{
 "cells": [
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# Project 2 report: Scotland Road Traffic Analysis\n",
    "Author:  Liyi Fan,  Dongrui Shen,  Zhier Chen,  Peixuan He"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Setup"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 1,
   "metadata": {},
   "outputs": [],
   "source": [
    "#  pip install folium  # uncomment it to install folium"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 2,
   "metadata": {},
   "outputs": [],
   "source": [
    "# Load the required modules\n",
    "import pandas as pd\n",
    "import numpy as np\n",
    "import matplotlib.pyplot as plt\n",
    "plt.style.use('seaborn')  # set plot style\n",
    "import seaborn as sns\n",
    "from matplotlib import cm\n",
    "from IPython.core.display import HTML\n",
    "import folium\n",
    "import helper.data as dt  # `helper` module contains all wrapped functions we used to assist our analysis\n",
    "import helper.visual as vs\n",
    "import helper.decision as dc"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Overview"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "The main purpose of this report is to estimate the traffic volumes for the past 20 years and help DfT determine where to put counters next year.\n",
    "\n",
    "The report is organized as follows. In the following section, we firstly preprocessed the manual counts dataset and give a briefly description about it. Next, we focused on setting up a criterion to measure the busyness of road links. We described the standard traffic volume formula used by the UK government and proposed two estimated traffic volume formulae. We calculated the traffic volume and gave the ranking of road links for each of the two estimated traffic volume formulae. For the second estimation method, we also provided interactive codes so that you can find out any number of \"valuable\" counting points that you want in the map."
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Dataset details"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Data we processed in this report is from the Department for Transport (DfT), which contains the data for all manual counts performed on Scottish roads from 2000 to 2019. Each row represents the observation data for a specific hour in different days at different counting point in a specific direction. \n",
    "\n",
    "\n",
    "#### Preprocess manual count data\n",
    "We firstly wrote a function `read_data` to convert the manual counting data file to a well-presented dataframe. In this dataframe, we added a column named `name_type` to indicate the road categories and dropped irrelevant columns."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 3,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>count_point_id</th>\n",
       "      <th>direction_of_travel</th>\n",
       "      <th>year</th>\n",
       "      <th>count_date</th>\n",
       "      <th>hour</th>\n",
       "      <th>local_authority_id</th>\n",
       "      <th>local_authority_name</th>\n",
       "      <th>road_name</th>\n",
       "      <th>road_type</th>\n",
       "      <th>start_junction_road_name</th>\n",
       "      <th>end_junction_road_name</th>\n",
       "      <th>latitude</th>\n",
       "      <th>longitude</th>\n",
       "      <th>link_length_km</th>\n",
       "      <th>link_length_miles</th>\n",
       "      <th>pedal_cycles</th>\n",
       "      <th>two_wheeled_motor_vehicles</th>\n",
       "      <th>cars_and_taxis</th>\n",
       "      <th>buses_and_coaches</th>\n",
       "      <th>lgvs</th>\n",
       "      <th>all_hgvs</th>\n",
       "      <th>all_motor_vehicles</th>\n",
       "      <th>name_type</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>931907</td>\n",
       "      <td>N</td>\n",
       "      <td>2019</td>\n",
       "      <td>2019-06-17</td>\n",
       "      <td>18</td>\n",
       "      <td>29</td>\n",
       "      <td>City of Edinburgh</td>\n",
       "      <td>U</td>\n",
       "      <td>Minor</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>55.967806</td>\n",
       "      <td>-3.30758</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>8</td>\n",
       "      <td>2</td>\n",
       "      <td>290</td>\n",
       "      <td>5</td>\n",
       "      <td>20</td>\n",
       "      <td>0</td>\n",
       "      <td>317</td>\n",
       "      <td>U</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>931907</td>\n",
       "      <td>S</td>\n",
