ipynb/Bike-Stats.ipynb

{
 "cells": [
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "<div align=\"right\" style=\"text-align: right\"><i>Peter Norvig, Oct 2017<br>Data updated regularly</i></div>\n",
    "\n",
    "# Bicycling Statistics\n",
    "\n",
    "During a pandemic, bicycling is a great way to (1) spend some time, (2) get some exercise, (3) stay outside and be safe, and (4) track how you are progressing against your goals. My data comes from [Strava](https://www.strava.com/athletes/575579). At various times I've had various goals:\n",
    "- **Distance**: I do about 6,000 miles a year.\n",
    "- **Climbing**: In 2022, I climbed to *space* (100 km of total elevation gain).\n",
    "- **Explorer Tiles**: In 2022, I started tracking the 1-mile-square [explorer tiles](https://rideeverytile.com/) I have visited.\n",
    "- **Wandering**: In 2020, I started using [Wandrer.earth](https://wandrer.earth/athletes/3534/) to track what new roads I have ridden.\n",
    "- **Eddington Number**: I've done 67 miles or more on 67 different days. So 67 is my Eddington Number.\n",
    "- **Speed**: I'm not going particularly fast, but I am interested in understanding how my speed varies with the steepness of the hill.\n",
    "\n",
    "This notebook is mostly for my own benefit, but if you're a cyclist you're welcome to adapt it to your own data, and if you're a data scientist, you might find it an interesting example of exploratory data analysis.  The companion notebook [**BikeCode.ipynb**](BikeCode.ipynb) has the implementation details."
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# Yearly Totals\n",
    "\n",
    "Here are my overall stats for each year since I started keeping track in mid-2014. I have done 6,000 miles per year since 2016, except for 2020 when an injury kept me sidelined for two months. The columns keep track of speed/distance (**mph** is the speed, computed as the quotient of **miles* and **hours**; **kms** is the metric conversion of **miles**) and climbing (**feet** is the total height climbed (or **km_up** in metric), **vam** is vertical meters ascended per hour, **fpm** is average feet ascended per mile and **pct** is average grade of climbing (**fpm** × 100 / 5280).\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 92,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
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       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>year</th>\n",
       "      <th>hours</th>\n",
       "      <th>miles</th>\n",
       "      <th>feet</th>\n",
       "      <th>mph</th>\n",
       "      <th>vam</th>\n",
       "      <th>fpm</th>\n",
       "      <th>pct</th>\n",
       "      <th>kms</th>\n",
       "      <th>km_up</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th></th>\n",
       "      <td>2022</td>\n",
       "      <td>532.93</td>\n",
       "      <td>6028</td>\n",
       "      <td>362323</td>\n",
       "      <td>11.31</td>\n",
       "      <td>207.0</td>\n",
       "      <td>60.0</td>\n",
       "      <td>1.14</td>\n",
       "      <td>9699.05</td>\n",
       "      <td>110.4</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th></th>\n",
       "      <td>2021</td>\n",
       "      <td>490.53</td>\n",
       "      <td>6064</td>\n",
       "      <td>196634</td>\n",
       "      <td>12.36</td>\n",
       "      <td>122.0</td>\n",
       "      <td>32.0</td>\n",
       "      <td>0.61</td>\n",
       "      <td>9756.98</td>\n",
       "      <td>59.9</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th></th>\n",
       "      <td>2020</td>\n",
       "      <td>438.88</td>\n",
       "      <td>5341</td>\n",
       "      <td>94777</td>\n",
       "      <td>12.17</td>\n",
       "      <td>66.0</td>\n",
       "      <td>18.0</td>\n",
       "      <td>0.34</td>\n",
       "      <td>8593.67</td>\n",
       "      <td>28.9</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th></th>\n",
       "      <td>2019</td>\n",
       "      <td>476.32</td>\n",
       "      <td>6016</td>\n",
       "      <td>149797</td>\n",
       "      <td>12.63</td>\n",
       "      <td>96.0</td>\n",
       "      <td>25.0</td>\n",
       "      <td>0.47</td>\n",
       "      <td>9679.74</td>\n",
