traffic.ipynb

{
 "cells": [
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Analysis of road traffic\n",
    "\n",
    "Data fetched from [Department for Transport](https://roadtraffic.dft.gov.uk/downloads)\n",
    "\n",
    "Two datasets, Regional Traffic by vehicle type and local authority traffic are analysed."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 9,
   "metadata": {},
   "outputs": [],
   "source": [
    "# load libraries\n",
    "\n",
    "import pandas as pd\n",
    "import geopandas as gpd\n",
    "import matplotlib.pyplot as plt"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 10,
   "metadata": {},
   "outputs": [],
   "source": [
    "# regional analysis\n",
    "\n",
    "traffic_df = pd.read_csv('https://storage.googleapis.com/dft-statistics/road-traffic/downloads/data-gov-uk/region_traffic_by_vehicle_type.csv')\n",
    "\n",
    "la_traffic_df = pd.read_csv('https://storage.googleapis.com/dft-statistics/road-traffic/downloads/data-gov-uk/local_authority_traffic.csv')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 11,
   "metadata": {},
   "outputs": [],
   "source": [
    "# extract London\n",
    "\n",
    "london_ons = 'E12000007'\n",
    "london_traffic = traffic_df[traffic_df['ons_code'] == london_ons]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 12,
   "metadata": {},
   "outputs": [],
   "source": [
    "# extract local authority\n",
    "\n",
    "london_la_traffic = la_traffic_df[la_traffic_df['ONS_code'].str.contains('E09')]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 13,
   "metadata": {},
   "outputs": [],
   "source": [
    "# save traffic\n",
    "\n",
    "# london_traffic.to_csv('data/london_traffic.csv')\n",
    "# london_la_traffic.to_csv('data/london_traffic_boroughs.csv')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 14,
   "metadata": {},
   "outputs": [
    {
     "data": {
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       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>year</th>\n",
       "      <th>region_id</th>\n",
       "      <th>Region_name</th>\n",
       "      <th>ons_code</th>\n",
       "      <th>total_link_length_km</th>\n",
       "      <th>total_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",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>5</th>\n",
       "      <td>1993</td>\n",
       "      <td>6</td>\n",
       "      <td>London</td>\n",
       "      <td>E12000007</td>\n",
       "      <td>14350.44600</td>\n",
       "      <td>8916.95</td>\n",
       "      <td>272098090.7</td>\n",
       "      <td>358169320.0</td>\n",
       "      <td>15882514166</td>\n",
       "      <td>273427487.5</td>\n",
       "      <td>1928558767</td>\n",
       "      <td>640880245.8</td>\n",
       "      <td>19083549986</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>16</th>\n",
       "      <td>1994</td>\n",
       "      <td>6</td>\n",
       "      <td>London</td>\n",
       "      <td>E12000007</td>\n",
       "      <td>14384.45600</td>\n",
       "      <td>8938.09</td>\n",
       "      <td>278441721.3</td>\n",
       "      <td>369382328.5</td>\n",
       "      <td>16062810857</td>\n",
       "      <td>281778335.3</td>\n",
       "      <td>2010906197</td>\n",
       "      <td>623654797.9</td>\n",
       "      <td>19348532516</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>27</th>\n",
       "      <td>1995</td>\n",
       "      <td>6</td>\n",
       "      <td>London</td>\n",
       "      <td>E12000007</td>\n",
       "      <td>14417.87400</td>\n",
       "      <td>8958.85</td>\n",
       "      <td>283280561.7</td>\n",
       "      <td>359949803.2</td>\n",
       "      <td>16003118930</td>\n",
       "      <td>303703868.8</td>\n",
       "      <td>2086967051</td>\n",
       "      <td>608719496.9</td>\n",
       "      <td>19362459150</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>38</th>\n",
       "      <td>1996</td>\n",
       "      <td>6</td>\n",
       "      <td>London</td>\n",
       "      <td>E12000007</td>\n",
       "      <td>14447.84700</td>\n",
       "      <td>8977.48</td>\n",
       "      <td>290084450.6</td>\n",
       "      <td>375012094.2</td>\n",
       "      <td>16161494717</td>\n",
