03 - Time-Series Visualization using bokeh.ipynb

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  {
   "cell_type": "markdown",
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   "source": [
    "# Time-Series Visualization using bokeh/plotly - Neerja Doshi\n",
    "For this assignment, Bokeh has been used as the package for creating plots."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 1,
   "metadata": {},
   "outputs": [
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "/Users/neerjadoshi/anaconda2/lib/python2.7/site-packages/bokeh/util/deprecation.py:34: BokehDeprecationWarning: \n",
      "The bokeh.charts API has moved to a separate 'bkcharts' package.\n",
      "\n",
      "This compatibility shim will remain until Bokeh 1.0 is released.\n",
      "After that, if you want to use this API you will have to install\n",
      "the bkcharts package explicitly.\n",
      "\n",
      "  warn(message)\n"
     ]
    }
   ],
   "source": [
    "# import packages\n",
    "import pandas as pd\n",
    "import numpy as np\n",
    "from bokeh.plotting import figure, show, output_file, output_notebook\n",
    "from bokeh.palettes import Spectral11, colorblind, Inferno, BuGn, brewer\n",
    "import datetime\n",
    "from bokeh.charts import HeatMap\n",
    "from bokeh.models import HoverTool, value, LabelSet, Legend, ColumnDataSource,LinearColorMapper,BasicTicker, PrintfTickFormatter, ColorBar"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 2,
   "metadata": {},
   "outputs": [
    {
     "data": {
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       "    }\n",
       "\n",
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       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>Date</th>\n",
       "      <th>Category</th>\n",
       "      <th>IncidntNum</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>2014-02-01</td>\n",
       "      <td>BURGLARY</td>\n",
       "      <td>506</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>2007-02-01</td>\n",
       "      <td>VANDALISM</td>\n",
       "      <td>531</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>2012-07-01</td>\n",
       "      <td>BURGLARY</td>\n",
       "      <td>522</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>2013-07-01</td>\n",
       "      <td>LARCENY/THEFT</td>\n",
       "      <td>3318</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>2010-08-01</td>\n",
       "      <td>VANDALISM</td>\n",
       "      <td>694</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "        Date       Category  IncidntNum\n",
       "0 2014-02-01       BURGLARY         506\n",
       "1 2007-02-01      VANDALISM         531\n",
       "2 2012-07-01       BURGLARY         522\n",
       "3 2013-07-01  LARCENY/THEFT        3318\n",
       "4 2010-08-01      VANDALISM         694"
      ]
     },
     "execution_count": 2,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# Load the data\n",
    "data = pd.read_csv('Monthly_Property_Crime_2005_to_2015.csv', parse_dates=['Date'])\n",
    "data.head()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 3,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "(Timestamp('2005-01-01 00:00:00'), Timestamp('2015-12-01 00:00:00'))"
      ]
     },
     "execution_count": 3,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "data.Date.min(), data.Date.max()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 4,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "STOLEN PROPERTY    132\n",
       "VEHICLE THEFT      132\n",
       "VANDALISM          132\n",
       "LARCENY/THEFT      132\n",
       "ARSON              132\n",
       "BURGLARY           132\n",
       "Name: Category, dtype: int64"
      ]
     },
     "execution_count": 4,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "data.Category.value_counts()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 5,
   "metadata": {},
   "outputs": [
    {
     "data": {
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       "    }\n",
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       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>Date</th>\n",
       "      <th>Category</th>\n",
       "      <th>IncidntNum</th>\n",
       "      <th>Year</th>\n",
       "      <th>Month</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>2014-02-01</td>\n",
       "      <td>BURGLARY</td>\n",
       "      <td>506</td>\n",
       "      <td>2014</td>\n",
       "      <td>2</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>2007-02-01</td>\n",
       "      <td>VANDALISM</td>\n",
       "      <td>531</td>\n",
       "      <td>2007</td>\n",
       "      <td>2</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>2012-07-01</td>\n",
       "      <td>BURGLARY</td>\n",
       "      <td>522</td>\n",
       "      <td>2012</td>\n",