       "      <td>45.7</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th></th>\n",
       "      <td>2018</td>\n",
       "      <td>475.93</td>\n",
       "      <td>6101</td>\n",
       "      <td>158642</td>\n",
       "      <td>12.82</td>\n",
       "      <td>102.0</td>\n",
       "      <td>26.0</td>\n",
       "      <td>0.49</td>\n",
       "      <td>9816.51</td>\n",
       "      <td>48.4</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th></th>\n",
       "      <td>2017</td>\n",
       "      <td>567.33</td>\n",
       "      <td>7356</td>\n",
       "      <td>202096</td>\n",
       "      <td>12.97</td>\n",
       "      <td>109.0</td>\n",
       "      <td>27.0</td>\n",
       "      <td>0.52</td>\n",
       "      <td>11835.80</td>\n",
       "      <td>61.6</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th></th>\n",
       "      <td>2016</td>\n",
       "      <td>486.38</td>\n",
       "      <td>6339</td>\n",
       "      <td>201453</td>\n",
       "      <td>13.03</td>\n",
       "      <td>126.0</td>\n",
       "      <td>32.0</td>\n",
       "      <td>0.60</td>\n",
       "      <td>10199.45</td>\n",
       "      <td>61.4</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th></th>\n",
       "      <td>2015</td>\n",
       "      <td>419.95</td>\n",
       "      <td>5452</td>\n",
       "      <td>209859</td>\n",
       "      <td>12.98</td>\n",
       "      <td>152.0</td>\n",
       "      <td>38.0</td>\n",
       "      <td>0.73</td>\n",
       "      <td>8772.27</td>\n",
       "      <td>64.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th></th>\n",
       "      <td>2014</td>\n",
       "      <td>191.03</td>\n",
       "      <td>2469</td>\n",
       "      <td>118481</td>\n",
       "      <td>12.92</td>\n",
       "      <td>189.0</td>\n",
       "      <td>48.0</td>\n",
       "      <td>0.91</td>\n",
       "      <td>3972.62</td>\n",
       "      <td>36.1</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "  year   hours  miles    feet    mph    vam   fpm   pct       kms  km_up\n",
       "  2022  532.93   6028  362323  11.31  207.0  60.0  1.14   9699.05  110.4\n",
       "  2021  490.53   6064  196634  12.36  122.0  32.0  0.61   9756.98   59.9\n",
       "  2020  438.88   5341   94777  12.17   66.0  18.0  0.34   8593.67   28.9\n",
       "  2019  476.32   6016  149797  12.63   96.0  25.0  0.47   9679.74   45.7\n",
       "  2018  475.93   6101  158642  12.82  102.0  26.0  0.49   9816.51   48.4\n",
       "  2017  567.33   7356  202096  12.97  109.0  27.0  0.52  11835.80   61.6\n",
       "  2016  486.38   6339  201453  13.03  126.0  32.0  0.60  10199.45   61.4\n",
       "  2015  419.95   5452  209859  12.98  152.0  38.0  0.73   8772.27   64.0\n",
       "  2014  191.03   2469  118481  12.92  189.0  48.0  0.91   3972.62   36.1"
      ]
     },
     "execution_count": 92,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "%run BikeCode.ipynb\n",
    "\n",
    "yearly"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "And here's the same data on a daily basis, assuming 350 days of riding in a year:"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 93,
   "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>hours</th>\n",
       "      <th>miles</th>\n",
       "      <th>feet</th>\n",
       "      <th>mph</th>\n",
       "      <th>vam</th>\n",
       "      <th>fpm</th>\n",
       "      <th>pct</th>\n",
       "      <th>kms</th>\n",
       "      <th>km_up</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th></th>\n",
       "      <td>2022</td>\n",
       "      <td>1.5</td>\n",
       "      <td>17.2</td>\n",
       "      <td>1035.2</td>\n",
       "      <td>11.31</td>\n",
       "      <td>207.0</td>\n",
       "      <td>60.0</td>\n",
       "      <td>1.14</td>\n",
       "      <td>27.7</td>\n",
       "      <td>0.315</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th></th>\n",
       "      <td>2021</td>\n",
       "      <td>1.4</td>\n",
       "      <td>17.3</td>\n",
       "      <td>561.8</td>\n",
       "      <td>12.36</td>\n",
       "      <td>122.0</td>\n",
       "      <td>32.0</td>\n",
       "      <td>0.61</td>\n",
       "      <td>27.9</td>\n",
       "      <td>0.171</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th></th>\n",