       "      <td>309645905.8</td>\n",
       "      <td>2055510242</td>\n",
       "      <td>647225102.1</td>\n",
       "      <td>19548888061</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>49</th>\n",
       "      <td>1997</td>\n",
       "      <td>6</td>\n",
       "      <td>London</td>\n",
       "      <td>E12000007</td>\n",
       "      <td>14488.18100</td>\n",
       "      <td>9002.54</td>\n",
       "      <td>289069781.3</td>\n",
       "      <td>398621461.7</td>\n",
       "      <td>16229364980</td>\n",
       "      <td>314989192.0</td>\n",
       "      <td>2105300362</td>\n",
       "      <td>646069123.6</td>\n",
       "      <td>19694345119</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>60</th>\n",
       "      <td>1998</td>\n",
       "      <td>6</td>\n",
       "      <td>London</td>\n",
       "      <td>E12000007</td>\n",
       "      <td>14522.65300</td>\n",
       "      <td>9023.96</td>\n",
       "      <td>274374870.4</td>\n",
       "      <td>406485726.5</td>\n",
       "      <td>16283310614</td>\n",
       "      <td>317415517.5</td>\n",
       "      <td>2113837083</td>\n",
       "      <td>698619750.2</td>\n",
       "      <td>19819668691</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>71</th>\n",
       "      <td>1999</td>\n",
       "      <td>6</td>\n",
       "      <td>London</td>\n",
       "      <td>E12000007</td>\n",
       "      <td>14568.80000</td>\n",
       "      <td>9052.63</td>\n",
       "      <td>280888940.9</td>\n",
       "      <td>443326861.0</td>\n",
       "      <td>16643703170</td>\n",
       "      <td>329838479.5</td>\n",
       "      <td>2224175485</td>\n",
       "      <td>673954979.6</td>\n",
       "      <td>20314998976</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>82</th>\n",
       "      <td>2000</td>\n",
       "      <td>6</td>\n",
       "      <td>London</td>\n",
       "      <td>E12000007</td>\n",
       "      <td>14603.80000</td>\n",
       "      <td>9074.38</td>\n",
       "      <td>285064173.2</td>\n",
       "      <td>443197633.7</td>\n",
       "      <td>16579095382</td>\n",
       "      <td>320750641.3</td>\n",
       "      <td>2246917172</td>\n",
       "      <td>698395128.5</td>\n",
       "      <td>20288355958</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>93</th>\n",
       "      <td>2001</td>\n",
       "      <td>6</td>\n",
       "      <td>London</td>\n",
       "      <td>E12000007</td>\n",
       "      <td>14640.30000</td>\n",
       "      <td>9097.06</td>\n",
       "      <td>303232071.7</td>\n",
       "      <td>470668954.5</td>\n",
       "      <td>16581792774</td>\n",
       "      <td>318642518.0</td>\n",
       "      <td>2275163005</td>\n",
       "      <td>683621998.7</td>\n",
       "      <td>20329889250</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>104</th>\n",
       "      <td>2002</td>\n",
       "      <td>6</td>\n",
       "      <td>London</td>\n",
       "      <td>E12000007</td>\n",
       "      <td>14678.82000</td>\n",
       "      <td>9121.00</td>\n",
       "      <td>311966481.9</td>\n",
       "      <td>471420594.9</td>\n",
       "      <td>16689506246</td>\n",
       "      <td>331580609.1</td>\n",
       "      <td>2253473670</td>\n",
       "      <td>669524447.4</td>\n",
       "      <td>20415505567</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>115</th>\n",
       "      <td>2003</td>\n",
       "      <td>6</td>\n",
       "      <td>London</td>\n",
       "      <td>E12000007</td>\n",
       "      <td>14712.91900</td>\n",
       "      <td>9142.18</td>\n",
       "      <td>337003066.6</td>\n",
       "      <td>533109216.0</td>\n",
       "      <td>16445284463</td>\n",
       "      <td>361644655.3</td>\n",
       "      <td>2434451988</td>\n",
       "      <td>673623035.9</td>\n",
       "      <td>20448113358</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>126</th>\n",
       "      <td>2004</td>\n",
       "      <td>6</td>\n",
       "      <td>London</td>\n",
       "      <td>E12000007</td>\n",
       "      <td>14681.11000</td>\n",
       "      <td>9122.42</td>\n",
       "      <td>324364786.1</td>\n",
