Long-term London transport trends.ipynb

{
 "cells": [
  {
   "cell_type": "code",
   "execution_count": 2,
   "metadata": {
    "extensions": {
     "jupyter_dashboards": {
      "version": 1,
      "views": {
       "grid_default": {},
       "report_default": {
        "hidden": true
       }
      }
     }
    }
   },
   "outputs": [],
   "source": [
    "import pandas as pd\n",
    "import seaborn as sns\n",
    "import matplotlib.pyplot as plt\n",
    "sns.set(palette='Set1')"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "extensions": {
     "jupyter_dashboards": {
      "version": 1,
      "views": {
       "grid_default": {},
       "report_default": {
        "hidden": false
       }
      }
     }
    }
   },
   "source": [
    "## Vehicle counts on London main roads"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 3,
   "metadata": {
    "extensions": {
     "jupyter_dashboards": {
      "version": 1,
      "views": {
       "grid_default": {},
       "report_default": {
        "hidden": true
       }
      }
     }
    }
   },
   "outputs": [],
   "source": [
    "df = pd.read_csv(\"data/main_road_vehicle_counts_years.csv\") # 2MB file"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 4,
   "metadata": {
    "extensions": {
     "jupyter_dashboards": {
      "version": 1,
      "views": {
       "grid_default": {},
       "report_default": {
        "hidden": true
       }
      }
     }
    }
   },
   "outputs": [],
   "source": [
    "dfyr = df.groupby('Year').mean().reset_index()\n",
    "cyc_base = dfyr.iloc[0]['PedalCycles']\n",
    "motor_base = dfyr.iloc[0]['AllMotorVehicles']\n",
    "dfyr['Bicycles'] = dfyr['PedalCycles'] / cyc_base\n",
    "dfyr['Other Vehicles'] = dfyr['AllMotorVehicles'] / motor_base\n",
    "dfyr = dfyr[['Year','Bicycles','Other Vehicles']]\n",
    "dfyr_melt = pd.melt(dfyr, id_vars=['Year'])\n",
    "dfyr_melt.columns = ['Year','Vehicle type','Number']"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 5,
   "metadata": {
    "extensions": {
     "jupyter_dashboards": {
      "version": 1,
      "views": {
       "grid_default": {},
       "report_default": {
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      }
     }
    }
   },
   "outputs": [
    {
     "data": {
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\n",
      "text/plain": [
       "<Figure size 576x432 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "g = sns.lineplot(x='Year', y='Number', hue='Vehicle type', data=dfyr_melt)\n",
    "g.set(ylim=(0,None),xticks=([2000,2004,2008,2012,2016]))\n",
    "g.figure.set_size_inches(8,6)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "extensions": {
     "jupyter_dashboards": {
      "version": 1,
      "views": {
       "grid_default": {},
       "report_default": {
        "hidden": false
       }
      }
     }
    }
   },
   "source": [
    "## Mode of transport for journeys in London"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 10,
   "metadata": {
    "extensions": {
     "jupyter_dashboards": {
      "version": 1,
      "views": {
       "grid_default": {},
       "report_default": {
        "hidden": true
       }
      }
     }
    }
   },
   "outputs": [],
   "source": [
    "tt = pd.read_csv('data/trips-pub-priv-walk-cycle.csv')\n",
    "tt = tt[tt['Year']>=2000]\n",
    "tt['all'] = tt['Cycle']+tt['Priv_Trans']+tt['Pub_Trans']+tt['Walk']\n",
    "tt['Cycle-%'] = (tt['Cycle'] / tt['all']) * 100\n",
    "tt['Private-%'] = (tt['Priv_Trans'] / tt['all']) * 100\n",
    "\n",
    "#the below could be done more succinctly\n",
    "ttyr = tt.groupby('Year').mean().reset_index()\n",
    "ttyrabs = ttyr\n",
    "cyc_base = ttyr.iloc[0]['Cycle']\n",
    "priv_base = ttyr.iloc[0]['Priv_Trans']\n",