       "      <td>2020</td>\n",
       "      <td>1.3</td>\n",
       "      <td>15.3</td>\n",
       "      <td>270.8</td>\n",
       "      <td>12.17</td>\n",
       "      <td>66.0</td>\n",
       "      <td>18.0</td>\n",
       "      <td>0.34</td>\n",
       "      <td>24.6</td>\n",
       "      <td>0.083</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th></th>\n",
       "      <td>2019</td>\n",
       "      <td>1.4</td>\n",
       "      <td>17.2</td>\n",
       "      <td>428.0</td>\n",
       "      <td>12.63</td>\n",
       "      <td>96.0</td>\n",
       "      <td>25.0</td>\n",
       "      <td>0.47</td>\n",
       "      <td>27.7</td>\n",
       "      <td>0.131</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th></th>\n",
       "      <td>2018</td>\n",
       "      <td>1.4</td>\n",
       "      <td>17.4</td>\n",
       "      <td>453.3</td>\n",
       "      <td>12.82</td>\n",
       "      <td>102.0</td>\n",
       "      <td>26.0</td>\n",
       "      <td>0.49</td>\n",
       "      <td>28.0</td>\n",
       "      <td>0.138</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th></th>\n",
       "      <td>2017</td>\n",
       "      <td>1.6</td>\n",
       "      <td>21.0</td>\n",
       "      <td>577.4</td>\n",
       "      <td>12.97</td>\n",
       "      <td>109.0</td>\n",
       "      <td>27.0</td>\n",
       "      <td>0.52</td>\n",
       "      <td>33.8</td>\n",
       "      <td>0.176</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th></th>\n",
       "      <td>2016</td>\n",
       "      <td>1.4</td>\n",
       "      <td>18.1</td>\n",
       "      <td>575.6</td>\n",
       "      <td>13.03</td>\n",
       "      <td>126.0</td>\n",
       "      <td>32.0</td>\n",
       "      <td>0.60</td>\n",
       "      <td>29.1</td>\n",
       "      <td>0.175</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th></th>\n",
       "      <td>2015</td>\n",
       "      <td>1.2</td>\n",
       "      <td>15.6</td>\n",
       "      <td>599.6</td>\n",
       "      <td>12.98</td>\n",
       "      <td>152.0</td>\n",
       "      <td>38.0</td>\n",
       "      <td>0.73</td>\n",
       "      <td>25.1</td>\n",
       "      <td>0.183</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th></th>\n",
       "      <td>2014</td>\n",
       "      <td>0.5</td>\n",
       "      <td>7.1</td>\n",
       "      <td>338.5</td>\n",
       "      <td>12.92</td>\n",
       "      <td>189.0</td>\n",
       "      <td>48.0</td>\n",
       "      <td>0.91</td>\n",
       "      <td>11.4</td>\n",
       "      <td>0.103</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "  year  hours  miles    feet    mph    vam   fpm   pct   kms  km_up\n",
       "  2022    1.5   17.2  1035.2  11.31  207.0  60.0  1.14  27.7  0.315\n",
       "  2021    1.4   17.3   561.8  12.36  122.0  32.0  0.61  27.9  0.171\n",
       "  2020    1.3   15.3   270.8  12.17   66.0  18.0  0.34  24.6  0.083\n",
       "  2019    1.4   17.2   428.0  12.63   96.0  25.0  0.47  27.7  0.131\n",
       "  2018    1.4   17.4   453.3  12.82  102.0  26.0  0.49  28.0  0.138\n",
       "  2017    1.6   21.0   577.4  12.97  109.0  27.0  0.52  33.8  0.176\n",
       "  2016    1.4   18.1   575.6  13.03  126.0  32.0  0.60  29.1  0.175\n",
       "  2015    1.2   15.6   599.6  12.98  152.0  38.0  0.73  25.1  0.183\n",
       "  2014    0.5    7.1   338.5  12.92  189.0  48.0  0.91  11.4  0.103"
      ]
     },
     "execution_count": 93,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "daily"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# Climbing \n",
    "\n",
    "In 2022 my friend [A. J. Jacobs](https://ajjacobs.com/)  set a goal of **walking to space**: climbing a total elevation equal to the distance from the Earth's surface to the top of the atmoshere. [A group](https://www.facebook.com/groups/260966686136038) of about 40 of us joined the quest. The boundary of \"space\" is vague, but could is often reckoned as  either 100 km (the [Kármán line](https://en.wikipedia.org/wiki/K%C3%A1rm%C3%A1n_line)) or [50 miles](https://science.nasa.gov/edge-space); in 2022 I surpassed 100 kilometers of climbing (over 1,000 feet per day), but most years I'm closer to 60 kilometers (about 600 feet per day)."
