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Procfile

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+web: voila --port=$PORT --no-browser --enable_nbextensions=True sf_crime.ipynb

requirements.txt

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+voila
+folium
+numpy
+pandas
+ipywidgets
+ipykernel
+matplotlib

sf_crime.ipynb

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+{
+ "cells": [
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "# Simple Dashboard of San Fransisco Crime Dataset with Voila"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 1,
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "import numpy as np\n",
+    "import pandas as pd\n",
+    "import folium"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 2,
+   "metadata": {},
+   "outputs": [
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "0.11.0\n"
+     ]
+    }
+   ],
+   "source": [
+    "print(folium.__version__)"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 3,
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "df = pd.read_csv('SF_crimes.csv')"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 4,
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "import ipywidgets as widgets\n",
+    "\n",
+    "style = {'description_width': 'initial'}\n",
+    "\n",
+    "limit_case = widgets.IntSlider(\n",
+    "    value=1000,\n",
+    "    min=100,\n",
+    "    max=5000,\n",
+    "    step=1,\n",
+    "    description='Max Number of Case:',\n",
+    "    disabled=False,\n",
+    "    style=style)"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 5,
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "unique_district = df.PdDistrict.unique()"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 6,
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "unique_cat = df.Category.unique()"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 7,
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "from ipywidgets import Layout\n",
+    "\n",
+    "\n",
+    "\n",
+    "district = widgets.SelectMultiple(\n",
+    "    options = unique_district.tolist(),\n",
+    "    value = ['BAYVIEW', 'NORTHERN'],\n",
+    "    #rows=10,\n",
+    "    description='District',\n",
+    "    disabled=False,\n",
+    "    layout = Layout(width='50%', height='80px')\n",
+    ")\n",
+    "\n",
+    "category = widgets.SelectMultiple(\n",
+    "    options = unique_cat.tolist(),\n",
+    "    value = ['VANDALISM', 'ASSAULT', 'ROBBERY'],\n",
+    "    #rows=10,\n",
+    "    description='Criminal Case',\n",
+    "    disabled=False,\n",
+    "    style=style,\n",
+    "    layout = Layout(width='50%', height='80px')\n",
+    ")\n",
+    "\n"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 8,
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "import matplotlib.pyplot as plt\n",
+    "from folium import plugins\n",
+    "\n",
+    "def update_map(district, category, limit):\n",
+    "    \n",
+    "    df = pd.read_csv('SF_crimes.csv')\n",
+    "    df = df.iloc[0:limit, :]\n",
+    "    \n",
+    "    latitude = 37.77\n",
+    "    longitude = -122.42\n",
+    "    \n",
+    "    df_dist = df.loc[df['PdDistrict'].isin(np.array(district))]\n",
+    "    df_category = df_dist.loc[df_dist['Category'].isin(np.array(category))]\n",
+    "    \n",
+    "    cat_unique = df_category['Category'].value_counts()\n",
+    "    cat_unique = cat_unique.reset_index()\n",
+    "    \n",
+    "    dist_unique = df_category['PdDistrict'].value_counts()\n",
+    "    dist_unique = dist_unique.reset_index()\n",
+    "    \n",
+    "    fig, (ax1, ax2) = plt.subplots(1, 2, figsize=(20,10))\n",
+    "\n",
+    "    # create map and display it\n",
+    "    sanfran_map = folium.Map(location=[latitude, longitude], zoom_start=12)\n",
+    "\n",
+    "    \n",
+    "    incidents = plugins.MarkerCluster().add_to(sanfran_map)\n",
+    "\n",
+    "# loop through the dataframe and add each data point to the mark cluster\n",
+    "    for lat, lng, label, in zip(df_category.Y, df_category.X, df_category.Category):\n",
+    "        folium.Marker(\n",
+    "        location=[lat, lng],\n",
+    "        icon=None,\n",
+    "        popup=label,\n",
+    "        ).add_to(incidents)\n",
+    "# show map\n",
+    "    display(sanfran_map)\n",
+    "    \n",
+    "    ax1.bar(cat_unique['index'], cat_unique['Category'])\n",
+    "    ax1.set_title('Amount of Criminal Case Based on Category')\n",
+    "    ax2.bar(dist_unique['index'], dist_unique['PdDistrict'])\n",
+    "    ax2.set_title('Amount of Criminal Case in Selected District')\n",
+    "    \n",
+    "    plt.show()"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 14,
+   "metadata": {
+    "scrolled": false
+   },
+   "outputs": [
+    {
+     "data": {
+      "application/vnd.jupyter.widget-view+json": {
+       "model_id": "c185e97d8e6e44bd99be6e236eee426a",
+       "version_major": 2,
+       "version_minor": 0
+      },
+      "text/plain": [
+       "interactive(children=(SelectMultiple(description='District', index=(0, 1), layout=Layout(height='80px', width=…"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    }
+   ],
+   "source": [
+    "\n",
+    "widgets.interactive(update_map, district = district, category = category, limit=limit_case)"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "metadata": {},
+   "outputs": [],
+   "source": []
+  }
+ ],
+ "metadata": {
+  "kernelspec": {
+   "display_name": "Python 3",
+   "language": "python",
+   "name": "python3"
+  },
+  "language_info": {
+   "codemirror_mode": {
+    "name": "ipython",
+    "version": 3
+   },
+   "file_extension": ".py",
+   "mimetype": "text/x-python",
+   "name": "python",
+   "nbconvert_exporter": "python",
+   "pygments_lexer": "ipython3",
+   "version": "3.7.6"
+  }
+ },
+ "nbformat": 4,
+ "nbformat_minor": 4
+}