       "      <td>2019</td>\n",
       "      <td>2019-06-17</td>\n",
       "      <td>13</td>\n",
       "      <td>29</td>\n",
       "      <td>City of Edinburgh</td>\n",
       "      <td>U</td>\n",
       "      <td>Minor</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>55.967806</td>\n",
       "      <td>-3.30758</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>258</td>\n",
       "      <td>4</td>\n",
       "      <td>36</td>\n",
       "      <td>7</td>\n",
       "      <td>306</td>\n",
       "      <td>U</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>931907</td>\n",
       "      <td>N</td>\n",
       "      <td>2019</td>\n",
       "      <td>2019-06-17</td>\n",
       "      <td>9</td>\n",
       "      <td>29</td>\n",
       "      <td>City of Edinburgh</td>\n",
       "      <td>U</td>\n",
       "      <td>Minor</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>55.967806</td>\n",
       "      <td>-3.30758</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>5</td>\n",
       "      <td>1</td>\n",
       "      <td>270</td>\n",
       "      <td>5</td>\n",
       "      <td>44</td>\n",
       "      <td>8</td>\n",
       "      <td>328</td>\n",
       "      <td>U</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>931907</td>\n",
       "      <td>S</td>\n",
       "      <td>2019</td>\n",
       "      <td>2019-06-17</td>\n",
       "      <td>12</td>\n",
       "      <td>29</td>\n",
       "      <td>City of Edinburgh</td>\n",
       "      <td>U</td>\n",
       "      <td>Minor</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>55.967806</td>\n",
       "      <td>-3.30758</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>2</td>\n",
       "      <td>2</td>\n",
       "      <td>266</td>\n",
       "      <td>4</td>\n",
       "      <td>50</td>\n",
       "      <td>9</td>\n",
       "      <td>331</td>\n",
       "      <td>U</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>931907</td>\n",
       "      <td>S</td>\n",
       "      <td>2019</td>\n",
       "      <td>2019-06-17</td>\n",
       "      <td>10</td>\n",
       "      <td>29</td>\n",
       "      <td>City of Edinburgh</td>\n",
       "      <td>U</td>\n",
       "      <td>Minor</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>55.967806</td>\n",
       "      <td>-3.30758</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>4</td>\n",
       "      <td>0</td>\n",
       "      <td>247</td>\n",
       "      <td>8</td>\n",
       "      <td>35</td>\n",
       "      <td>8</td>\n",
       "      <td>298</td>\n",
       "      <td>U</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>"
      ],
      "text/plain": [
       "<IPython.core.display.HTML object>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "# Read and preprocess manual count data\n",
    "df = dt.read_data(\"dft_rawcount_region_id_3.csv\")\n",
    "# Pretty print dataframe in jupyter notebook\n",
    "dt.view(df)  # display the first 5 rows"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "#### How many counting points did DfT set?\n",
    "In order to get a sense of how counting points were set for the past 20 years, we defined a function `counter_stat` to count the number of counting points each year and considered two types of groups separately. One is the major roads and the other one is the minor roads. "
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 17,
   "metadata": {},
   "outputs": [
    {
     "data": {
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\n",
      "text/plain": [
       "<Figure size 1296x360 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "# Compute how many counting points were set on major roads and minor roads each year.\n",
    "# Make a stacked bar plot to show trend.\n",
    "cpdf = vs.counter_stat(df)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "We firstly observed that the number of counting points for each year increased with fluctuations from 2000 to 2009, and then decreased from 2012 to 2017, but more than doubled in 2018. For major roads, the number of counting points firstly around 300 to 430 during year 2000 to 2009, but then suddenly decreased in 2010 and kept it around 150 to 300, then decreased again in 2013, which failed to less then 100. It finally turned back to around 150 in year 2018 and 2019. However, for minor roads, it's interesting to find that the number of counting points was increasing with slightly fluctuation and exceeded it for major roads in 2010."