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "tags": []
   },
   "source": [
    "# Explorer Tiles\n",
    "\n",
    "\n",
    "The [OpenStreetMap](https://www.openstreetmap.org/) world map is divided into **[explorer tiles](https://www.statshunters.com/faq-10-what-are-explorer-tiles)** of approximately 1 mile square.  Sites like [Veloviewer](https://veloviewer.com) and [Statshunter](https://www.statshunters.com/) challenge bicyclist/hikers to record which tiles they have passed through. The process is gamified to highlight the following statistics:\n",
    "- The largest **square** (an *n* × *n* array of visited ties). \n",
    "- The maximum **cluster** (a set of contiguous interior visited tiles, where \"interior\" means surrounded by visited tiles).\n",
    "- The **total** number of visited tiles.\n",
    " \n",
    "\n",
    "Since I live on a penninsula, it is not easy for me to form a large square, and I sometimes have to work hard to connect different parts of my map (such as connecting San Francisco and Marin). I have a [separrate page]() documenting my explorations, but here are a few key points along the way:"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 94,
   "metadata": {},
   "outputs": [
    {
     "data": {
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       "  <thead>\n",
       "    <tr>\n",
       "      <th class=\"blank level0\" >&nbsp;</th>\n",
       "      <th id=\"T_df010_level0_col0\" class=\"col_heading level0 col0\" >date</th>\n",
       "      <th id=\"T_df010_level0_col1\" class=\"col_heading level0 col1\" >square</th>\n",
       "      <th id=\"T_df010_level0_col2\" class=\"col_heading level0 col2\" >cluster</th>\n",
       "      <th id=\"T_df010_level0_col3\" class=\"col_heading level0 col3\" >total</th>\n",
       "      <th id=\"T_df010_level0_col4\" class=\"col_heading level0 col4\" >comment</th>\n",
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       "      <th id=\"T_df010_level0_row0\" class=\"row_heading level0 row0\" ></th>\n",
       "      <td id=\"T_df010_row0_col0\" class=\"data row0 col0\" ><a href=\"https://www.statshunters.com/?to=20230630\" rel=\"noopener noreferrer\" target=\"_blank\">06/30/2023</a></td>\n",
       "      <td id=\"T_df010_row0_col1\" class=\"data row0 col1\" >13</td>\n",
       "      <td id=\"T_df010_row0_col2\" class=\"data row0 col2\" >689</td>\n",
       "      <td id=\"T_df010_row0_col3\" class=\"data row0 col3\" >2640</td>\n",
       "      <td id=\"T_df010_row0_col4\" class=\"data row0 col4\" ><a href=\"https://www.strava.com/activities/9298603815\" rel=\"noopener noreferrer\" target=\"_blank\">Rides in east Bay</a></td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th id=\"T_df010_level0_row1\" class=\"row_heading level0 row1\" ></th>\n",
       "      <td id=\"T_df010_row1_col0\" class=\"data row1 col0\" ><a href=\"https://www.statshunters.com/?to=20230414\" rel=\"noopener noreferrer\" target=\"_blank\">04/14/2023</a></td>\n",
       "      <td id=\"T_df010_row1_col1\" class=\"data row1 col1\" >13</td>\n",
       "      <td id=\"T_df010_row1_col2\" class=\"data row1 col2\" >630</td>\n",
       "      <td id=\"T_df010_row1_col3\" class=\"data row1 col3\" >2595</td>\n",
       "      <td id=\"T_df010_row1_col4\" class=\"data row1 col4\" ><a href=\"https://www.strava.com/activities/8891171008\" rel=\"noopener noreferrer\" target=\"_blank\">Black Sands Beach connects Marin to max cluster</a></td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th id=\"T_df010_level0_row2\" class=\"row_heading level0 row2\" ></th>\n",