       "      <td>7</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>2013-07-01</td>\n",
       "      <td>LARCENY/THEFT</td>\n",
       "      <td>3318</td>\n",
       "      <td>2013</td>\n",
       "      <td>7</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>2010-08-01</td>\n",
       "      <td>VANDALISM</td>\n",
       "      <td>694</td>\n",
       "      <td>2010</td>\n",
       "      <td>8</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "        Date       Category  IncidntNum  Year  Month\n",
       "0 2014-02-01       BURGLARY         506  2014      2\n",
       "1 2007-02-01      VANDALISM         531  2007      2\n",
       "2 2012-07-01       BURGLARY         522  2012      7\n",
       "3 2013-07-01  LARCENY/THEFT        3318  2013      7\n",
       "4 2010-08-01      VANDALISM         694  2010      8"
      ]
     },
     "execution_count": 5,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "data['Year'] = data.Date.apply(lambda x: x.year)\n",
    "data['Month'] = data.Date.apply(lambda x: x.month)\n",
    "data.head()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 6,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
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       "\n",
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       "<table border=\"1\" class=\"dataframe\">\n",
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       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>Date</th>\n",
       "      <th>Category</th>\n",
       "      <th>IncidntNum</th>\n",
       "      <th>Year</th>\n",
       "      <th>Month</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>198</th>\n",
       "      <td>2005-01-01</td>\n",
       "      <td>ARSON</td>\n",
       "      <td>21</td>\n",
       "      <td>2005</td>\n",
       "      <td>1</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>215</th>\n",
       "      <td>2005-02-01</td>\n",
       "      <td>ARSON</td>\n",
       "      <td>17</td>\n",
       "      <td>2005</td>\n",
       "      <td>2</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>36</th>\n",
       "      <td>2005-03-01</td>\n",
       "      <td>ARSON</td>\n",
       "      <td>19</td>\n",
       "      <td>2005</td>\n",
       "      <td>3</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>313</th>\n",
       "      <td>2005-04-01</td>\n",
       "      <td>ARSON</td>\n",
       "      <td>24</td>\n",
       "      <td>2005</td>\n",
       "      <td>4</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>261</th>\n",
       "      <td>2005-05-01</td>\n",
       "      <td>ARSON</td>\n",
       "      <td>13</td>\n",
       "      <td>2005</td>\n",
       "      <td>5</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
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      "text/plain": [
       "          Date Category  IncidntNum  Year  Month\n",
       "198 2005-01-01    ARSON          21  2005      1\n",
       "215 2005-02-01    ARSON          17  2005      2\n",
       "36  2005-03-01    ARSON          19  2005      3\n",
       "313 2005-04-01    ARSON          24  2005      4\n",
       "261 2005-05-01    ARSON          13  2005      5"
      ]
     },
     "execution_count": 6,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "burglary = data[data.Category == 'BURGLARY'].sort_values(['Date'])\n",
    "stolen_property = data[data.Category == 'STOLEN PROPERTY'].sort_values(['Date'])\n",
    "vehicle_theft = data[data.Category == 'VEHICLE THEFT'].sort_values(['Date'])\n",
    "vandalism = data[data.Category == 'VANDALISM'].sort_values(['Date'])\n",
    "larceny = data[data.Category == 'LARCENY/THEFT'].sort_values(['Date'])\n",
    "arson = data[data.Category == 'ARSON'].sort_values(['Date'])\n",
    "arson.head()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 7,
   "metadata": {},
   "outputs": [
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    "output_notebook()"
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   "source": [
    "### Bar Chart\n",
    "This is used to analyse the average crimes per month. All the months have between 600-800 average crimes, with February being the least."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 8,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
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       "    .dataframe thead tr:only-child th {\n",
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       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>Month</th>\n",
       "      <th>IncidntNum</th>\n",
       "      <th>Year</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>1</td>\n",
       "      <td>702.560606</td>\n",
       "      <td>2010.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>2</td>\n",
       "      <td>620.409091</td>\n",
       "      <td>2010.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>3</td>\n",
       "      <td>707.712121</td>\n",