    "pub_base = ttyr.iloc[0]['Pub_Trans']\n",
    "walk_base = ttyr.iloc[0]['Walk']\n",
    "all_base = ttyr.iloc[0]['all']\n",
    "\n",
    "ttyr['Cycle'] = ttyr['Cycle'] / cyc_base\n",
    "ttyr['Private_Transport'] = ttyr['Priv_Trans'] / priv_base\n",
    "ttyr['Public_Transport'] = ttyr['Pub_Trans'] / pub_base\n",
    "ttyr['Walk'] = ttyr['Walk'] / walk_base\n",
    "ttyr['All'] = ttyr['all'] / all_base\n",
    "\n",
    "ttyr = ttyr[['Year','Cycle','Private_Transport','Public_Transport','Walk','All']]\n",
    "ttyr = pd.melt(ttyr, id_vars=['Year'])\n",
    "ttyr.columns = ['Year','Journey type','Number']"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 11,
   "metadata": {
    "extensions": {
     "jupyter_dashboards": {
      "version": 1,
      "views": {
       "grid_default": {},
       "report_default": {
        "hidden": false
       }
      }
     }
    }
   },
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 576x432 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "g = sns.lineplot(x='Year', y='Number', hue='Journey type', data=ttyr)\n",
    "g.set(ylim=(0,None),xticks=([2000,2004,2008,2012,2016]))\n",
    "g.figure.set_size_inches(8,6)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "extensions": {
     "jupyter_dashboards": {
      "version": 1,
      "views": {
       "grid_default": {},
       "report_default": {
        "hidden": false
       }
      }
     }
    }
   },
   "source": [
    "- Cycling has grown more rapidly than other forms of transport"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "extensions": {
     "jupyter_dashboards": {
      "version": 1,
      "views": {
       "grid_default": {},
       "report_default": {
        "hidden": false
       }
      }
     }
    }
   },
   "source": [
    "## London Underground usage"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 7,
   "metadata": {
    "extensions": {
     "jupyter_dashboards": {
      "version": 1,
      "views": {
       "grid_default": {},
       "report_default": {
        "hidden": true
       }
      }
     }
    }
   },
   "outputs": [],
   "source": [
    "t = pd.read_csv('data/ee.csv')\n",
    "tg = t.groupby('Year').sum()\n",
    "#tg.plot(y='Annual-e-and-e-million',ylim=(0,3500))\n",
    "tg = tg.reset_index()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "extensions": {
     "jupyter_dashboards": {
      "version": 1,
      "views": {
       "grid_default": {},
       "report_default": {
        "hidden": false
       }
      }
     }
    }
   },
   "source": [
    "## Annual bus count data"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 8,
   "metadata": {
    "extensions": {
     "jupyter_dashboards": {
      "version": 1,
      "views": {
       "grid_default": {},
       "report_default": {
        "hidden": true
       }
      }
     }
    }
   },
   "outputs": [],
   "source": [
    "buses = pd.read_csv('data/annual-buses.csv')\n",
    "buses['Buses'] = buses['Buses'].astype(int)\n",
    "#buses.plot(x='Year', ylim=(0,12000));"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "extensions": {
     "jupyter_dashboards": {
      "version": 1,
      "views": {
       "grid_default": {},
       "report_default": {
        "hidden": false
       }
      }
     }
    }
   },
   "source": [
    "## London working age population"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 9,
   "metadata": {
    "extensions": {
     "jupyter_dashboards": {
      "version": 1,
      "views": {
       "grid_default": {},
       "report_default": {
        "hidden": false
       }
      }
     }
    }
   },
   "outputs": [
    {
     "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>index</th>\n",
       "      <th>Year</th>\n",
       "      <th>All aged 16 to 64 (m)</th>\n",