       "      <td id=\"T_df010_row2_col0\" class=\"data row2 col0\" ><a href=\"https://www.statshunters.com/?to=20230304\" rel=\"noopener noreferrer\" target=\"_blank\">03/04/2023</a></td>\n",
       "      <td id=\"T_df010_row2_col1\" class=\"data row2 col1\" >13</td>\n",
       "      <td id=\"T_df010_row2_col2\" class=\"data row2 col2\" >583</td>\n",
       "      <td id=\"T_df010_row2_col3\" class=\"data row2 col3\" >2574</td>\n",
       "      <td id=\"T_df010_row2_col4\" class=\"data row2 col4\" ><a href=\"https://www.strava.com/activities/8654437264\" rel=\"noopener noreferrer\" target=\"_blank\">Almaden rides connects Gilroy to max cluster</a></td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th id=\"T_df010_level0_row3\" class=\"row_heading level0 row3\" ></th>\n",
       "      <td id=\"T_df010_row3_col0\" class=\"data row3 col0\" ><a href=\"https://www.statshunters.com/?to=20221022\" rel=\"noopener noreferrer\" target=\"_blank\">10/22/2022</a></td>\n",
       "      <td id=\"T_df010_row3_col1\" class=\"data row3 col1\" >13</td>\n",
       "      <td id=\"T_df010_row3_col2\" class=\"data row3 col2\" >396</td>\n",
       "      <td id=\"T_df010_row3_col3\" class=\"data row3 col3\" >2495</td>\n",
       "      <td id=\"T_df010_row3_col4\" class=\"data row3 col4\" ><a href=\"https://www.strava.com/activities/8003921626\" rel=\"noopener noreferrer\" target=\"_blank\">Alviso levees to get to 13x13 max square</a></td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th id=\"T_df010_level0_row4\" class=\"row_heading level0 row4\" ></th>\n",
       "      <td id=\"T_df010_row4_col0\" class=\"data row4 col0\" ><a href=\"https://www.statshunters.com/?to=20221016\" rel=\"noopener noreferrer\" target=\"_blank\">10/16/2022</a></td>\n",
       "      <td id=\"T_df010_row4_col1\" class=\"data row4 col1\" >12</td>\n",
       "      <td id=\"T_df010_row4_col2\" class=\"data row4 col2\" >393</td>\n",
       "      <td id=\"T_df010_row4_col3\" class=\"data row4 col3\" >2492</td>\n",
       "      <td id=\"T_df010_row4_col4\" class=\"data row4 col4\" ><a href=\"https://www.strava.com/activities/7974994605\" rel=\"noopener noreferrer\" target=\"_blank\">Milpitas ride connects East Bay to max cluster</a></td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th id=\"T_df010_level0_row5\" class=\"row_heading level0 row5\" ></th>\n",
       "      <td id=\"T_df010_row5_col0\" class=\"data row5 col0\" ><a href=\"https://www.statshunters.com/?to=20220908\" rel=\"noopener noreferrer\" target=\"_blank\">09/08/2022</a></td>\n",
       "      <td id=\"T_df010_row5_col1\" class=\"data row5 col1\" >11</td>\n",
       "      <td id=\"T_df010_row5_col2\" class=\"data row5 col2\" >300</td>\n",
       "      <td id=\"T_df010_row5_col3\" class=\"data row5 col3\" >2487</td>\n",
       "      <td id=\"T_df010_row5_col4\" class=\"data row5 col4\" >First started tracking tiles</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n"
      ],
      "text/plain": [
       "<pandas.io.formats.style.Styler at 0x7fd3a8b8deb0>"
      ]
     },
     "execution_count": 94,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "tiles"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# Wandering \n",
    "\n",
    "The website [**Wandrer.earth**](https://wandrer.earth) tracks the  distinct roads a user has biked on. It provides a fun incentive to get out and explore new roads. The site is gamified in a way that there is a reward for first reaching 25% of the road-miles in each city, and further rewards for higher percentages.  (You get no credit for repeating a road you've already been on.) \n",
    "\n",