       "      <td>498362587.9</td>\n",
       "      <td>16383732580</td>\n",
       "      <td>372359587.8</td>\n",
       "      <td>2428689194</td>\n",
       "      <td>680369836.5</td>\n",
       "      <td>20363513786</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>137</th>\n",
       "      <td>2005</td>\n",
       "      <td>6</td>\n",
       "      <td>London</td>\n",
       "      <td>E12000007</td>\n",
       "      <td>14741.26000</td>\n",
       "      <td>9159.79</td>\n",
       "      <td>365182556.1</td>\n",
       "      <td>521479996.5</td>\n",
       "      <td>16355486488</td>\n",
       "      <td>374086734.2</td>\n",
       "      <td>2483299940</td>\n",
       "      <td>688309252.0</td>\n",
       "      <td>20422662411</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>148</th>\n",
       "      <td>2006</td>\n",
       "      <td>6</td>\n",
       "      <td>London</td>\n",
       "      <td>E12000007</td>\n",
       "      <td>14745.60000</td>\n",
       "      <td>9162.49</td>\n",
       "      <td>392590748.0</td>\n",
       "      <td>533107655.5</td>\n",
       "      <td>16333921491</td>\n",
       "      <td>400324190.8</td>\n",
       "      <td>2743030224</td>\n",
       "      <td>671312085.1</td>\n",
       "      <td>20681695646</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>159</th>\n",
       "      <td>2007</td>\n",
       "      <td>6</td>\n",
       "      <td>London</td>\n",
       "      <td>E12000007</td>\n",
       "      <td>14783.53000</td>\n",
       "      <td>9186.06</td>\n",
       "      <td>364097173.3</td>\n",
       "      <td>569389179.1</td>\n",
       "      <td>16185087836</td>\n",
       "      <td>403123777.1</td>\n",
       "      <td>2823260460</td>\n",
       "      <td>660504083.6</td>\n",
       "      <td>20641365336</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>170</th>\n",
       "      <td>2008</td>\n",
       "      <td>6</td>\n",
       "      <td>London</td>\n",
       "      <td>E12000007</td>\n",
       "      <td>14795.80000</td>\n",
       "      <td>9193.68</td>\n",
       "      <td>385927089.6</td>\n",
       "      <td>493830858.6</td>\n",
       "      <td>16003801206</td>\n",
       "      <td>388955485.2</td>\n",
       "      <td>2678730010</td>\n",
       "      <td>668128210.0</td>\n",
       "      <td>20233445770</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>181</th>\n",
       "      <td>2009</td>\n",
       "      <td>6</td>\n",
       "      <td>London</td>\n",
       "      <td>E12000007</td>\n",
       "      <td>14800.60000</td>\n",
       "      <td>9196.67</td>\n",
       "      <td>389992003.9</td>\n",
       "      <td>490341866.6</td>\n",
       "      <td>16042986454</td>\n",
       "      <td>389755686.8</td>\n",
       "      <td>2561954570</td>\n",
       "      <td>626595728.6</td>\n",
       "      <td>20111634306</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>192</th>\n",
       "      <td>2010</td>\n",
       "      <td>6</td>\n",
       "      <td>London</td>\n",
       "      <td>E12000007</td>\n",
       "      <td>14819.10000</td>\n",
       "      <td>9208.16</td>\n",
       "      <td>395831005.8</td>\n",
       "      <td>452237351.5</td>\n",
       "      <td>15844171977</td>\n",
       "      <td>385705140.8</td>\n",
       "      <td>2535439802</td>\n",
       "      <td>634440723.3</td>\n",
       "      <td>19851994994</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>203</th>\n",
       "      <td>2011</td>\n",
       "      <td>6</td>\n",
       "      <td>London</td>\n",
       "      <td>E12000007</td>\n",
       "      <td>14800.10000</td>\n",
       "      <td>9196.36</td>\n",
       "      <td>392051038.7</td>\n",
       "      <td>435298565.1</td>\n",
       "      <td>15525387246</td>\n",
       "      <td>373973848.1</td>\n",
       "      <td>2529308379</td>\n",
       "      <td>631287597.6</td>\n",
       "      <td>19495255636</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>214</th>\n",
       "      <td>2012</td>\n",
       "      <td>6</td>\n",
       "      <td>London</td>\n",
       "      <td>E12000007</td>\n",
       "      <td>14814.53333</td>\n",
       "      <td>9205.32</td>\n",