       "      <th>Total in employment (m)</th>\n",
       "      <th>Employment rate (%)</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>0</td>\n",
       "      <td>2010</td>\n",
       "      <td>5.52</td>\n",
       "      <td>3.74</td>\n",
       "      <td>67.72</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>8</td>\n",
       "      <td>2018</td>\n",
       "      <td>6.11</td>\n",
       "      <td>4.57</td>\n",
       "      <td>74.82</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "   index  Year  All aged 16 to 64 (m)  Total in employment (m)  \\\n",
       "0      0  2010                   5.52                     3.74   \n",
       "1      8  2018                   6.11                     4.57   \n",
       "\n",
       "   Employment rate (%)  \n",
       "0                67.72  \n",
       "1                74.82  "
      ]
     },
     "execution_count": 9,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "popn = pd.read_csv('data/popn-employment-rate.csv')\n",
    "popn['All aged 16 to 64'] = popn['All aged 16 to 64'].astype(int)\n",
    "popn = popn[popn['Year']>=2010]\n",
    "popn['All aged 16 to 64'] = popn['All aged 16 to 64']/1000000\n",
    "popn['Total in employment'] = popn['Total in employment']/1000000\n",
    "popn = popn.rename(columns={'All aged 16 to 64':'All aged 16 to 64 (m)',\n",
    "           'Total in employment':'Total in employment (m)'})\n",
    "ann_popn = popn.groupby('Year').mean()\n",
    "ann_popn = ann_popn.reset_index()\n",
    "#ann_popn.plot(y=['All aged 16 to 64 (m)','Total in employment (m)'],ylim=(0,8));\n",
    "ann_popnmm = ann_popn[ann_popn['All aged 16 to 64 (m)'].isin(\n",
    "    [ann_popn['All aged 16 to 64 (m)'].min(),ann_popn['All aged 16 to 64 (m)'].max()])]\n",
    "ann_popnmm.round(2).reset_index()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "extensions": {
     "jupyter_dashboards": {
      "version": 1,
      "views": {
       "grid_default": {},
       "report_default": {
        "hidden": false
       }
      }
     }
    }
   },
   "source": [
    "## Collate and plot together for comparison"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 10,
   "metadata": {
    "extensions": {
     "jupyter_dashboards": {
      "version": 1,
      "views": {
       "grid_default": {},
       "report_default": {
        "hidden": true
       }
      }
     }
    }
   },
   "outputs": [],
   "source": [
    "ann = pd.DataFrame(list(range(2010,2018)))\n",
    "ann.columns = ['Year']"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 11,
   "metadata": {
    "extensions": {
     "jupyter_dashboards": {
      "version": 1,
      "views": {
       "grid_default": {},
       "report_default": {
        "hidden": true
       }
      }
     }
    }
   },
   "outputs": [],
   "source": [
    "ann['Bicycle use'] = dfyr['Bicycles']\n",
    "ann['Underground use'] = list(tg['Annual-e-and-e-million']) / tg.iloc[0]['Annual-e-and-e-million']\n",
    "ann['Buses in service'] = buses['Buses'] / buses.iloc[0]['Buses']\n",
    "ann['Working age population'] = ann_popn['All aged 16 to 64 (m)'] / ann_popn.iloc[0]['All aged 16 to 64 (m)']\n",
    "ann['Total in employment'] = ann_popn['Total in employment (m)'] / ann_popn.iloc[0]['Total in employment (m)']"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 12,
   "metadata": {
    "extensions": {
     "jupyter_dashboards": {
      "version": 1,
      "views": {
       "grid_default": {},
       "report_default": {
        "hidden": true
       }
      }
     }
    }
   },
   "outputs": [],
   "source": [
    "ann_index = pd.melt(ann, id_vars=['Year'])\n",
    "ann_index.columns = ['Year','Value','Number']"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 13,