       "      <td>2010.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>4</td>\n",
       "      <td>700.060606</td>\n",
       "      <td>2010.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>5</td>\n",
       "      <td>708.378788</td>\n",
       "      <td>2010.0</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "   Month  IncidntNum    Year\n",
       "0      1  702.560606  2010.0\n",
       "1      2  620.409091  2010.0\n",
       "2      3  707.712121  2010.0\n",
       "3      4  700.060606  2010.0\n",
       "4      5  708.378788  2010.0"
      ]
     },
     "execution_count": 8,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "temp_df = data.groupby(['Month']).mean().reset_index()\n",
    "temp_df.head()"
   ]
  },
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     "metadata": {},
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    }
   ],
   "source": [
    "TOOLS = \"hover,save,pan,box_zoom,reset,wheel_zoom,tap\"\n",
    "p = figure(plot_height=350,\n",
    "#     plot_width=1000,\n",
    "    title=\"Average Number of Crimes by Month\",\n",
    "    tools=TOOLS,\n",
    "    toolbar_location='above')\n",
    "\n",
    "p.vbar(x=temp_df.Month, top=temp_df.IncidntNum, width=0.9)\n",
    "\n",
    "p.y_range.start = 0\n",
    "p.x_range.range_padding = 0.1\n",
    "p.xgrid.grid_line_color = None\n",
    "p.axis.minor_tick_line_color = None\n",
    "p.outline_line_color = None\n",
    "p.xaxis.axis_label = 'Month'\n",
    "p.yaxis.axis_label = 'Average Crimes'\n",
    "p.select_one(HoverTool).tooltips = [\n",
    "    ('month', '@x'),\n",
    "    ('Number of crimes', '@top'),\n",
    "]\n",
    "output_file(\"barchart.html\", title=\"barchart\")\n",
    "show(p)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### Line Chart\n",
    "This plot shows the trend in number of crimes over the years. It can be seen that the crime rate decreased from 2005-2010, with 2010 having the lowest crime rate. From then on, it has kept increasing steadily with 2015 having the highest number of crimes."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 10,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style>\n",
       "    .dataframe thead tr:only-child th {\n",
       "        text-align: right;\n",
       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: left;\n",
       "    }\n",
       "\n",
       "    .dataframe tbody tr th {\n",
       "        vertical-align: top;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>Year</th>\n",
       "      <th>IncidntNum</th>\n",
       "      <th>Month</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>2005</td>\n",
       "      <td>58368</td>\n",
       "      <td>468</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>2006</td>\n",
       "      <td>50150</td>\n",
       "      <td>468</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>2007</td>\n",
       "      <td>46023</td>\n",
       "      <td>468</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>2008</td>\n",
       "      <td>45647</td>\n",
       "      <td>468</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>2009</td>\n",
       "      <td>44633</td>\n",
       "      <td>468</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "   Year  IncidntNum  Month\n",
       "0  2005       58368    468\n",
       "1  2006       50150    468\n",
       "2  2007       46023    468\n",
       "3  2008       45647    468\n",
       "4  2009       44633    468"
      ]
     },
     "execution_count": 10,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "temp_df = data.groupby(['Year']).sum().reset_index()\n",
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   "source": [
    "TOOLS = 'save,pan,box_zoom,reset,wheel_zoom,hover'\n",
    "p = figure(title=\"Year-wise total number of crimes\", y_axis_type=\"linear\", plot_height = 400,\n",
    "           tools = TOOLS, plot_width = 800)\n",
    "p.xaxis.axis_label = 'Year'\n",
    "p.yaxis.axis_label = 'Total Crimes'\n",
    "p.circle(2010, temp_df.IncidntNum.min(), size = 10, color = 'red')\n",
    "\n",
    "p.line(temp_df.Year, temp_df.IncidntNum,line_color=\"purple\", line_width = 3)\n",
    "p.select_one(HoverTool).tooltips = [\n",
    "    ('year', '@x'),\n",
    "    ('Number of crimes', '@y'),\n",
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    "\n",
    "output_file(\"line_chart.html\", title=\"Line Chart\")\n",
    "show(p)"
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  {
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   "source": [
    "### Stacked bar chart\n",
    "This chart explores the distribution of crimes among the various categories over the years. In particular, larceny/theft are the most frequently occuring crimes, while stolen property occur the least. 2005 saw a high number of vehicle thefts, which reduced quite a bit subsequently."