       "      <td>395619606.2</td>\n",
       "      <td>409196420.1</td>\n",
       "      <td>15344905761</td>\n",
       "      <td>378519000.4</td>\n",
       "      <td>2552620710</td>\n",
       "      <td>655304368.4</td>\n",
       "      <td>19340546260</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>225</th>\n",
       "      <td>2013</td>\n",
       "      <td>6</td>\n",
       "      <td>London</td>\n",
       "      <td>E12000007</td>\n",
       "      <td>14829.63798</td>\n",
       "      <td>9214.71</td>\n",
       "      <td>374087538.8</td>\n",
       "      <td>391983185.9</td>\n",
       "      <td>15295412417</td>\n",
       "      <td>363094903.4</td>\n",
       "      <td>2618477754</td>\n",
       "      <td>645494588.8</td>\n",
       "      <td>19314462849</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>236</th>\n",
       "      <td>2014</td>\n",
       "      <td>6</td>\n",
       "      <td>London</td>\n",
       "      <td>E12000007</td>\n",
       "      <td>14842.84000</td>\n",
       "      <td>9222.91</td>\n",
       "      <td>411222525.8</td>\n",
       "      <td>407845063.5</td>\n",
       "      <td>15488605735</td>\n",
       "      <td>355378727.9</td>\n",
       "      <td>2785404035</td>\n",
       "      <td>643184910.0</td>\n",
       "      <td>19680418471</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>247</th>\n",
       "      <td>2015</td>\n",
       "      <td>6</td>\n",
       "      <td>London</td>\n",
       "      <td>E12000007</td>\n",
       "      <td>14796.15000</td>\n",
       "      <td>9193.90</td>\n",
       "      <td>408463670.9</td>\n",
       "      <td>416409268.3</td>\n",
       "      <td>15407096977</td>\n",
       "      <td>343059895.3</td>\n",
       "      <td>2820168438</td>\n",
       "      <td>663447725.5</td>\n",
       "      <td>19650182304</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>258</th>\n",
       "      <td>2016</td>\n",
       "      <td>6</td>\n",
       "      <td>London</td>\n",
       "      <td>E12000007</td>\n",
       "      <td>14833.53000</td>\n",
       "      <td>9217.13</td>\n",
       "      <td>506307274.6</td>\n",
       "      <td>473572637.2</td>\n",
       "      <td>15421402742</td>\n",
       "      <td>325407324.8</td>\n",
       "      <td>3224395889</td>\n",
       "      <td>638247686.6</td>\n",
       "      <td>20083026279</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>269</th>\n",
       "      <td>2017</td>\n",
       "      <td>6</td>\n",
       "      <td>London</td>\n",
       "      <td>E12000007</td>\n",
       "      <td>14842.02000</td>\n",
       "      <td>9222.40</td>\n",
       "      <td>500504499.9</td>\n",
       "      <td>468824367.1</td>\n",
       "      <td>15397820259</td>\n",
       "      <td>314755652.2</td>\n",
       "      <td>3268081817</td>\n",
       "      <td>605877014.1</td>\n",
       "      <td>20055359109</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>280</th>\n",
       "      <td>2018</td>\n",
       "      <td>6</td>\n",
       "      <td>London</td>\n",
       "      <td>E12000007</td>\n",
       "      <td>14807.72850</td>\n",
       "      <td>9201.10</td>\n",
       "      <td>518009547.1</td>\n",
       "      <td>463426229.7</td>\n",
       "      <td>15360300487</td>\n",
       "      <td>311386464.0</td>\n",
       "      <td>3259883751</td>\n",
       "      <td>597864775.3</td>\n",
       "      <td>19992861706</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>291</th>\n",
       "      <td>2019</td>\n",
       "      <td>6</td>\n",
       "      <td>London</td>\n",
       "      <td>E12000007</td>\n",
       "      <td>14814.84900</td>\n",
       "      <td>9205.52</td>\n",
       "      <td>467836359.5</td>\n",
       "      <td>493178964.4</td>\n",
       "      <td>15628909709</td>\n",
       "      <td>280323854.7</td>\n",
       "      <td>3264434508</td>\n",
       "      <td>597522653.8</td>\n",
       "      <td>20264369690</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>302</th>\n",
       "      <td>2020</td>\n",
       "      <td>6</td>\n",
       "      <td>London</td>\n",
       "      <td>E12000007</td>\n",
       "      <td>14806.32400</td>\n",