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Problem: Which road link is the busiest?"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Counters should be sent to the most \"valuable\" places. We regarded \"valuable\" here as the \"busiest\" places with \"effective\" time. We considered \"busiest\" not only by counting the daily average number of vehicles observed by each counting point per year, but also considered the link length. By combining these two factors together, we rasied the definition of traffic volume:\n",
    "$$\n",
    "\\mathrm{Traffic_{\\,CP}} = \\mathrm{AADN_{\\,CP}} \\times \\mathrm{Length_{\\,link}} \\times 365.\n",
    "$$\n",
    "\n",
    "We first considered \"effective\" as data available. Alternatively, we explained \"effective\" by using the following formula calculating penalized traffic volume:\n",
    "\n",
    "\\begin{align}\n",
    "\\mathrm{avg_{\\,weighted}} &= \\sum_{i=1}^n \\frac{i}{\\sum_{i=1}^n i}{\\mathrm{Traffic^{\\,2020-i}_{\\,CP}}}. \\\\\n",
    "&= \\frac{2}{(1+n)n}\\mathrm{{Traffic^{\\,2020-n}_{\\,CP}}} + \\frac{4}{(1+n)n}\\mathrm{{Traffic^{\\,2020-(n-1)}_{\\,CP}}} + ... + \\frac{2n}{(1+n)n}\\mathrm{{Traffic^{\\,2020-1}_{\\,CP}}}\n",
    "\\end{align}\n",
    "Here, n means the number of years we choose.\n",
    "\n",
    "We mainly divided this problem into three parts: \n",
    "1. The first part analyzed the daily average observation of vehicles and pedal cycles in different type of roads: A, B, M, C, U, which can give us a general understanding of the total vehicle numbers in each road and the trend for the passing 20 years. \n",
    "2. In the second part, we analyzed it much \"deeper\". We analyzed the daily average observation based on each counting point. We emulated the model given by UK government which can be used to calculate the traffic volumes, which can help us determine which road is busier.\n",
    "3. In the final part, we further modified the model we used in part 2 by measuring the busy degree with the penalized traffic volume. We provide an interactive code at the end to help DfT find out those busy road sections."
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "#### Remark on daily traffic volume\n",
    "\n",
    "UK government usually calculates the yearly traffic volume for each counting point as:\n",
    "\n",
    "$$\n",
    "\\mathrm{Traffic_{\\,CP}} = \\mathrm{AADF_{\\,CP}} \\times \\mathrm{Length_{\\,link}} \\times 365,\n",
    "$$\n",
    "\n",
    "also, calculating the traffic volume of all counting points in one year as: $\\mathrm{Total\\,traffic} = \\sum \\mathrm{Traffic_{\\,CP}}$. [2]\n",
    "\n",
    "Here AADF is the annual average daily flows, but calculated with information from a network of automatic traffic counters (ATCs), which we cannot accessed. Thus, we modified the first formula to:\n",
    "\n",
    "$$\n",
    "\\mathrm{Traffic_{\\,CP}} = \\mathrm{AADN_{\\,CP}} \\times \\mathrm{Length_{\\,link}} \\times 365.\n",
    "$$\n",
    "\n",
    "where AADN is the annual average daily number of all vehicles.\n",
    "\n",
    "Since minor roads in our data set do not have link length, we calculated as the following for minor roads: $\n",
    "\\mathrm{Traffic_{\\,CP}} = \\mathrm{AADN_{\\,CP}}  \\times 365.\n",
    "$"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### Part 1: Annual average daily vehicle number (AADN)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "In this part, we will explore how the number of vehicles for different road categories changed by year.\n",
    "\n",
    "#### Road categories\n",
    "\n",
    "According to the road classification defined by UK government [1], we regarded M-roads and A-roads as our major roads, while B, C and U-roads as minor roads in our report.\n",
    "\n",
    "- Major roads: Includes motorways (M-roads) and all A-roads. These roads usually have high traffic flows and are often the main arteries to major destinations.\n",
    "- Minor Roads: These are B and C classified roads and unclassified roads.\n",
    "\n",
    "The number of vehicles can be quite different to pedal cycles in different types of roads. For example, we cannot ride bicycles on motorways while some kinds of vehicles may not possible to pass on some very small roads. Thus, we considered the daily observation into two parts to see how busy it was for different type of roads: one is all the vehicles but pedal cycles and the other one is pedal cycles."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 5,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 1008x720 with 2 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "# Annual daily vehicle number by road categories\n",
    "vs.AADN_cat(df)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "For both daily average observation for motor vehicles and pedal cycles, the trends of B-roads, C-roads and U-roads were quite similar. Also, the observation in all of the roads for both vehicles and pedal cycles rised in 2018, which is probably because the doubled number of counting points in 2018.\n",