   "metadata": {
    "extensions": {
     "jupyter_dashboards": {
      "version": 1,
      "views": {
       "grid_default": {},
       "report_default": {
        "hidden": false
       }
      }
     }
    }
   },
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 576x432 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "g = sns.lineplot(x='Year', y='Number', hue='Value', data=ann_index)\n",
    "g.set(ylim=(0,None))\n",
    "g.figure.set_size_inches(8,6)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "extensions": {
     "jupyter_dashboards": {
      "version": 1,
      "views": {
       "grid_default": {},
       "report_default": {
        "hidden": false
       }
      }
     }
    }
   },
   "source": [
    "- Increases in other public transport usage and provision is somewhat more in line with the increase in population\n",
    "- Difficult to increase to capacity for these modes (financial, environmnental, geographical reasons)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "extensions": {
     "jupyter_dashboards": {
      "version": 1,
      "views": {
       "grid_default": {},
       "report_default": {
        "hidden": false
       }
      }
     }
    }
   },
   "source": [
    "## TfL Cycle Hire bikes in service"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 14,
   "metadata": {
    "extensions": {
     "jupyter_dashboards": {
      "version": 1,
      "views": {
       "grid_default": {},
       "report_default": {
        "hidden": false
       }
      }
     }
    }
   },
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "bb = pd.read_csv('data/hire-bike-volumes.csv')\n",
    "bb = bb.rename(columns={'Stations':'Dock_Points'})\n",
    "bb['Date'] = pd.to_datetime(bb['Date'], dayfirst=True).dt.date\n",
    "#missing values imputed using last known or estimated value\n",
    "bb = bb.fillna(method='ffill')\n",
    "bb = bb.set_index('Date')\n",
    "bb.plot(y='Bicycles',ylim=(0,20000));"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "extensions": {
     "jupyter_dashboards": {
      "version": 1,
      "views": {
       "grid_default": {},
       "report_default": {
        "hidden": false
       }
      }
     }
    }
   },
   "source": [
    "## Motor fuel price history"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 15,
   "metadata": {
    "extensions": {
     "jupyter_dashboards": {
      "version": 1,
      "views": {
       "grid_default": {},
       "report_default": {
        "hidden": false
       }
      }
     }
    }
   },
   "outputs": [
    {
     "data": {
      "image/png": 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iQIckHpu1jvtnak7t046rxnY7/J3ZxHFjb3kNiwIFf31uGQbQr30iZw/K5oQeaSSG0XxRriz+fsvm719t553l28hOimbaWX3plh5X93N7z258D9yHPX8eRo7C89iTmAMGtWJi0ZqMtHQ8F19Cxk/PI/f2u/E/8zT+mf/Be/c0zKHDG9ymY0oMD58/gHeWb+e9Fdv5384Sbj61V4MXB4q2razax5IfCliwLp/VO4qxbGdeqCtO7MLYXumkx4f+osNQcF3xLyyv4dHZ6/l2ezETVAa/Gt+dmECLzPb7sd59C/9fngLLwvPbWzB/fmmbnudehI4nKwvvI09gLVyA74Hp+K64FPPc8/HceDNGUvIh60d4TC4Z3ZmhnZN5fPZ6fv/+aqYM78iUEZ1kfqA2rtrnZ/nmQudMnc2F+Cyb7KRoLhzekXE56XRKOfoZX/beAqzFi7AXLcBa8RUV990LJ0w8Bukdrir+K7cV8djs9VTU+PnNxB5M6tOurpvHWrsG//Rp2N+txjjhJLx33oPRsVMrJxbhyBw3nogRI/D/9VmsGa9hzZ+H59bfYf74zAYvIOvXPpGnfzqIFxZu4u3l2/l6axE3n9qL9skxrZBeNJffslm1zTk1c8nGAiprLVJjI/jJgCzG52TQs13cES8gtG0bW6/BXrQQa+F87P+tBtuGjAzM8ScTNXo0x3IiGFcUf79l8/aX2/j7V9vpmBLDfWf3qzsX266swP/cM1hvvg5JyXgeeATzRz8OizlbRPgyYmLx3nQr1o/PwH/fNPx33Y714Qd47/wDRpeuh6wfF+XlplN7MbxrCs/O38hv313FVSd147S+7eRvLYzZts3a3aUsWJfP4g35FFf6iIvycFKvdMbnZNC/feIRj+LsygrspUuwFi3EWrwQcveAYWD064/nuusxxo7H6N0HwzDwZCTAMRwgP+6Lf0FZDY/MWsd3O0s4pXcG147vXjfKbi1eiO/+6bBzxxEP34U4HFP1xnj1Taz3/4H/6cepveAcZ0D4F1dgRB46IDy2Vzp9shN4Ys4G/vLZD3y1pZDrT+4hN44JM5sDp2YuXJ9Pbmk1kR6Tkd1SGJ+TwbAuyUe8ktvesR1r0QKshQuwv/rSuQdGfDzG6BMwx47HPGksRlr6MXw3DTuui/+KLYU8Pns91T6Lmyb1ZGJv51J+uyAf/yMPYn3yX+jWHe/Lr2MOa3jgToijMTwePBf+FPPkU/A/8sD+AeG7pjX4d5UeH8X0s/vy4cpdvLZkCze8vZLfntKTYV1SWiG92GdPSRUL1zln6mzZW4FpwOBOyVw8qhOju6cd9mwt2+fDXrXS6cpZtAB74w/OD7p0xZxyEebY8RhDhjZ4dlhranTxV0olAl8AZ2itNyulrgF+A9jAV8AvtdY1SqnBwEtAIrAQuFZr3Yh7/4WO37KZsXQr7329gy6psfx+cg6dUmKxLQvrX+/jf/IxqKrEc931mJdf1WALTYimMjIy8D78ONZZ5+C7fzq+Ky/FPOc8PDfeipF84BGlaRicM6Q9gzol8eisdUz7aA1nDMjishO7EOWVU0KPlaKKGhZvKGDhunzW7Ha6XPpkJ3Dt+G6c1DP9sEdkdmEh1heLsBcuwPricygtAa8XY9gIPOddgDl2XIPdf+GkUcVfKTUKeBHICTzOAW4DhgGlwKvAr4EngBnAVVrrpUqpl4GrgedCnvww8kqreWTWOtbsKuX0vplcPa4rUV4P9sYf8E2fiv3N1xjDRuC9ZxpG127HKpZwEfOkcUS8/yH+F57DeuNVrAWf4bn5d5hnnHVI/3639DieuHAQry3ZwoerdrFqezG3nNaLHhlyPUlLKa/yMW9tLgvW5bNyWxGWDV3TYrl0TGfG9Uons4Eb9di2jb1+HfbC+ViLFmKvXgWW5dwfe+IpmOMmYIw+wbkfdRvR2Jb/1TjF/Y3A42rgV1rrEgCl1Gqgs1KqCxCjtV4aWO9V4F6OUfFfvnkvT8zegM+yuOXUXkxQGdjV1fheeNa5XD82Fs+0+zDPPlcG2USLMmJi8P72ZmdAePo0/PfcgfXRB3jvmnpIizDSa3L12G4M75LCk3M3cOs/VvPz0Z05Z3B7OSU0RPyWzddbC5m7No+vNhdS7bNolxDF/w3twPicdLqkHVq07cpK7OXLsAIFnz27ATD69se8+lqnO6dvvzZ7z44mTe+glNoMTNBab663LANYDlyGs1N4RGt9UuBnPYH/aq1zGvH0XYFNjQ5Tj9+yeXb2Ot78YjO9shL40wWD6JweR/XnX1B0+x34Nm4k5rxzSZr6BzzprT/QItzFtiwq3nyL4vsfwK6qIuE3N5Dwq+sanDSuuKKGBz/6ns++38OQrilMPXcAWXJKaLNt2FPKf1fu5JNvd7K3rIbk2Agm9c/m9IHZ9O+YdEgj0Ld9O1Vz5lI1dx7VX3wOVdUYcXFEjRtL9KRTiD75ZDyZma30bo7q2E3voJTqAMwEXtZaz1dKnYgzBrCPAVhNec7mzO3zQ14Zb36xmcn9M7nqpG5EFO5l1z3OqXd07IT3uZfwjzmBvTbH9FQqCN/5TSB8sx2XuX50Nt7hJ+B/9CFKH32M0vf+6VwhPHzEIavedHJ3BmYn8MLCjVz8zOdcN6E743MyWiZXC2qtXMWVtSxYl8+8tbn8kFeOxzQY0TWFU8a1Y1iXZNpnJZGXV0p+fpkzWLt6FdaiBdgLF2BvWO88SadOmOdd6LTuhw3HioykAqiAFqshIZjbp0maXfyVUr2BT4GntdaPBRZvB+pPdZkF7GzuazRWj4x4Pr5tAv6KaqyPP6L2sYegtBTziqvwXH0dRoy0nETrM9Iz8D74KNaZZzsDwlf9AvOsc/DcdBtGyv4zfQzDYFKfdvRvn8hjs9fz6CznlpHXju9+yL0lhKPWb7FiSxFz1+ayfHMhfsumR0Yc14ztxricAwdurcJC/P/9xLmy9vNFUBIYrB0yDM8tv8McOz7oO761Bc36S1JKJQCzgLu01vvGAdBab1FKVSmlTtRafw5cgnNk0OKS8naSe8vvsZctwRg4CM8992L2akxvkxDHlnniWCLe+zf+F/+K9frfsBbOdwaEzzz7gIKTlRTNg+f15x8rtvP2l9v4LjA/0IAOcstI2D9V8ry1eczXeZRU+UiOjeDMgdmc0juDrvXn69q9C2vuHKx5s9n1zdfOYG1KKub4ic6ZOWNOxEhw17xLzW1GXAVkArcopW4JLPtQa/0H4GLgxcCpoV8DTwcf88jsLZvZM+Vc8EbgueMezAumtNlBGOEORkwM3t/ctH9A+A93OlcI3z2V+meheUyDn47oxNDOyTw6az13/es7zhvagYtHdXLtLSMLK2pYoPOZuzaXzQUVeE2DUd1TOaV3BkM7p9QNktvbt2HNmYU1dzb26m8BMHrlkHDD9VQOH4PRb4Cr68RxMZ+/XV5OzEfvUTlxcrPuydqSwrU/FsI3m9ty2ZaF9c/38D/1uHP9yZXXYF5x9SHXn1TW+Hl58WY+/X4P3dPjuOW0XnROjXXF51Xrt/hy017mrs1jxZZCLBtyMuM5pXc7xvZKIyHa6daxN29yCv6cWdhr1wBg9O2HecqpmJNOw+jS9bj7vJo7n/9xUfzBfQUjFMI1m1tz2QX5+B99CGvmx9ClqzMgPGLkIest3biXP8/bQFWtxeUnduFn43pQUlTRYrmaK9jPy7Zt1ueWMXdtHgvX5VNW7SM1LpKTVQan9M6gU2qsc/79DxuwZn+KPXd23YCtMXAQ5qTTME85FaNDx5DmailyMxchXMpIS8f7wCNYZ56D7/4/4rv6Mswzz8Fz84EDwqO7p6IyB/PUvA08v3ATLy3eTHZSNF3SYumSGkvXtFi6pMWSmRjdJq8TKCirYf66POauyWVbYSWRHpPRgW6dQZ2SMQ2w167B96bTwmfLZmeytKHDnPtqn3IqRmZWa7+NsCfFX4gwY55w4v4B4ddewVo0H89Nt2GedU7dgHBKXCRTz+jD8s2FbC+t4fttRWzMK+eLDQV151pHek06p8bQNS2OLqnODqFrWizJsRFhdyZLtc/Pso2FzF2bW3fVbZ+sBK4/uQcn9XTm1bH/9y3WUy9TO2cW7NgOHg/G8BGYP78U8+RTMNIPfzqsOJQUfyHCkBEdjfeGG7Em/wT/fffin3rX/gHhbt2ddQyDkd1S+Um97oKqWj9b91awpaCCzQUVbN1bwVdbCpmzJrfuuROivXVHB86RQhyd02IOuHf1sWDbNnp3GXPW5rJ4fT7lNX7S4yM5f1hHJqoM2idFYa/6BuupV6idNxt273ZOyRw1BvOqX2JOmHjAEZFoGin+QoQxs2cvjFdex/rgn/ifeJTaC8/FvPwqPFde0+AVwtERHnIyE8jJPPC0xeLK2rodwpaCcrYUVDB3TS6VtfuvwWyXEFW3Q9h3lNAhJSbkZxXllVbzmc5j3tpcdhRVEeU1OaFHGqf0zqB/VhzGNyuwnnvNKfj5+RAZiXHCiZjX3+jMoZOYGNI8biXFX4gwZ5gmnvPOxxw/Af9jD2O98BzWJ//Fe/dUzJGjG/UcSTERDOyYxMCO+68RsGyb3NJqttbtFJx/X28twh846cJjGnRIjna6jvYdLaTF0i4hCrMJXUdVtX6WbNzLvLW5rNpWjA30b5/I+UM7MKZLIjErv8J65Q388+dCYSFEx2CcNNYZtB07vk1NmNZWSPEXoo0w0tLx3v9wYED4XnzXXIF5xllU/Ph0LE80JKdgpKRCcnKjpik3DYOsxGiyEqMZ2S21bnmt32JHYSVb6nUfrd1dysL1+XXrxESYdE7dtzOIqztSqH8lrW3bfLezhLlrclm8oYDKWj+ZiVFcNLITE7olkfn9Cqy33sRa8Bm+0hKIi8McOwHz