    "The wandrer.earth site does a good job of showing my current status, but it requires clicking around a bit, so I summarize it all in one place here.  Each line gives the county (e.g. SMC for San Mateo County); city preceeded by the percentage of roads I've rode there; miles rode/total miles in city; and miles to go to the next big reward level."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 95,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "SMC 100.0% Los Trancos OSP                0.3/0.3 mi \n",
      "SMC  99.9% Los Trancos Woods              5.3/5.3 mi \n",
      "SMC  99.9% Menlo Oaks                     3.5/3.5 mi \n",
      "SMC  99.9% Kensington Square              0.6/0.6 mi \n",
      "SMC  99.9% Ladera                         8.1/8.1 mi \n",
      "SMC  99.9% Palomar Park                   4.0/4.0 mi \n",
      "SMC  99.8% North Fair Oaks                  27/27 mi \n",
      "SMC  99.8% Emerald Lake Hills               25/25 mi \n",
      "SMC  99.8% West Menlo Park                  11/11 mi \n",
      "SMC  99.8% Atherton                         56/56 mi \n",
      "SMC  99.7% Sequoia Tract                    11/11 mi \n",
      "SCC  99.6% Los Altos                      138/138 mi \n",
      "SCC  99.6% Loyola                           18/18 mi \n",
      "SMC  99.6% East Palo Alto                   48/48 mi \n",
      "SMC  99.5% Menlo Park                     139/140 mi \n",
      "SMC  99.5% Woodside                         75/75 mi \n",
      "SMC  99.5% Portola Valley                   48/48 mi \n",
      "SMC  99.4% Sky Londa                        12/12 mi \n",
      "SCC  99.4% Los Altos Hills                  91/91 mi \n",
      "SMC  99.3% Redwood City                   239/240 mi \n",
      "SCC  99.2% Mountain View                  206/208 mi \n",
      "SMC  99.1% Windy Hill Preserve            4.1/4.1 mi \n",
      "SMC  99.0% San Carlos                       98/99 mi \n",
      "SCC  99.0% Palo Alto                      294/297 mi \n",
      "SMC  91.6% Burleigh Murray Park           1.9/2.1 mi   0.2 mi for 99%\n",
      "SCC  86.8% Foothills Preserve             1.0/1.1 mi   0.0 mi for 90%\n",
      "SMC  80.7% Foster City                    121/150 mi    14 mi for 90%\n",
      "SMC  77.9% San Mateo Highlands              14/18 mi   2.2 mi for 90%\n",
      "SMC  74.9% Skyline Ridge OSP              0.6/0.8 mi   0.1 mi for 90%\n",
      "SMC  71.4% Burlingame Hills               4.3/6.0 mi   1.1 mi for 90%\n",
      "SMC  66.7% Coal Creek Preserve            2.6/3.9 mi   0.9 mi for 90%\n",
      "SCC  62.7% San Francisco Bay Trail        164/261 mi    71 mi for 90%\n",
      "---  61.6% San Mateo County           1,732/2,814 mi   800 mi for 90%\n",
      "SMC  54.3% Burlingame                       48/88 mi    32 mi for 90%\n",
      "SMC  54.2% Belmont                          53/98 mi    35 mi for 90%\n",
      "SCC  52.4% Sunnyvale                      187/357 mi   134 mi for 90%\n",
      "SMC  52.3% Hillsborough                     45/85 mi    32 mi for 90%\n",
      "SMC  51.8% San Mateo                      133/256 mi    98 mi for 90%\n",
      "SMC  51.5% Half Moon Bay State Beach      2.3/4.4 mi   1.7 mi for 90%\n",
      "SMC  51.2% Russian Ridge Preserve          6.2/12 mi   4.7 mi for 90%\n",
      "SMC  51.2% Long Ridge Preserve             5.6/11 mi   4.3 mi for 90%\n",
      "SCC  51.2% Castle Rock State Park          5.7/11 mi   4.3 mi for 90%\n",
      "NSW  47.3% Barangaroo                     0.8/1.7 mi   0.0 mi for 50%\n",
      "SCC  47.2% Gardner                          11/23 mi   0.7 mi for 50%\n",
      "SCC  47.0% Edenvale                         14/30 mi   0.9 mi for 50%\n",
      "SMC  46.7% Brisbane                         19/41 mi   1.3 mi for 50%\n",