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      "text/html": [
       "<div>\n",
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       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th>Category</th>\n",
       "      <th>Year</th>\n",
       "      <th>ARSON</th>\n",
       "      <th>BURGLARY</th>\n",
       "      <th>LARCENY/THEFT</th>\n",
       "      <th>STOLEN PROPERTY</th>\n",
       "      <th>VANDALISM</th>\n",
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       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>2005</td>\n",
       "      <td>231</td>\n",
       "      <td>7071</td>\n",
       "      <td>25319</td>\n",
       "      <td>540</td>\n",
       "      <td>7013</td>\n",
       "      <td>18194</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>2006</td>\n",
       "      <td>240</td>\n",
       "      <td>7004</td>\n",
       "      <td>27352</td>\n",
       "      <td>575</td>\n",
       "      <td>7688</td>\n",
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       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>2007</td>\n",
       "      <td>246</td>\n",
       "      <td>5454</td>\n",
       "      <td>25770</td>\n",
       "      <td>527</td>\n",
       "      <td>7566</td>\n",
       "      <td>6460</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>2008</td>\n",
       "      <td>248</td>\n",
       "      <td>5679</td>\n",
       "      <td>25807</td>\n",
       "      <td>518</td>\n",
       "      <td>7342</td>\n",
       "      <td>6053</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>2009</td>\n",
       "      <td>222</td>\n",
       "      <td>5379</td>\n",
       "      <td>25585</td>\n",
       "      <td>660</td>\n",
       "      <td>7604</td>\n",
       "      <td>5183</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "Category  Year  ARSON  BURGLARY  LARCENY/THEFT  STOLEN PROPERTY  VANDALISM  \\\n",
       "0         2005    231      7071          25319              540       7013   \n",
       "1         2006    240      7004          27352              575       7688   \n",
       "2         2007    246      5454          25770              527       7566   \n",
       "3         2008    248      5679          25807              518       7342   \n",
       "4         2009    222      5379          25585              660       7604   \n",
       "\n",
       "Category  VEHICLE THEFT  \n",
       "0                 18194  \n",
       "1                  7291  \n",
       "2                  6460  \n",
       "3                  6053  \n",
       "4                  5183  "
      ]
     },
     "execution_count": 12,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "wide = data.pivot(index='Date', columns='Category', values='IncidntNum')\n",
    "wide.reset_index(inplace=True)\n",
    "wide['Year'] = wide.Date.apply(lambda x: x.year)\n",
    "wide['Month'] = wide.Date.apply(lambda x: x.month)\n",
    "\n",
    "temp_df = wide.groupby(['Year']).sum().reset_index()\n",
    "temp_df.head()\n",
    "cats = ['ARSON','BURGLARY','LARCENY/THEFT','STOLEN PROPERTY','VANDALISM','VEHICLE THEFT'] \n",
    "temp_df.drop(['Month'], axis = 1, inplace=True)\n",
    "temp_df.head()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 13,
   "metadata": {},
   "outputs": [
    {
     "data": {
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       "\n",
       "\n",
       "    <div class=\"bk-root\">\n",
       "        <div class=\"bk-plotdiv\" id=\"e514fbb4-e605-4265-9904-1c7166a63776\"></div>\n",
       "    </div>\n",
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       "  \n",
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       "    if (typeof (root._bokeh_timeout) === \"undefined\" || force === true) {\n",
       "      root._bokeh_timeout = Date.now() + 0;\n",
       "      root._bokeh_failed_load = false;\n",
       "    }\n",
       "  \n",
       "    var NB_LOAD_WARNING = {'data': {'text/html':\n",
       "       \"<div style='background-color: #fdd'>\\n\"+\n",
       "       \"<p>\\n\"+\n",
       "       \"BokehJS does not appear to have successfully loaded. If loading BokehJS from CDN, this \\n\"+\n",
       "       \"may be due to a slow or bad network connection. Possible fixes:\\n\"+\n",
       "       \"</p>\\n\"+\n",
       "       \"<ul>\\n\"+\n",
       "       \"<li>re-rerun `output_notebook()` to attempt to load from CDN again, or</li>\\n\"+\n",