       "      <td>9200.22</td>\n",
       "      <td>697725718.5</td>\n",
       "      <td>463528883.4</td>\n",
       "      <td>12453531229</td>\n",
       "      <td>226088090.9</td>\n",
       "      <td>2877490141</td>\n",
       "      <td>592999898.5</td>\n",
       "      <td>16613638242</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>313</th>\n",
       "      <td>2021</td>\n",
       "      <td>6</td>\n",
       "      <td>London</td>\n",
       "      <td>E12000007</td>\n",
       "      <td>14808.32000</td>\n",
       "      <td>9201.46</td>\n",
       "      <td>647245366.3</td>\n",
       "      <td>607582338.7</td>\n",
       "      <td>13983441245</td>\n",
       "      <td>239005332.1</td>\n",
       "      <td>2987781031</td>\n",
       "      <td>635481336.9</td>\n",
       "      <td>18453291284</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>324</th>\n",
       "      <td>2022</td>\n",
       "      <td>6</td>\n",
       "      <td>London</td>\n",
       "      <td>E12000007</td>\n",
       "      <td>14812.69000</td>\n",
       "      <td>9204.18</td>\n",
       "      <td>605772496.9</td>\n",
       "      <td>701570589.6</td>\n",
       "      <td>14459479463</td>\n",
       "      <td>247774000.2</td>\n",
       "      <td>3031919003</td>\n",
       "      <td>648604037.9</td>\n",
       "      <td>19089347093</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "     year  region_id Region_name   ons_code  total_link_length_km  \\\n",
       "5    1993          6      London  E12000007           14350.44600   \n",
       "16   1994          6      London  E12000007           14384.45600   \n",
       "27   1995          6      London  E12000007           14417.87400   \n",
       "38   1996          6      London  E12000007           14447.84700   \n",
       "49   1997          6      London  E12000007           14488.18100   \n",
       "60   1998          6      London  E12000007           14522.65300   \n",
       "71   1999          6      London  E12000007           14568.80000   \n",
       "82   2000          6      London  E12000007           14603.80000   \n",
       "93   2001          6      London  E12000007           14640.30000   \n",
       "104  2002          6      London  E12000007           14678.82000   \n",
       "115  2003          6      London  E12000007           14712.91900   \n",
       "126  2004          6      London  E12000007           14681.11000   \n",
       "137  2005          6      London  E12000007           14741.26000   \n",
       "148  2006          6      London  E12000007           14745.60000   \n",
       "159  2007          6      London  E12000007           14783.53000   \n",
       "170  2008          6      London  E12000007           14795.80000   \n",
       "181  2009          6      London  E12000007           14800.60000   \n",
       "192  2010          6      London  E12000007           14819.10000   \n",
       "203  2011          6      London  E12000007           14800.10000   \n",
       "214  2012          6      London  E12000007           14814.53333   \n",
       "225  2013          6      London  E12000007           14829.63798   \n",
       "236  2014          6      London  E12000007           14842.84000   \n",
       "247  2015          6      London  E12000007           14796.15000   \n",
       "258  2016          6      London  E12000007           14833.53000   \n",
       "269  2017          6      London  E12000007           14842.02000   \n",
       "280  2018          6      London  E12000007           14807.72850   \n",
       "291  2019          6      London  E12000007           14814.84900   \n",
       "302  2020          6      London  E12000007           14806.32400   \n",
       "313  2021          6      London  E12000007           14808.32000   \n",
       "324  2022          6      London  E12000007           14812.69000   \n",
       "\n",
       "     total_link_length_miles  pedal_cycles  two_wheeled_motor_vehicles  \\\n",
       "5                    8916.95   272098090.7                 358169320.0   \n",
       "16                   8938.09   278441721.3                 369382328.5   \n",