    "\n",
    "For the daily average observation for motor vehicles, M-roads and A-roads were larger than that of another three roads from 2000 to 2019. However, M-roads did not have any records from 2010 to 2013. We pointed this as the \"missing value\" in the graph. The observation number also decreased and kept in a level for A-roads during 2010 to 2013. This is probably the consequence of the suddenly decreased number of counting point during 2010 to 2013, which has been pointed out in the Overview section. In addition, the daily observation also had a sharp decrease for A-roads in 2015.\n",
    "\n",
    "For the daily average observation for pedal cycles, the number of observation was quite less than which for vehicles. It's not surprisingly to find that the observation was almost 0 in M-roads. Moreover, we can observe that the daily observation on A-roads was always the largest, except for year 2014, 2017 and 2019. The observation value on the A-roads increased by nearly 5 times."
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### Part 2:  Annual average traffic volume\n",
    "\n",
    "In this part, we analyzed \"how busy\" of different links in each road by comparing the annual average traffic volume of different links. It should be noted that all comparisons are based on road sections without missing data. Instead of calculating the total traffic volume, we used the average of existing value to measure the magnitude of traffic volume for a year."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 19,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th>year</th>\n",
       "      <th>2000</th>\n",
       "      <th>2001</th>\n",
       "      <th>2002</th>\n",
       "      <th>2003</th>\n",
       "      <th>2004</th>\n",
       "      <th>2005</th>\n",
       "      <th>2006</th>\n",
       "      <th>2007</th>\n",
       "      <th>2008</th>\n",
       "      <th>2009</th>\n",
       "      <th>2010</th>\n",
       "      <th>2011</th>\n",
       "      <th>2012</th>\n",
       "      <th>2013</th>\n",
       "      <th>2014</th>\n",
       "      <th>2015</th>\n",
       "      <th>2016</th>\n",
       "      <th>2017</th>\n",
       "      <th>2018</th>\n",
       "      <th>2019</th>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>count_point_id</th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>700</th>\n",
       "      <td>NaN</td>\n",
       "      <td>85469903.8</td>\n",
       "      <td>NaN</td>\n",
       "      <td>83318988.0</td>\n",
       "      <td>92689888.5</td>\n",
       "      <td>NaN</td>\n",
       "      <td>94817604.9</td>\n",
       "      <td>96088600.6</td>\n",
       "      <td>94093452.2</td>\n",
       "      <td>NaN</td>\n",
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       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>95157310.4</td>\n",
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       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
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       "    </tr>\n",
       "    <tr>\n",
       "      <th>701</th>\n",
       "      <td>NaN</td>\n",
       "      <td>55976400.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>63288810.0</td>\n",
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       "      <td>59034078.0</td>\n",
       "      <td>68828634.0</td>\n",
       "      <td>55493505.0</td>\n",
       "      <td>60724539.0</td>\n",
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       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>702</th>\n",
       "      <td>NaN</td>\n",
       "      <td>28501974.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>27488880.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>29713482.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>28400796.0</td>\n",
       "      <td>NaN</td>\n",
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       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>31352040.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>703</th>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>9535698.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>10020235.5</td>\n",
       "      <td>NaN</td>\n",
       "      <td>13789291.2</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>14668780.6</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>704</th>\n",
       "      <td>NaN</td>\n",
       "      <td>8098160.1</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>9160682.4</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>11370195.3</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>"
      ],
      "text/plain": [