       "       \"<li>use INLINE resources instead, as so:</li>\\n\"+\n",
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       "       \"<code>\\n\"+\n",
       "       \"from bokeh.resources import INLINE\\n\"+\n",
       "       \"output_notebook(resources=INLINE)\\n\"+\n",
       "       \"</code>\\n\"+\n",
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       "        delete root._bokeh_onload_callbacks\n",
       "      }\n",
       "      console.info(\"Bokeh: all callbacks have finished\");\n",
       "    }\n",
       "  \n",
       "    function load_libs(js_urls, callback) {\n",
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       "      if (root._bokeh_is_loading > 0) {\n",
       "        console.log(\"Bokeh: BokehJS is being loaded, scheduling callback at\", now());\n",
       "        return null;\n",
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       "      if (js_urls == null || js_urls.length === 0) {\n",
       "        run_callbacks();\n",
       "        return null;\n",
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       "      console.log(\"Bokeh: BokehJS not loaded, scheduling load and callback at\", now());\n",
       "      root._bokeh_is_loading = js_urls.length;\n",
       "      for (var i = 0; i < js_urls.length; i++) {\n",
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       "          if (root._bokeh_is_loading === 0) {\n",
       "            console.log(\"Bokeh: all BokehJS libraries loaded\");\n",
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       "        s.onerror = function() {\n",
       "          console.warn(\"failed to load library \" + url);\n",
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       "        console.log(\"Bokeh: injecting script tag for BokehJS library: \", url);\n",
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       "      console.log(\"Bokeh: ERROR: autoload.js configured with elementid 'e514fbb4-e605-4265-9904-1c7166a63776' but no matching script tag was found. \")\n",
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       "    }\n",
       "  \n",
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       "      function(Bokeh) {\n",
       "        (function() {\n",
       "          var fn = function() {\n",
       "            var docs_json = {\"47ad6e89-e4d1-4cd7-9d65-4cb050cfa203\":{\"roots\":{\"references\":[{\"attributes\":{\"fields\":[\"ARSON\",\"BURGLARY\",\"LARCENY/THEFT\"]},\"id\":\"1aa86656-e1ec-487a-9a46-c33f98f618d7\",\"type\":\"Stack\"},{\"attributes\":{\"label\":{\"value\":\"LARCENY/THEFT\"},\"renderers\":[{\"id\":\"df2855ae-8bc1-46a5-a797-1faf31591833\",\"type\":\"GlyphRenderer\"}]},\"id\":\"d74b8b38-0451-4eb8-9562-7761aa9699e6\",\"type\":\"LegendItem\"},{\"attributes\":{\"below\":[{\"id\":\"e608d43c-2df6-43d0-8b56-af70ff7478a6\",\"type\":\"LinearAxis\"}],\"left\":[{\"id\":\"60fb9d57-df4a-4455-9ce1-854b00e9775e\",\"type\":\"LinearAxis\"}],\"outline_line_color\":{\"value\":null},\"plot_width\":800,\"renderers\":[{\"id\":\"e608d43c-2df6-43d0-8b56-af70ff7478a6\",\"type\":\"LinearAxis\"},{\"id\":\"f874a4bd-a11c-4a0a-9549-f1c23b3016db\",\"type\":\"Grid\"},{\"id\":\"60fb9d57-df4a-4455-9ce1-854b00e9775e\",\"type\":\"LinearAxis\"},{\"id\":\"91b78f9f-1194-473a-91e3-e502ed4912fc\",\"type\":\"Grid\"},{\"id\":\"8c88710d-0311-4858-a864-197af47f3e5f\",\"type\":\"BoxAnnotation\"},{\"id\":\"073c7d47-cb9a-4839-a90b-55fa88cca970\",\"type\":\"Legend\"},{\"id\":\"a05075ba-612a-45e1-8565-445fbe307ba8\",\"type\":\"GlyphRenderer\"},{\"id\":\"4361abc9-3d08-4824-840a-f8580eaafa20\",\"type\":\"GlyphRenderer\"},{\"id\":\"df2855ae-8bc1-46a5-a797-1faf31591833\",\"type\":\"GlyphRenderer\"},{\"id\":\"0516c4e8-6771-4df2-ae30-4ddd670b9bc2\",\"type\":\"GlyphRenderer\"},{\"id\":\"7b49b617-c6d2-4230-bae8-289812688777\",\"type\":\"GlyphRenderer\"},{\"id\":\"7d386a64-388d-4a03-90a1-e3467cbce552\",\"type\":\"GlyphRenderer\"}],\"title\":{\"id\":\"901ffb7e-2650-4867-b55c-67a4948a9a1b\",\"type\":\"Title\"},\"toolbar\":{\"id\":\"6bee4670-2422-4665-92b2-02d96a49dd0d\",\"type\":\"Toolbar\"},\"toolbar_location\":\"above\",\"x_range\":{\"id\":\"1918296b-19ab-4e68-9d03-a5a0ce463f40\",\"type\":\"DataRange1d\"},\"x_scale\":{\"id\":\"075b4807-7ed9-45f2-9950-3a04656c831b\",\"type\":\"LinearScale\"},\"y_range\":{\"id\":\"860bf451-a4ea-4b9a-b0e0-013e93d012a9\",\"type\":\"DataRange1d\"},\"y_scale\":{\"id\":\"a6082