       "27                   8958.85   283280561.7                 359949803.2   \n",
       "38                   8977.48   290084450.6                 375012094.2   \n",
       "49                   9002.54   289069781.3                 398621461.7   \n",
       "60                   9023.96   274374870.4                 406485726.5   \n",
       "71                   9052.63   280888940.9                 443326861.0   \n",
       "82                   9074.38   285064173.2                 443197633.7   \n",
       "93                   9097.06   303232071.7                 470668954.5   \n",
       "104                  9121.00   311966481.9                 471420594.9   \n",
       "115                  9142.18   337003066.6                 533109216.0   \n",
       "126                  9122.42   324364786.1                 498362587.9   \n",
       "137                  9159.79   365182556.1                 521479996.5   \n",
       "148                  9162.49   392590748.0                 533107655.5   \n",
       "159                  9186.06   364097173.3                 569389179.1   \n",
       "170                  9193.68   385927089.6                 493830858.6   \n",
       "181                  9196.67   389992003.9                 490341866.6   \n",
       "192                  9208.16   395831005.8                 452237351.5   \n",
       "203                  9196.36   392051038.7                 435298565.1   \n",
       "214                  9205.32   395619606.2                 409196420.1   \n",
       "225                  9214.71   374087538.8                 391983185.9   \n",
       "236                  9222.91   411222525.8                 407845063.5   \n",
       "247                  9193.90   408463670.9                 416409268.3   \n",
       "258                  9217.13   506307274.6                 473572637.2   \n",
       "269                  9222.40   500504499.9                 468824367.1   \n",
       "280                  9201.10   518009547.1                 463426229.7   \n",
       "291                  9205.52   467836359.5                 493178964.4   \n",
       "302                  9200.22   697725718.5                 463528883.4   \n",
       "313                  9201.46   647245366.3                 607582338.7   \n",
       "324                  9204.18   605772496.9                 701570589.6   \n",
       "\n",
       "     cars_and_taxis  buses_and_coaches        lgvs     all_hgvs  \\\n",
       "5       15882514166        273427487.5  1928558767  640880245.8   \n",
       "16      16062810857        281778335.3  2010906197  623654797.9   \n",
       "27      16003118930        303703868.8  2086967051  608719496.9   \n",
       "38      16161494717        309645905.8  2055510242  647225102.1   \n",
       "49      16229364980        314989192.0  2105300362  646069123.6   \n",
       "60      16283310614        317415517.5  2113837083  698619750.2   \n",
       "71      16643703170        329838479.5  2224175485  673954979.6   \n",
       "82      16579095382        320750641.3  2246917172  698395128.5   \n",
       "93      16581792774        318642518.0  2275163005  683621998.7   \n",
       "104     16689506246        331580609.1  2253473670  669524447.4   \n",
       "115     16445284463        361644655.3  2434451988  673623035.9   \n",
       "126     16383732580        372359587.8  2428689194  680369836.5   \n",
       "137     16355486488        374086734.2  2483299940  688309252.0   \n",
       "148     16333921491        400324190.8  2743030224  671312085.1   \n",
       "159     16185087836        403123777.1  2823260460  660504083.6   \n",
       "170     16003801206        388955485.2  2678730010  668128210.0   \n",
       "181     16042986454        389755686.8  2561954570  626595728.6   \n",
       "192     15844171977        385705140.8  2535439802  634440723.3   \n",
       "203     15525387246        373973848.1  2529308379  631287597.6   \n",
       "214     15344905761        378519000.4  2552620710  655304368.4   \n",
       "225     15295412417        363094903.4  2618477754  645494588.8   \n",
       "236     15488605735        355378727.9  2785404035  643184910.0   \n",