       "<IPython.core.display.HTML object>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "# Caculate the traffic volume of all road links with data for one certain year.\n",
    "dt.view(dt.TV(df))"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "We then made the following line chart, which can show the trend of the annual average traffic volume (in terms of counting points) for major roads and minor roads during 2000 to 2019. When calculating the annual average estimation, we only used the traffic volume for those counting points that had data (not NAN), then divided the number of those counting points."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 7,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 1008x360 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "dfs = vs.TV_stat(df)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "We can see that the annual traffic volume estimation for major road is much larger than that in minor road. Also, by using the log-number of our traffic volume estimation, we can see the changes clearer. The most obvious decreasing was happened in 2010. If you look back for the counting points number before, you may find that the number of counting points in 2010 have been halved.\n",
    "\n",
    "Next, we used the annual \"average\" number to estimate the \"busy level\" of each counting point. Similarly, we only counted for those year having data, and then subtracted the number of years with NAN data when calculating the denominator. Since we did not consider the length of minor roads, we gave the top 5 busiest counting points in major roads and minor roads separately."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 8,
   "metadata": {},
   "outputs": [],
   "source": [
    "cpdf = dt.cp_info(df).set_index(['count_point_id'])  # get counting points information"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 9,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "The top 5 busiest counting points for major roads: \n"
     ]
    },
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
       "        vertical-align: middle;\n",
       "    }\n",
       "\n",
       "    .dataframe tbody tr th {\n",
       "        vertical-align: top;\n",
       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: right;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>TV</th>\n",
       "      <th>road_name</th>\n",
       "      <th>name_type</th>\n",
       "      <th>latitude</th>\n",
       "      <th>longitude</th>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>count_point_id</th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>700</th>\n",
       "      <td>9.166225e+07</td>\n",
       "      <td>M8</td>\n",
       "      <td>M</td>\n",
       "      <td>55.927220</td>\n",
       "      <td>-3.441936</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>10768</th>\n",
       "      <td>8.376794e+07</td>\n",
       "      <td>A90</td>\n",
       "      <td>A</td>\n",
       "      <td>56.426074</td>\n",
       "      <td>-3.217554</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>20700</th>\n",
       "      <td>9.241957e+07</td>\n",
       "      <td>M8</td>\n",
       "      <td>M</td>\n",
       "      <td>55.837029</td>\n",
       "      <td>-3.925646</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>90101</th>\n",
       "      <td>9.264999e+07</td>\n",
       "      <td>M8</td>\n",
       "      <td>M</td>\n",
       "      <td>56.000000</td>\n",
       "      <td>-4.000000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>90102</th>\n",
       "      <td>8.916664e+07</td>\n",
       "      <td>M8</td>\n",
       "      <td>M</td>\n",
       "      <td>56.000000</td>\n",
       "      <td>-4.000000</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "                          TV road_name name_type   latitude  longitude\n",
       "count_point_id                                                        \n",
       "700             9.166225e+07        M8         M  55.927220  -3.441936\n",
       "10768           8.376794e+07       A90         A  56.426074  -3.217554\n",
       "20700           9.241957e+07        M8         M  55.837029  -3.925646\n",
       "90101           9.264999e+07        M8         M  56.000000  -4.000000\n",
       "90102           8.916664e+07        M8         M  56.000000  -4.000000"
      ]
     },
     "execution_count": 9,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "mtemp = dt.TV(df, type='Major') # compute traffic volume\n",
    "# find the top 5 busiest counting points on major roads\n",
    "busylink = mtemp.apply(lambda row: np.mean(row[~np.isnan(row)]), \n",
    "                      axis=1).sort_values(ascending=False).to_frame(name='TV').head()\n",
    "m_cpls = busylink.index.tolist()\n",
    "# merge the counting points information with the TV\n",
    "busym = pd.concat([busylink,cpdf.loc[m_cpls,]],axis=1).sort_values(by='count_point_id')\n",