202-73a1-4dae-a169-b2ca3483ac29\",\"type\":\"LinearScale\"}},\"id\":\"6f8c99bb-ae21-4ab1-adf7-c66aa8281fd4\",\"subtype\":\"Figure\",\"type\":\"Plot\"},{\"attributes\":{\"bottom\":{\"expr\":{\"id\":\"1be39a1f-7198-49c8-9a54-ff89a71508cf\",\"type\":\"Stack\"}},\"fill_color\":{\"value\":\"#e6ab02\"},\"line_color\":{\"value\":\"#e6ab02\"},\"top\":{\"expr\":{\"id\":\"6013de6f-6c65-47a8-865c-d09248f56c00\",\"type\":\"Stack\"}},\"width\":{\"value\":0.9},\"x\":{\"field\":\"Year\"}},\"id\":\"edd32877-a0a5-425f-8dac-175cb604cf35\",\"type\":\"VBar\"},{\"attributes\":{\"source\":{\"id\":\"31dc074d-7924-45e2-a842-971c3e102c05\",\"type\":\"ColumnDataSource\"}},\"id\":\"539ae159-762f-4ba4-98a0-1164d1f5cd7e\",\"type\":\"CDSView\"},{\"attributes\":{\"active_drag\":\"auto\",\"active_inspect\":\"auto\",\"active_scroll\":\"auto\",\"active_tap\":\"auto\",\"tools\":[{\"id\":\"6e73dff3-71df-4536-aad0-7ca7c6447331\",\"type\":\"SaveTool\"},{\"id\":\"1bebddcd-6094-4a47-8336-305aa953ab11\",\"type\":\"PanTool\"},{\"id\":\"4349ccfb-6bfa-4b04-af0c-1e164aad1c1e\",\"type\":\"BoxZoomTool\"},{\"id\":\"e37aa4e5-9f7d-4d91-b9b0-d6a672dd031b\",\"type\":\"ResetTool\"},{\"id\":\"15dfd17e-97f0-448e-bdfc-281b37bcab37\",\"type\":\"WheelZoomTool\"},{\"id\":\"cce3e00a-03a8-4fca-bdf3-ac75c8971f55\",\"type\":\"TapTool\"}]},\"id\":\"6bee4670-2422-4665-92b2-02d96a49dd0d\",\"type\":\"Toolbar\"},{\"attributes\":{\"data_source\":{\"id\":\"31dc074d-7924-45e2-a842-971c3e102c05\",\"type\":\"ColumnDataSource\"},\"glyph\":{\"id\":\"6492de09-7b5d-4334-8133-4dcbfb6fad3b\",\"type\":\"VBar\"},\"hover_glyph\":null,\"muted_glyph\":null,\"nonselection_glyph\":{\"id\":\"25c55c24-6b4b-47b2-883b-26dded138acd\",\"type\":\"VBar\"},\"selection_glyph\":null,\"view\":{\"id\":\"2773c324-4916-4f90-bfef-659eb9d3b66f\",\"type\":\"CDSView\"}},\"id\":\"df2855ae-8bc1-46a5-a797-1faf31591833\",\"type\":\"GlyphRenderer\"},{\"attributes\":{\"bottom\":{\"expr\":{\"id\":\"0f44e406-77fe-4dc6-8432-02847b2bcacd\",\"type\":\"Stack\"}},\"fill_alpha\":{\"value\":0.1},\"fill_color\":{\"value\":\"#1f77b4\"},\"line_alpha\":{\"value\":0.1},\"line_color\":{\"value\":\"#1f77b4\"},\"top\":{\"expr\":{\"id\":\"012665a0-7be6-4627-9fae-ba6f86394018\",\"type\":\"Stack\"}},\"width\":{\"value\":0.9},\"x\":{\"field\":\"Year\"}},\"id\":\"b7d94cc8-98ad-4208-bf64-83cb3bdaa979\",\"type\":\"VBar\"},{\"attributes\":{\"bottom\":{\"expr\":{\"id\":\"a5a12464-fc99-4c33-ac20-d623d727f8c9\",\"type\":\"Stack\"}},\"fill_alpha\":{\"value\":0.1},\"fill_color\":{\"value\":\"#1f77b4\"},\"line_alpha\":{\"value\":0.1},\"line_color\":{\"value\":\"#1f77b4\"},\"top\":{\"expr\":{\"id\":\"9868e416-63fe-47dc-996e-5188667f2f04\",\"type\":\"Stack\"}},\"width\":{\"value\":0.9},\"x\":{\"field\":\"Year\"}},\"id\":\"fe060a74-9ad9-41cc-8132-6e66910bc57c\",\"type\":\"VBar\"},{\"attributes\":{\"source\":{\"id\":\"31dc074d-7924-45e2-a842-971c3e102c05\",\"type\":\"ColumnDataSource\"}},\"id\":\"b2d81da1-2b3c-4e10-8d1d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     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "TOOLS = \"save,pan,box_zoom,reset,wheel_zoom,tap\"\n",
    "\n",
    "source = ColumnDataSource(data=temp_df)\n",
    "p = figure( plot_width=800, title=\"Category wise count of crimes by year\",toolbar_location='above', tools=TOOLS)\n",
    "colors = brewer['Dark2'][6]\n",
    "\n",
    "p.vbar_stack(cats, x='Year', width=0.9, color=colors, source=source,\n",
    "             legend=[value(x) for x in cats])\n",
    "\n",
    "p.y_range.start = 0\n",
    "p.x_range.range_padding = 0.1\n",
    "p.xgrid.grid_line_color = None\n",
    "p.axis.minor_tick_line_color = None\n",
    "p.outline_line_color = None\n",
    "p.xaxis.axis_label = 'Year'\n",
    "p.yaxis.axis_label = 'Total Crimes'\n",
    "p.legend.location = \"top_left\"\n",
    "p.legend.orientation = \"horizontal\"\n",
    "\n",
    "output_file(\"stacked_bar.html\", title=\"Stacked Bar Chart\")\n",
    "\n",
    "show(p)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### Heat Map\n",
    "The heat map shows the total number of crimes by month and year, with darker colours represnting higher number of crimes. Months in 2015 have the highest total while the least are in the some months in 2009 and 2010."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 14,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style>\n",
       "    .dataframe thead tr:only-child th {\n",
       "        text-align: right;\n",