1NMwTjhJrsxvYVL8hWhjzDEnEPGPf+N/+QWsv71E4X8+PHSluDhISXXuI7Bvp5CSjJGccuDyVGdnQUJi3QVPER6TrulxB1whC1BR42NrgbNT2BzoOlqycS+zvt8/npAcG0GX1FiykqL5384SdhRWEhNhcmLPdCZ2S6LPxpXwz3ewFs3HV14OCYmYEyZiTjrVmRK5ga4s0TKk+AvRBhnR0Xh//RvsSy8nxVfG3h+2Q1EhdlEhFBZiFxYGHhdBQT7WD+uhsAiqKht+QtOEpGRnADUlJbDDCHxNdpZFp6SQk5yCSk2B7tkYMTHYtk1RRa3TbbR3f9fRovX59O2QxIX90xm1YzWRM9/BXrwIq6oSUlIwT5vstPBHjAy7O1y5hRR/IdowIyGBiIz2mCnZR18ZZ476up1C4d7ATqIIu3DvAcvZtBHrmyIoKnTmwWlIdDQkJxOfkkr/5BQGJCc7RxUpKRAbS8SCFVTNXwA1Ndjp6ZhnneO08IcOx/BK6Wlt8hsQwkWMmBiIicHIbt+o9W3Lcm5RWFSEvbfeDqKo0NlhFBYFjjb2Ym3b6uwsysqcjbOzMc+f4rTwBw7G8MjtKcOJFH8hxGEZge4gkpIbfU9au6YGSkvIyOlCfkF5ywYUzSbFXwgRUkZkJKSlu3rGzLZAfjtCCOFCUvyFEMKFpPgLIYQLSfEXQggXkuIvhBAuJMVfCCFcSIq/EEK4UKPP81dKJQJfAGdorTcrpSYBjwMxwLta67sD6w0GXgISgYXAtVprX8iTCyGEaLZGtfyVUqOAxUBO4HEM8ApwNtAHGKGUmhxYfQZwvdY6BzCAq0MdWgghRHAa2+1zNfBrYGfg8UhgvdZ6U6BVPwO4QCnVBYjRWi8NrPcqcEEI8wohhAiBRnX7aK2vAlBK7VvUHthVb5VdQMcjLG+0tLT4pqx+gIyMhKOv1ArCNReEbzbJ1TSSq2kkV/Pn9jEBu95jA7COsLzRCgrKsCz76CseJKPeTazDSbjmgvDNJrmaRnI1zfGWyzSNZjWam3u2z3ag/gTiWThdQodbLoQQIow0t/gvA5RSqqdSygP8DJiptd4CVCmlTgysdwkwMwQ5hRBChFCzir/Wugq4DHgf+B5YC7wX+PHFwBNKqbVAPPB08DGFEEKEUpP6/LXWXet9PxcY1MA6q3DOBhJCCBGm5ApfIYRwISn+QgjhQlL8hRDChaT4CyGEC0nxF0IIF5LiL4QQLiTFXwghXEiAdkF/AAAUYElEQVSKvxBCuJAUfyGEcCEp/kII4UJS/IUQwoWk+AshhAtJ8RdCCBeS4i+EEC4kxV8IIVxIir8QQriQFH8hhHAhKf5CCOFCUvyFEMKFpPgLIYQLNekG7gdTSv0cuCPwcKbW+lal1GDgJSARWAhcq7X2BRdTCCFEKDW75a+UigWeBsYDg4CxSqlJwAzgeq11DmAAV4ciqBBCiNAJptvHE9g+DogI/KsFYrTWSwPrvApcEExAIYQQodfsbh+tdalS6h5gLVABLABqgF31VtsFdGzK86alxTc3EhkZCc3etiWFay4I32ySq2kkV9NIriCKv1JqIHAF0AUoxunuOQ2w661mAFZTnregoAzLso++4kEyMhLIyytt8nYtLVxzQfhmk1xNI7ma5njLZZpGsxrNwXT7nA7M1Vrnaq2rcbp4JgDZ9dbJAnYG8RpCCCFaQDDFfxUwSSkVp5QygDNxun6qlFInBta5BJgZZEYhhBAh1uzir7WeBbwNrAC+xRnwfRC4GHhCKbUWiMc5I0gIIUQYCeo8f631Q8BDBy1eBYwM5nmFEEK0LLnCVwghXEiKvxBCuJAUfyGEcCEp/kII4UJS/IUQwoWk+AshhAtJ8RdCCBeS4i+EEC4kxV8IIVxIir8QQriQFH8hhHAhKf5CCOFCUvyFEMKFpPgLIYQLSfEXQggXkuIvhBAuJMVfCCFcSIq/EEK4kBR/IYRwISn+QgjhQkHdwF0pdSYwFYgDZmmtf6uUmgQ8DsQA72qt7w4+phBCiFBqdstfKdUd+CtwDjAQGKqUmgy8ApwN9AFGBJYJIYQII8F0+5yL07LfrrWuBaYAFcB6rfUmrbUPmAFcEIKcQgghQiiYbp+eQI1S6kOgM/Af4DtgV711dgEdm/KkaWnxzQ6UkZHQ7G1bUrjmgvDNJrmaRnI1jeQKrvh7gXHABKAM+BCoBOx66xiA1ZQnLSgow7Lso694kIyMBPLySpu8XUsL11wQvtkkV9NIrqY53nKZptGsRnMwxX83MEdrnQeglPoXThePv946WcDOIF5DCCFECwim+P8HeE0plQyUApOB94DblVI9gU3Az3AGgIUQQoSRZg/4aq2XAQ8Di4HvgS3Ac8BlwPuBZWtxdghCCCHCSFDn+WutX+HQlv1cYFAwzyuEEKJlyRW+QgjhQlL8hRDChaT4CyGEC0nxF0IIF5LiL4QQLiTFXwghXEiKvxBCuJAUfyGEcCEp/kII4UJS/IUQwoWk+AshhAtJ8RdCCBeS4i+EEC4kxV8IIVxIir8QQriQFH8hhHAhKf5CCOFCUvyFEMKFpPgLIYQLSfEXQggXCuoG7vsopR4F0rXWlymlBgMvAYnAQuBarbUvFK8jhBAiNIJu+SulTgF+UW/RDOB6rXUOYABXB/saQgghQiuo4q+USgX+BNwfeNwFiNFaLw2s8ipwQTCvIYQQIvSC7fZ5HrgL6BR43B7YVe/nu4COTXnCtLT4ZofJyEho9rYtKVxzQfhmk1xNI7maRnIFUfyVUlcB27TWc5VSlwUWm4BdbzUDsJryvAUFZViWffQVD5KRkUBeXmmTt2tp4ZoLwjeb5GoaydU0x1su0zSa1WgOpuU/BchWSq0EUoF4nMKfXW+dLGBnEK8hhBCiBTS7z19rfarWur/WejDwB+BDrfXlQJVS6sTAapcAM0OQUwghRAi1xHn+FwNPKKXW4hwNPN0CryGEECIIITnPX2v9Ks6ZPWitVwEjQ/G8QgghWoZc4SuEEC4kxV8IIVxIir8QQriQFH8hhHAhKf5CCOFCUvyFEMKFpPgLIYQLSfEXQggXkuIvhBAuJMVfCCFcSIq/EEK4kBR/IYRwISn+QgjhQiGZ1bOl+f0+Cgvz8PlqDrtObq6JZTXppmHHREvl8nojSUnJwONpE79CIUSYaROVo7Awj+joWOLisjAMo8F1vF4Tny/8in9L5LJtm/LyEgoL80hPzz76BkIIcZA20e3j89UQF5d42MLvNoZhEBeXeMQjISGEOJI2UfwBKfwHkc9DCBGMNtHtE2527drJRRedR9eu3TEMqK31kZ6ezp13TqVdu8wGt/nww38RExPDqaf+qNGvc/3113DFFdcwdOjwUEUXQgigDbX8w016egavvvoWf/vbW8yY8Xd69OjFM888ddj1V69eRW1t7TFMKIQQhyct/xAZOnQ4zz//F9as+Y6nn36c6uoqkpKSueOOu9myZSuLFy9kxYrlpKWlM2fOpxQXF7Njxzauu+43JCen8NRTj1JTU0NycjK33XYnHTt2au23JIQ4jgVV/JVSU4ELAw8/1lr/Tik1CXgciAHe1VrfHWTGA/g/+jfWB/88ZLnPANsO7rnNc87Dc+bZTd7O5/Mxf/5cevfuy4MP3sdDDz1BVlYWy5Yt4f77p/Pkk89y0knjGDJkGKNGjWHOnE9JSkri4YefoLa2losuOo/p0x+kT59+zJs3h2nT7uKll14P7s0IIcQRNLv4B4r8acAQwAY+UUpdBDwEjAe2AR8rpSZrrWeGImw4yc/P47LLfgZAbW0Nffr04yc/OYvPPpvD7bffXLdeRUV5g9v37dsfgG3btpCQkECfPv0AmDhxEg8//CfKyspa+B0IIdwsmJb/LuAWrXUNgFJqDZADrNdabwosmwFcAISs+HvOPLvB1vmxPs9/X59/fevXr6N9+w51y/1+PyUlRQ1uHxUVBYBlNXS4YmNZ/pDmFUKI+ppd/LXW3+37XinVC6f75884O4V9dgEdm/K8aWnxhyzLzTXxeo8+Nt2YdULB4zEbfL0ePbpTUlLC//63ksGDh/Kf/3zAp5/O5LnnXsTr9WLbFl6viWEYmKaB12vSvXs3SkpKWLduDX379mPOnFlkZWWTmpqCYRh4PId/76ZpkpGRENR7CXb7liK5mkZyNY3kCsGAr1KqH/AxcBvgw2n972MATWqOFxSUHdIatizrqK36Y9ny9/ud1zn49UzTy/TpD9YN3sbGxjF16h/x+SyGDRvB888/S2xsHLZtY1k2Pp+FaXq59977eeSRB6mqqiQxMYl7730An8/Ctm38/sO/d8uyyMsrbfb7yMhICGr7liK5mkZyNc3xlss0jQYbzUdj2EGMkiqlTgTeB27UWr+jlBoP3KO1nhT4+SXAyVrrKxrxdF2BTQ0V/927t5CV1eWIG7tpeod9GvO5HMnx9p+gpUmuppFcTROC4t8N2NzY7YIZ8O0EfABM0VrPCyxe5vxI9QQ2AT8DXmnuawghhGgZwXT73ApEA48rpfYt+ytwGc7RQDTwX+C9IF5DCCFECwhmwPe3wG8P8+NBzX1eIYQQLU+mdxBCCBeS4i+EEC4kxV8IIVxIir8QQriQzOrZDPXn8weorq5iwIBBXHvt9eTm7uGDD97n9tvvCdlr3XDDL3nvvY9C8nxCCAFS/Jut/tw+tm3z/PPPcPfdv+fZZ1/i9tv7tnI6IYQ4Min+IWAYBlde+UvOPPM0/vGPd1iwYB5/+csLbN++jccee5Di4iKioqK56abbyMnpzaxZn/DWW69jmibt27fnnnumExUVxRtvvMpnn83G77cYNWo01133m9Z+a0KI41SbK/7z1uYy+/vcQ5YbIZjP/9S+7ZjYu12zto2IiKBTp06kpqbVLfvTn6Zy662306NHDps2beTOO2/l7bf/yYsvPscLL/yNlJRUnnnmKbZu3UxBQQFar+HFF1/HMAymT/8Ds2bNZODAwcG9KSGEaECbK/7hzaibqrmiooI1a77nvvum1e2UKisrKS4u4sQTx3LddVcybtwExo+fSK9eik8/fZLvv/8fV155CeCMI2RmZknxF0K0iDZX/Cf2brh13toTu9XW1rJt2xaKivYCzoybkZFRvPHGO3W5cnP3kJiYxI033sqGDWezZMlipk+/hyuuuAbL8nPhhRfx05/+HIDS0lI8Hg/FxQ3fD0AIIYIhp3qGgGVZvPzy8/TtO4D27Z3bF8THx9OxYydmzvwYgOXLl/LrX1+D3+/npz89l+TkZC655HJ+9KOfsG6dZujQEXz66X+pqKjA5/Nxxx23MH/+3NZ8W0KI41iba/mHi/q3cbQsP716KaZN+xMbNqyrW2fq1Pt49NEHmDHjNbzeCP74x/vxer1ceeUvufHGXxMVFUVKSgp33TWNlJRUNmxYxzXXXIZl+Rk16gQmTz6D3bt3HS6CEEI0W1Dz+YdYV2Q+/yaR+fyPLcnVNJKraY71fP7S7SOEEC4kxV8IIVxIir8QQrhQmyn+YTQ2ERbk8xBCBKNNFH+vN5Ly8hIpeAG2bVNeXoLXG9naUYQQbVSbONUzJSWDwsI8ysoOf8GTaZpYVvid7dNSubzeSFJSMkL+vEIId2gTxd/j8ZKenn3EdY6307eEEKIltUjxV0r9DLgbiACe1Fo/0xKvI4QQonlC3uevlOoA/Ak4CRgMXKOUkgnuhRAijLREy38SME9rvRdAKfUecD7wx6Ns5wHnarXmCmbblhSuuSB8s0muppFcTXM85aq3jacp27VE8W8P1J+QZhcwshHbZQOkpMQ1+4UDlziHnXDNBeGbTXI1jeRqmuM0VzbwQ2NXbonibwL1z8k0gMac7rIcGIuzs/C3QC4hhDgeeXAK//KmbNQSxX87ThHfJwvY2YjtqoHFLZBHCCGOd41u8e/TEsV/DjBNKZUBlAP/B1zTAq8jhBCimUJ+to/WegdwF/AZsBJ4S2v9ZahfRwghRPOF03z+QgghjpE2MbePEEKI0JLiL4QQLiTFXwghXEiKvxBCuFBYz+qplJoKXBh4+LHW+ndKqUnA40AM8K7W+u6DtnkdZ3qJVwOPOwMzgHaABi7WWpeFQ7Z6y6cDfq31tHDIpZQ6EXgCiAQKgCu01lvCINdY4MlArk3AL7TWha2dq97yIcBSrXVUMJlClUsp9QvgQWBPvee5KwxyZQMv4cwGUIHzf3Jza+ZSSrUDZtX7cRKQobUO6pLbEH1eXYHXgUSgCOfvPqj/jxDGLf/AB3QaMARngrhhSqmLgFeAs4E+wAil1OTA+u2VUh/hzCNU37PAs1rr3sBXwD3hkk0plaSUehm4JdhMocwFvAlcpbUeHPj+6TDJ9TfgEq31AOB74LYwyYVSKhb4M86OKSghzDUcuFlrPTjwL9jCH6pcbwAfaa2HBL5/qLVzaa1z931OwFBgM0FenxTCz2s68HYg2/s4E2cGLWyLP840D7dorWu01rXAGiAHWK+13qS19uG06C8IrH8x8G/g7/ueQCkVAYwD3gsserXe+q2aLeBsYD3wWAgyhSSXUioKuFtr/W1g0bdA59bOFdBHa/194PfaAQiq1R/CXOD8Dp8MMk+oc40AfqGUWq2UmqGUSmntXEqpdGAQ8Hxg0d9wpn9v1VwHuRyo0Fq/FSa5PDitfoA4oDLIXEAYd/torb/b971SqhfOodOfOXTSuI6B9R8JrHtSvZ+nAyWBD/mA9cMgG1rr1wPLpwWbKVS5tNbVOH+QKKVMYBrwQWvnCiyvVUoNwLmKvBa4MxxyKaXOAmK11u8ppYKJFNJcgXUeBb4A7gf+glNgWjNXD2Ar8FigG283cH1zM4Uw177tPTgXqZ4dTKYQ57oH+EIp9RucI8sxwWaD8G75A6CU6gfMxjnE30jTJo07eJI5jrL+sczWYkKRSykVidPl48UpHGGRS2u9WmudiXMo/G5r51JKZeG0XG8IRZZQ5QLQWp+rtf5ca20DDwOTwyCXF6cbZJ7WegROS/e1MMi1z49wWuarQ5EpRLleA67RWncArgX+pZQKek7qsC7+gYHHucDtWuvXcCaNq38/x6NNGpcLJAX25gS2bcwkc8ciW4sIRS6lVDzwCc5/1LMDh6ytmkspFa2UOqfeohnAwNbOBZwBpAELlVIrA8+5UimV0Jq5AuNJN9VbZAC+w61/rHLhtPRLtdb/CTx+i8ZN+d7SufY5B3gn2DyhyqWcOdJ6a63/DaC1fj+wTXqw2cK220cp1Qmnu2GK1npeYPEy50eqJ87ZHj/DGTxpUKCbYBEwBeeP7FJgZjhkawkhzDUD2ABcq7UO+uglRLlqgWeUUtu01itwDqGDmgU2RH9jL+GcubLvOe3AwFyr5gLKgN8ppb7QWi/D6Vr5V2vn0lr/oJTarpSarLWeCZwJrGjtXPWMIcgB6BDnygeqlFJjtdaLAjuTUq11XrD5wrb4A7cC0cDj9fpR/wpchjPiHQ38l/2DuYfzK+A1pdTdOH2NF4VRtlALOpdyTlc8G+dsmq8Dz7NTa/3j1syltfYrpaYALwSO5HYAVwWRKSS5WkioPq8LgeeUUjHAOpzGT6vmCjgPeF4p9QhQAvwiTHIBdMdpnYdCKH6PtlLqPODPgd9jKc5MyUGTid2EEMKFwrrPXwghRMuQ4i+EEC4kxV8IIVxIir8QQriQFH8hhHChcD7VU4gWo5R6BhgGnKi19geWeYCFwGcHz7QoxPFGWv7CrW7BmSTrjnrL7gD8wNRWSSTEMSTn+QvXCkwS9znOzK8G8DEwQmu9IzCVxJ1ABFCOMzvjMuXMRf88kIFzmf1m4AKtdb5SajvOVceDgN9prT861u9JiMaSlr9wrcDkXXfhTM/wCnBloPD3Bu4FTg/MOf8rnMm0onEux1+otR6DM0NlLQfOlLlKa91HCr8Id1L8hatprf+M07JfGphrBpwbcHQAPgtM1vY6zkyMPbTWjwFfKqVuBp7BuSFH/bs9LTpm4YUIggz4CuFMsPVDvcce4FOtdV2LPjBJ1w6l1GM43TqvAp/h3Iqv/vS6Qd8iVIhjQVr+QhxqLjBZKZUDdTdrWYkzEdfpwBNa6xk4My6egrOzEKJNkeIvxEECt7C8Dvi7UmoV8AfgLK11Bc5YwFNKqW9xpkheBPRstbBCNJOc7SOEEC4kLX8hhHAhKf5CCOFCUvyFEMKFpPgLIYQLSfEXQggXkuIvhBAuJMVfCCFcSIq/EEK40P8DNZW9JJVm+qkAAAAASUVORK5CYII=\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "fuel = pd.read_csv('data/fuel-prices.csv')\n",
    "fuel['Date'] = pd.to_datetime(fuel['Date'], dayfirst=True)\n",
    "fuel['Year'] = fuel['Date'].dt.year\n",
    "ann_fuel = fuel.groupby('Year').mean()\n",
    "ann_fuel.plot(ylim=(0,150));"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "extensions": {
     "jupyter_dashboards": {
      "version": 1,
      "views": {
       "grid_default": {},
       "report_default": {
        "hidden": false
       }
      }
     }
    }
   },
   "source": [
    "## Air pollution"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 16,
   "metadata": {
    "extensions": {
     "jupyter_dashboards": {
      "version": 1,
      "views": {
       "grid_default": {},
       "report_default": {
        "hidden": true
       }
      }
     }
    }
   },
   "outputs": [],
   "source": [
    "nox = pd.read_csv('data/nox.csv')\n",
    "nox['Date'] = pd.to_datetime(nox['Month'], dayfirst=True)\n",
    "nox['Month'] = nox['Date'].dt.month\n",
    "nox['Year'] = nox['Date'].dt.year\n",
    "nox = nox.drop('Date', axis=1)\n",
    "year_poll = nox.groupby('Year').mean()\n",
    "hour_poll = nox.groupby('GMT').mean()\n",
    "month_poll = nox.groupby('Month').mean()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 17,
   "metadata": {
    "extensions": {
     "jupyter_dashboards": {
      "version": 1,
      "views": {
       "grid_default": {},
       "report_default": {
        "hidden": false
       }
      }
     }
    }
   },
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "year_poll.plot(y='Roadside',ylim=(0,80));\n",
    "month_poll.plot(y='Roadside',ylim=(0,80));\n",
    "hour_poll.plot(y='Roadside',ylim=(0,80));"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "extensions": {
     "jupyter_dashboards": {
      "version": 1,
      "views": {
       "grid_default": {},
       "report_default": {
        "hidden": false
       }
      }
     }
    }
   },
   "source": [
    "- Roadside pollution has declined a little faster than private transport volumes; vehicles may be getting cleaner or and/or the composition of vehicles types may be changing.\n",
    "- Cycling does not decline in the summer months like roadside pollution does. Possible further investigation could be made into the effect of school holidays on overall journey volumes, the amount of people who switch modes of transport in summer (car to bike), and the contribution of the school run to road traffic volumes.\n",
    "- Daily pollution levels follow a similar pattern to bike use, with peaks in the morning and afternoon rush hours."
   ]
  }
 ],
 "metadata": {
  "extensions": {
   "jupyter_dashboards": {
    "activeView": "report_default",
    "version": 1,
    "views": {
     "grid_default": {
      "name": "grid",
      "type": "grid"
     },
     "report_default": {
      "name": "report",
      "type": "report"
     }
    }
   }
  },
  "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": "3.6.6"
  }
 },
 "nbformat": 4,
 "nbformat_minor": 2
}