    "print(\"The top 5 busiest counting points for major roads: \")\n",
    "busym"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 10,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
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     "text": [
      "The top 5 busiest counting points for minor roads: \n"
     ]
    },
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       "                          TV road_name name_type   latitude  longitude\n",
       "count_point_id                                                        \n",
       "811379          8.950530e+06         C         C  55.937762  -3.318158\n",
       "812146          6.538245e+06     B7071         B  55.794729  -4.056474\n",
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    "ntemp = dt.TV(df, type='Minor') # compute traffic volume\n",
    "# find the top 5 busiest counting points on minor roads\n",
    "busylink = ntemp.apply(lambda row: np.mean(row[~np.isnan(row)]), \n",
    "                      axis=1).sort_values(ascending=False).to_frame(name='TV').head()\n",
    "n_cpls = busylink.index.tolist()\n",
    "# merge the counting points information with the TV\n",
    "busyn = pd.concat([busylink,cpdf.loc[n_cpls,]],axis=1).sort_values(by='count_point_id')\n",
    "print(\"The top 5 busiest counting points for minor roads: \")\n",
    "busyn"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 11,
   "metadata": {
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   "cell_type": "code",
   "execution_count": 12,
   "metadata": {
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     "execution_count": 12,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "vs.counterloc(df,n_cpls) # make visualization for the busiest counting points on minor roads"
   ]
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    "It's interesting to find that we calculated top 5 busiest counting points for major roads, but there are only 4 points in the map. That is because there are two counting points with different id but same longitude and latitude.  This finding may slightly effect our analyzation, since our calculation for average busy level for each counting point is based on its counting point id. \n",
    "\n",
    "Thus, if the counting point has a large traffic volumn for these two years but a low traffic volumn for next two years, also, it has been counted as two different counting point id, then we may found that the average traffic volumn for the first counting point id is large but low for next. This is not what in actual happened.\n",
    "\n",
    "However, we considered this as the special circumstance for their \"large change\", which is deserved to counted as a counting point. Thus, if the higher one is large enough to be counted for the counting point it is also reasonable. If the different id but same longitude and latitude happen for place that always has similar traffic volume, for example, 90101 and 90102 here, then no other consideration is needed."
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   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### Part 3:  Penalized annual average traffic volume"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "In this part, we designed an interactive model to help decide where to set counters. Note that we used the penalized annual average traffic volume here. The number of the year that we would like to use for our data and the number of counters that we hope to have for major roads and minor roads can be decided by inputting the following box. The outputs contain two tables and a map. The first two tables tell us directly where the counters should be set on major roads and minor roads respectively. The map shows points in two colors. The blue points show the location of counting points on minor roads while green points show it for major roads."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 13,
   "metadata": {
    "scrolled": true
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     "name": "stdout",
     "output_type": "stream",
     "text": [
      "How many years of statistics are taken into consideration (an integer less than or equal to 20): 20\n",
      "how many counters are set on major road: 20\n",
      "how many counters are set on minor road: 10\n",
      "the counters on major roads should be set at: \n",
      "     latitude  longitude\n",
      "0   55.866081  -4.226141\n",
      "1   55.869385  -4.243721\n",
      "2   55.866178  -4.271506\n",
      "3   56.000000  -4.000000\n",
      "4   55.808790  -4.059896\n",
      "5   56.013029  -3.403426\n",
      "6   55.870078  -4.254950\n",
      "7   55.898721  -3.218572\n",
      "8   55.867126  -4.365624\n",
      "9   55.860952  -4.404642\n",
      "10  55.961201  -3.289672\n",
      "11  55.866537  -4.362152\n",