       "247     15407096977        343059895.3  2820168438  663447725.5   \n",
       "258     15421402742        325407324.8  3224395889  638247686.6   \n",
       "269     15397820259        314755652.2  3268081817  605877014.1   \n",
       "280     15360300487        311386464.0  3259883751  597864775.3   \n",
       "291     15628909709        280323854.7  3264434508  597522653.8   \n",
       "302     12453531229        226088090.9  2877490141  592999898.5   \n",
       "313     13983441245        239005332.1  2987781031  635481336.9   \n",
       "324     14459479463        247774000.2  3031919003  648604037.9   \n",
       "\n",
       "     all_motor_vehicles  \n",
       "5           19083549986  \n",
       "16          19348532516  \n",
       "27          19362459150  \n",
       "38          19548888061  \n",
       "49          19694345119  \n",
       "60          19819668691  \n",
       "71          20314998976  \n",
       "82          20288355958  \n",
       "93          20329889250  \n",
       "104         20415505567  \n",
       "115         20448113358  \n",
       "126         20363513786  \n",
       "137         20422662411  \n",
       "148         20681695646  \n",
       "159         20641365336  \n",
       "170         20233445770  \n",
       "181         20111634306  \n",
       "192         19851994994  \n",
       "203         19495255636  \n",
       "214         19340546260  \n",
       "225         19314462849  \n",
       "236         19680418471  \n",
       "247         19650182304  \n",
       "258         20083026279  \n",
       "269         20055359109  \n",
       "280         19992861706  \n",
       "291         20264369690  \n",
       "302         16613638242  \n",
       "313         18453291284  \n",
       "324         19089347093  "
      ]
     },
     "execution_count": 14,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "london_traffic"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 15,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "year\n",
       "1993    1.908355e+10\n",
       "1994    1.934853e+10\n",
       "1995    1.936246e+10\n",
       "1996    1.954889e+10\n",
       "1997    1.969435e+10\n",
       "1998    1.981967e+10\n",
       "1999    2.031500e+10\n",
       "2000    2.028836e+10\n",
       "2001    2.032989e+10\n",
       "2002    2.041551e+10\n",
       "2003    2.044811e+10\n",
       "2004    2.036351e+10\n",
       "2005    2.042266e+10\n",
       "2006    2.068170e+10\n",
       "2007    2.064137e+10\n",
       "2008    2.023345e+10\n",
       "2009    2.011163e+10\n",
       "2010    1.985199e+10\n",
       "2011    1.949526e+10\n",
       "2012    1.934055e+10\n",
       "2013    1.931446e+10\n",
       "2014    1.968042e+10\n",
       "2015    1.965018e+10\n",
       "2016    2.008303e+10\n",
       "2017    2.005536e+10\n",
       "2018    1.999286e+10\n",
       "2019    2.026437e+10\n",
       "2020    1.661364e+10\n",
       "2021    1.845329e+10\n",
       "2022    1.908935e+10\n",
       "Name: all_motor_vehicles, dtype: float64"
      ]
     },
     "execution_count": 15,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "london_la_traffic.groupby('year').all_motor_vehicles.sum()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 17,
   "metadata": {},
   "outputs": [
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "No artists with labels found to put in legend.  Note that artists whose label start with an underscore are ignored when legend() is called with no argument.\n"
     ]
    },
    {
     "data": {
      "text/plain": [
       "<matplotlib.legend.Legend at 0x211d8a3c490>"
      ]
     },
     "execution_count": 17,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 640x480 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "# create graph for annual change\n",
    "\n",
    "plt.plot(\n",
    "    london_traffic['year'],\n",
    "    london_traffic['pedal_cycles'],\n",
    "    legend = True\n",
    ")\n",
    "\n",
    "plt.plot(\n",
    "    london_traffic['year'],\n",
    "    london_traffic['all_motor_vehicles']\n",
    ")\n",
    "\n"
   ]
  }
 ],
 "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": "3.11.5"
  }
 },
 "nbformat": 4,
 "nbformat_minor": 2
}