       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: left;\n",
       "    }\n",
       "\n",
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       "        vertical-align: top;\n",
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       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>Year</th>\n",
       "      <th>Month</th>\n",
       "      <th>IncidntNum</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>2005</td>\n",
       "      <td>1</td>\n",
       "      <td>4991</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>2005</td>\n",
       "      <td>2</td>\n",
       "      <td>4166</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>2005</td>\n",
       "      <td>3</td>\n",
       "      <td>4815</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>2005</td>\n",
       "      <td>4</td>\n",
       "      <td>4711</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>2005</td>\n",
       "      <td>5</td>\n",
       "      <td>5120</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "   Year  Month  IncidntNum\n",
       "0  2005      1        4991\n",
       "1  2005      2        4166\n",
       "2  2005      3        4815\n",
       "3  2005      4        4711\n",
       "4  2005      5        5120"
      ]
     },
     "execution_count": 14,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "temp_df = data.groupby(['Year', 'Month']).sum().reset_index()\n",
    "# temp_df['Month_Category'] = pd.concat([temp_df['Month'], temp_df['Category']], axis = 1)\n",
    "temp_df.head()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 15,
   "metadata": {},
   "outputs": [
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   ],
   "source": [
    "TOOLS = \"hover,save,pan,box_zoom,reset,wheel_zoom,tap\"\n",
    "hm = figure(title=\"Month-Year wise crimes\", tools=TOOLS, toolbar_location='above')\n",
    "\n",
    "source = ColumnDataSource(temp_df)\n",
    "colors = brewer['BuGn'][9]\n",
    "colors = colors[::-1]\n",
    "mapper = LinearColorMapper(\n",
    "    palette=colors, low=temp_df.IncidntNum.min(), high=temp_df.IncidntNum.max())\n",
    "hm.rect(x=\"Year\", y=\"Month\",width=2,height=1,source = source,  \n",
    "    fill_color={\n",
    "        'field': 'IncidntNum',\n",
    "        'transform': mapper\n",
    "    },\n",
    "    line_color=None)\n",
    "color_bar = ColorBar(\n",
    "    color_mapper=mapper,\n",
    "    major_label_text_font_size=\"10pt\",\n",
    "    ticker=BasicTicker(desired_num_ticks=len(colors)),\n",
    "    formatter=PrintfTickFormatter(),\n",
    "    label_standoff=6,\n",
    "    border_line_color=None,\n",
    "    location=(0, 0))\n",
    "\n",
    "hm.add_layout(color_bar, 'right')\n",
    "hm.xaxis.axis_label = 'Year'\n",
    "hm.yaxis.axis_label = 'Month'\n",
    "hm.select_one(HoverTool).tooltips = [\n",
    "    ('Year', '@Year'),('Month', '@Month'), ('Number of Crimes', '@IncidntNum')\n",
    "]\n",
    "\n",
    "output_file(\"heatmap.html\", title=\"Heat Map\")\n",
    "\n",
    "show(hm)  # open a browser"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### Multiline Plot\n",
    "This plot shows the distribution of crimes across categories over the years. This plot shows information similar to the stacked bar chart, except that here it is easier to note that arson and property theft amount to almost the same amount of crimes every year. Similarly, vehicle theft(except for 2005), vandalism and burglary have very similar patterns. Only larceny/theft is increasing with every passing year and its count is much higher than any of the other types of crimes."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 17,
   "metadata": {},
   "outputs": [
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       "       \"may be due to a slow or bad network connection. Possible fixes:\\n\"+\n",
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       "        }\n",
       "      } else if (Date.now() < root._bokeh_timeout) {\n",
       "        setTimeout(display_loaded, 100)\n",
       "      }\n",
       "    }\n",
       "  \n",
       "  \n",
       "    function run_callbacks() {\n",
       "      try {\n",
       "        root._bokeh_onload_callbacks.forEach(function(callback) { callback() });\n",
       "      }\n",
       "      finally {\n",
       "        delete root._bokeh_onload_callbacks\n",
       "      }\n",
