode": {
@@ -2951,9 +2948,9 @@
    "name": "python",
    "nbconvert_exporter": "python",
    "pygments_lexer": "ipython3",
-   "version": "3.6.7"
+   "version": "3.7.6"
   }
  },
  "nbformat": 4,
- "nbformat_minor": 2
+ "nbformat_minor": 4
 }