      "12  55.940097  -3.319134\n",
      "13  55.938568  -3.384722\n",
      "14  55.861038  -4.105808\n",
      "15  55.867747  -4.210061\n",
      "16  55.789408  -4.036542\n",
      "17  55.849440  -4.301682\n",
      "18  55.931735  -3.089956\n",
      "19  55.921269  -3.306716\n",
      "\n",
      "\n",
      "the counters on minor roads should be set at: \n",
      "    latitude  longitude\n",
      "0  56.018319  -3.792509\n",
      "1  55.743214  -4.203172\n",
      "2  55.939678  -3.992063\n",
      "3  55.850801  -3.975211\n",
      "4  55.907177  -3.226675\n",
      "5  55.930565  -3.285837\n",
      "6  57.140592  -2.138878\n",
      "7  57.161224  -2.226463\n",
      "8  55.934978  -4.148725\n",
      "9  55.960887  -4.008693\n"
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    "# The aim is to find out where we should set counters\n",
    "# It is according to average number of vehicles travelling per day in a given year (aadf)\n",
    "# Two parts are considered seperately, major roads and minor roads\n",
    "# The influence of data in the past 20 years are decided by weighted average method and how many data are used can be controled \n",
    "# How many counters set on major roads and minor roads can also controled manually. \n",
    "\n",
    "# aadf calculated by weighted average method\n",
    "dfmajor_aadf, dfminor_aadf = dc.weighted_average_method(df)\n",
    "\n",
    "# where to send counters\n",
    "cmajor, cminor = dc.show_counters(dfmajor_aadf, dfminor_aadf)\n",
    "\n",
    "# plot the locations needing counters\n",
    "dc.plot_map(cmajor, cminor)\n"
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    "When all of the 20 years'statistics are used, 20 counters on major roads are needed and 10 counters on minor roads are needed, from the map, the conclusion can be drawn that:\n",
    "1. When considering the major roads, most counters are set on M8 road, and they are collective.\n",
    "2. When considering the minor roads, the counters are scattered.\n",
    "3. Almost all of the locations are at city center or near the coast.\n",
    "\n",
    "For major roads, it is possibly to appear that many counting points are displayed on the same road. This is because the major roads are usually very long and are distributed in the city center or near the coast. However, for minor roads, since they do not have link length in our data set, there will only contain one counting point for each minor road. This may be the reason why they seem scattered on the map."
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   "execution_count": 20,
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     "text": [
      "how many counters are set on road M8: 20\n",
      "The counters on the major roads should be set at:\n",
      "     latitude  longitude\n",
      "0   55.866081  -4.226141\n",
      "1   55.869385  -4.243721\n",
      "2   55.866178  -4.271506\n",
      "3   56.000000  -4.000000\n",
      "4   55.870078  -4.254950\n",
      "5   55.867126  -4.365624\n",
      "6   55.860952  -4.404642\n",
      "7   55.866537  -4.362152\n",
      "8   55.861038  -4.105808\n",
      "9   55.867747  -4.210061\n",
      "10  55.849440  -4.301682\n",
      "11  55.863698  -4.355586\n",
      "12  55.854702  -4.270037\n",
      "13  55.873028  -4.191179\n",
      "14  55.863457  -4.121920\n",
      "15  55.849422  -4.312225\n",
      "16  55.927220  -3.441936\n",
      "17  56.000000  -4.000000\n",
      "18  55.861519  -4.435202\n",
      "19  55.849738  -4.285723\n"
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                function latLngPop(e) {
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                        .setLatLng(e.latlng)
                        .setContent("Latitude: " + e.latlng.lat.toFixed(4) +
                                    "<br>Longitude: " + e.latlng.lng.toFixed(4))
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</script> onload=\"this.contentDocument.open();this.contentDocument.write(atob(this.getAttribute('data-html')));this.contentDocument.close();\" allowfullscreen webkitallowfullscreen mozallowfullscreen></iframe></div></div>"
      ],
      "text/plain": [
       "<folium.folium.Map at 0x7fce3687ac70>"
      ]
     },
     "execution_count": 20,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# Set counters on M8 road\n",
    "dc.show_counters_M8(dfmajor_aadf)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "More specifically, since M8 seems really busy and many points should be set on it, we would like to draw the counting points displayed on M8 independently. Similarly, you can input the number you'd like to set the counting points on M8.\n",
    "\n",
    "Here we put 10 counting points on M8 on the above map, from which we can see that all counters are collective at the city center, but only one is far away."