       "      console.info(\"Bokeh: all callbacks have finished\");\n",
       "    }\n",
       "  \n",
       "    function load_libs(js_urls, callback) {\n",
       "      root._bokeh_onload_callbacks.push(callback);\n",
       "      if (root._bokeh_is_loading > 0) {\n",
       "        console.log(\"Bokeh: BokehJS is being loaded, scheduling callback at\", now());\n",
       "        return null;\n",
       "      }\n",
       "      if (js_urls == null || js_urls.length === 0) {\n",
       "        run_callbacks();\n",
       "        return null;\n",
       "      }\n",
       "      console.log(\"Bokeh: BokehJS not loaded, scheduling load and callback at\", now());\n",
       "      root._bokeh_is_loading = js_urls.length;\n",
       "      for (var i = 0; i < js_urls.length; i++) {\n",
       "        var url = js_urls[i];\n",
       "        var s = document.createElement('script');\n",
       "        s.src = url;\n",
       "        s.async = false;\n",
       "        s.onreadystatechange = s.onload = function() {\n",
       "          root._bokeh_is_loading--;\n",
       "          if (root._bokeh_is_loading === 0) {\n",
       "            console.log(\"Bokeh: all BokehJS libraries loaded\");\n",
       "            run_callbacks()\n",
       "          }\n",
       "        };\n",
       "        s.onerror = function() {\n",
       "          console.warn(\"failed to load library \" + url);\n",
       "        };\n",
       "        console.log(\"Bokeh: injecting script tag for BokehJS library: \", url);\n",
       "        document.getElementsByTagName(\"head\")[0].appendChild(s);\n",
       "      }\n",
       "    };var element = document.getElementById(\"0cacc9a2-6aca-47a2-96e5-6ad97eb9089f\");\n",
       "    if (element == null) {\n",
       "      console.log(\"Bokeh: ERROR: autoload.js configured with elementid '0cacc9a2-6aca-47a2-96e5-6ad97eb9089f' but no matching script tag was found. \")\n",
       "      return false;\n",
       "    }\n",
       "  \n",
       "    var js_urls = [];\n",
       "  \n",
       "    var inline_js = [\n",
       "      function(Bokeh) {\n",
       "        (function() {\n",
       "          var fn = function() {\n",
       "            var docs_json = 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       "      function(Bokeh) {\n",
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       "        console.log(\"Bokeh: BokehJS failed to load within specified timeout.\");\n",
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       "  \n",
       "    if (root._bokeh_is_loading === 0) {\n",
       "      console.log(\"Bokeh: BokehJS loaded, going straight to plotting\");\n",
       "      run_inline_js();\n",
       "    } else {\n",
       "      load_libs(js_urls, function() {\n",
       "        console.log(\"Bokeh: BokehJS plotting callback run at\", now());\n",
       "        run_inline_js();\n",
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       "</script>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "TOOLS = 'crosshair,save,pan,box_zoom,reset,wheel_zoom'\n",
    "p = figure(title=\"Category-wise crimes through Time\", y_axis_type=\"linear\",x_axis_type='datetime', tools = TOOLS)\n",
    "\n",
    "p.line(burglary['Date'], burglary.IncidntNum, legend=\"burglary\", line_color=\"purple\", line_width = 3)\n",
    "p.line(stolen_property['Date'], stolen_property.IncidntNum, legend=\"stolen_property\", line_color=\"blue\", line_width = 3)\n",
    "\n",
    "p.line(vehicle_theft['Date'], vehicle_theft.IncidntNum, legend=\"vehicle_theft\", line_color = 'coral', line_width = 3)\n",
    "\n",
    "p.line(larceny['Date'], larceny.IncidntNum, legend=\"larceny\", line_color='green', line_width = 3)\n",
    "\n",
    "p.line(vandalism['Date'], vandalism.IncidntNum, legend=\"vandalism\", line_color=\"gold\", line_width = 3)\n",
    "\n",
    "p.line(arson['Date'], arson.IncidntNum, legend=\"arson\", line_color=\"magenta\",line_width = 3)\n",
    "\n",
    "p.legend.location = \"top_left\"\n",
    "\n",
    "p.xaxis.axis_label = 'Year'\n",
    "p.yaxis.axis_label = 'Count'\n",
    "\n",
    "output_file(\"multiline_plot.html\", title=\"Multi Line Plot\")\n",
    "\n",
    "show(p)  # open a browser"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {
    "collapsed": true
   },
   "outputs": [],
   "source": []
  }
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