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Other interesting facts\n",
    "\n",
    "#### Annual daily vehicle number by vehicle types"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 15,
   "metadata": {
    "scrolled": false
   },
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 1008x360 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "# Annual daily vehicle number statistics by vehicle types\n",
    "vs.AADN_veh(df,logscale=False)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "As the economy develops, people are more capable of choosing more comfortable transportation. So we can find that in the figure above, the number of cars and taxis was the largest for all 20 years in all of the vehicles, and the number of Igvs turned next.\n",
    "\n",
    "#### Major road length computation\n",
    "\n",
    "Assuming that every link (section) of a major road is associated to a counting point in the data, the length of major roads can be estimated by summing all of the relevant links to give a total road length. "
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 16,
   "metadata": {
    "scrolled": true
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Longest A-roads and M-roads\n"
     ]
    },
    {
     "data": {
      "text/html": [
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>road_name</th>\n",
       "      <th>road_length_km</th>\n",
       "      <th>road_length_miles</th>\n",
       "      <th>road_name</th>\n",
       "      <th>road_length_km</th>\n",
       "      <th>road_length_miles</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>A9</td>\n",
       "      <td>445.2</td>\n",
       "      <td>276.64</td>\n",
       "      <td>M74</td>\n",
       "      <td>122.49</td>\n",
       "      <td>76.11</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>A90</td>\n",
       "      <td>277.1</td>\n",
       "      <td>172.18</td>\n",
       "      <td>M8</td>\n",
       "      <td>99.30</td>\n",
       "      <td>61.68</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>A82</td>\n",
       "      <td>274.0</td>\n",
       "      <td>170.26</td>\n",
       "      <td>M90</td>\n",
       "      <td>54.60</td>\n",
       "      <td>33.92</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>A836</td>\n",
       "      <td>194.3</td>\n",
       "      <td>120.73</td>\n",
       "      <td>M9</td>\n",
       "      <td>46.40</td>\n",
       "      <td>28.83</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>A832</td>\n",
       "      <td>184.2</td>\n",
       "      <td>114.47</td>\n",
       "      <td>M77</td>\n",
       "      <td>39.01</td>\n",
       "      <td>24.25</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>"
      ],
      "text/plain": [
       "<IPython.core.display.HTML object>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "# Caculate the length of all roads (of one certain type) with data for one certain year.\n",
    "print(\"Longest A-roads and M-roads\")\n",
    "Alen = dt.roadlen(df,nametype='A').head().reset_index()\n",
    "Mlen = dt.roadlen(df,nametype='M').head().reset_index()\n",
    "dt.view(pd.concat([Alen,Mlen],axis=1))"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
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    "Accordidng to literature, our estimates for the length of major roads should be essentially correct. A9 is indeed the longest road in Scotland. However, instead of M74, M8 should be the longest motorways in Scotland. Besides, the literature length for M74 is 40 miles. This error could result from the fact that the counting point id of some road sections may be variant in different years. Using `count_point_id` to distinguish different road links might be convenient but sometimes it is not reliable."
   ]
  },
  {
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   "metadata": {},
   "source": [
    "## Reference\n",
    "\n",
    "[1]   [Road Lengths in Great Britain Statistics: Notes and Definitions](https://assets.publishing.service.gov.uk/government/uploads/system/uploads/attachment_data/file/860022/road-length-notes-definitions.pdf)\n",
    "\n",
    "[2]   [Road traffic estimates: Methodology note](https://assets.publishing.service.gov.uk/government/uploads/system/uploads/attachment_data/file/524848/annual-methodology-note.pdf)"
   ]
  }
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