      "ALA  45.9% Newark                          67/147 mi   6.0 mi for 50%\n",
      "SCC  44.7% Monte Sereno                    9.1/20 mi   1.1 mi for 50%\n",
      "SMC  44.3% Moss Beach                      8.7/20 mi   1.1 mi for 50%\n",
      "SFC  43.9% Presidio Terrace               1.2/2.8 mi   0.2 mi for 50%\n",
      "ALA  43.3% Hayward Acres                  1.5/3.5 mi   0.2 mi for 50%\n",
      "ALA  40.8% San Lorenzo                      23/56 mi   5.1 mi for 50%\n",
      "SMC  40.8% Millbrae                         27/65 mi   6.0 mi for 50%\n",
      "SFC  39.6% Lincoln Park                   1.8/4.5 mi   0.5 mi for 50%\n",
      "SCC  39.5% Communications Hill              11/28 mi   2.9 mi for 50%\n",
      "SMC  38.7% Purisima Creek Preserve         6.4/16 mi   1.9 mi for 50%\n",
      "MAR  38.7% Mt Tamalpais State Park          12/32 mi   3.6 mi for 50%\n",
      "SMC  38.4% El Granada                       19/49 mi   5.7 mi for 50%\n",
      "SMC  38.3% Colma                           5.2/14 mi   1.6 mi for 50%\n",
      "SMC  38.2% Broadmoor                      3.4/8.8 mi   1.0 mi for 50%\n",
      "SFC  37.4% South Beach                    1.8/4.8 mi   0.6 mi for 50%\n",
      "SCC  37.3% Milpitas                        84/224 mi    28 mi for 50%\n",
      "MAR  37.1% Muir Beach                     1.7/4.6 mi   0.6 mi for 50%\n",
      "SFC  36.8% Lake Street                    1.4/3.9 mi   0.5 mi for 50%\n",
      "SCC  35.7% Spartan Keyes                    23/64 mi   9.2 mi for 50%\n",
      "ALA  35.7% Ashland                          13/35 mi   5.0 mi for 50%\n",
      "SCC  34.9% Willow Glen                      28/82 mi    12 mi for 50%\n",
      "MAS  34.7% MIT                            3.3/9.6 mi   1.5 mi for 50%\n",
      "NSW  34.3% Millers Point                  1.1/3.2 mi   0.5 mi for 50%\n",
      "SCC  34.0% Santa Clara                    118/348 mi    56 mi for 50%\n",
      "SCC  33.6% Seven Trees                      14/41 mi   6.7 mi for 50%\n",
      "SCC  33.4% Parkview                         14/42 mi   7.1 mi for 50%\n",
      "SCC  33.2% Cupertino                       57/172 mi    29 mi for 50%\n",
      "SCC  33.2% Los Gatos                       49/148 mi    25 mi for 50%\n",
      "MAR  32.9% Stinson Beach                   3.7/11 mi   1.9 mi for 50%\n",
      "---  32.8% Santa Clara County         2,483/7,569 mi 1,302 mi for 50%\n",
      "SMC  32.7% Montara                         9.1/28 mi   4.8 mi for 50%\n",
      "SMC  32.7% Pacifica                        49/151 mi    26 mi for 50%\n",
      "SCC  32.7% Branham                          14/44 mi   7.6 mi for 50%\n",
      "SMC  32.2% Half Moon Bay                    22/68 mi    12 mi for 50%\n",
      "ALA  32.2% Fremont                        251/780 mi   139 mi for 50%\n",
      "MAR  31.9% Marin Headlands GGNRA            21/66 mi    12 mi for 50%\n",
      "SCC  31.1% San Martin                       11/35 mi   6.7 mi for 50%\n",
      "SCC  30.7% Forest of Nisene Marks SP        14/44 mi   8.5 mi for 50%\n",
      "ALA  30.7% Union City                      64/209 mi    40 mi for 50%\n",
      "SCC  30.5% Willow Glen South                19/63 mi    12 mi for 50%\n",
      "ALA  30.0% Hayward                        133/444 mi    89 mi for 50%\n",
      "SCC  29.7% Saratoga                        53/180 mi    37 mi for 50%\n",
      "SMC  29.5% San Bruno                       34/114 mi    23 mi for 50%\n",
      "SFC  29.4% Golden Gate Park                 12/41 mi   8.4 mi for 50%\n",
      "SFC  29.3% Seacliff                       1.2/4.1 mi   0.8 mi for 50%\n",
      "CCC  29.3% Rosie Riveter Park             1.6/5.5 mi   1.1 mi for 50%\n",
      "NSW  29.2% Dawes Point                    0.5/1.8 mi   0.4 mi for 50%\n",
      "SCC  28.8% Campbell                        34/119 mi    25 mi for 50%\n",
      "SCC  27.7% San Jose                     725/2,619 mi   584 mi for 50%\n",
      "ALA  27.5% San Leandro                     63/231 mi    52 mi for 50%\n",
      "SMC  27.2% South San Francisco             50/185 mi    42 mi for 50%\n",
      "SMC  27.2% Daly City                       40/148 mi    34 mi for 50%\n",
      "ALA  27.1% Cherryland                      5.7/21 mi   4.8 mi for 50%\n",
      "CAL  26.8% Mokelumne Hill                  3.9/15 mi   3.4 mi for 50%\n",
      "SFC  26.7% Presidio National Park           12/44 mi    10 mi for 50%\n",
      "SON  23.6% Guerneville                     5.4/23 mi   0.3 mi for 25%\n",
      "SFC  21.6% Presidio Heights               1.4/6.5 mi   0.2 mi for 25%\n",
      "SMC  21.4% Bay Area Ridge Trail            85/396 mi    14 mi for 25%\n",
      "SFC  20.6% Panhandle                      1.5/7.3 mi   0.3 mi for 25%\n",
      "SFC  18.2% Polk Gulch                     0.7/4.0 mi   0.3 mi for 25%\n",
      "SFC  18.2% Balboa Terrace                 0.6/3.4 mi   0.2 mi for 25%\n",
      "SFC  18.0% Cole Valley                    0.3/1.7 mi   0.1 mi for 25%\n",
      "SON  17.8% Healdsburg                      9.6/54 mi   3.9 mi for 25%\n",
      "SON  17.0% Bodega Bay                      4.9/29 mi   2.3 mi for 25%\n",
      "SFC  15.9% Forest Hill                    1.0/6.1 mi   0.6 mi for 25%\n",
      "SFC  15.5% Northern Waterfront            0.9/5.6 mi   0.5 mi for 25%\n",
      "SFC  15.4% Aquatic Park Fort Mason        1.0/6.4 mi   0.6 mi for 25%\n",
      "---  15.4% Alameda County               895/5,818 mi   560 mi for 25%\n",
      "SFC  15.2% Little Hollywood               0.6/3.7 mi   0.4 mi for 25%\n",
      "SFC  14.2% Clarendon Heights              0.9/6.0 mi   0.6 mi for 25%\n",
      "SFC  13.8% Fisherman's Wharf              0.9/6.2 mi   0.7 mi for 25%\n",
      "SFC  13.2% Sutro Heights                  0.9/7.1 mi   0.8 mi for 25%\n",
      "SFC  13.0% Ashbury Heights                0.5/3.7 mi   0.4 mi for 25%\n",
      "MAR  12.9% Corte Madera                    6.6/51 mi   6.2 mi for 25%\n",
      "MAR  12.9% Sausalito                       4.2/33 mi   4.0 mi for 25%\n",
      "SFC  12.3% Dogpatch                       0.6/5.1 mi   0.6 mi for 25%\n",
      "ALA  12.2% Alameda                         25/207 mi    26 mi for 25%\n",
      "SCC  12.1% Gilroy                          23/189 mi    24 mi for 25%\n",
      "SFC  11.9% Cow Hollow                      1.4/12 mi   1.6 mi for 25%\n",
      "---  10.8% Marin County                 251/2,333 mi   332 mi for 25%\n",
      "SFC  10.7% Golden Gate Heights             1.9/18 mi   2.5 mi for 25%\n",
      "SFC  10.7% Pacific Heights                 1.9/18 mi   2.6 mi for 25%\n",
      "SFC  10.2% Financial District             1.0/9.4 mi   1.4 mi for 25%\n",
      "MAR   9.1% Mill Valley                     8.4/92 mi    15 mi for 25%\n",
      "SFC   8.6% Mission Bay                     1.2/14 mi   2.3 mi for 25%\n",
      "ALA   8.0% Emeryville                      2.2/28 mi   4.8 mi for 25%\n",
      "ALA   7.4% Berkeley                        19/260 mi    46 mi for 25%\n",
      "---   7.2% San Francisco County          88/1,217 mi   217 mi for 25%\n",
      "---   7.1% Santa Cruz County            194/2,718 mi   486 mi for 25%\n",
      "ALA   6.8% Albany                          2.9/43 mi   7.8 mi for 25%\n",
      "MAS   6.2% Cambridge                       11/181 mi    34 mi for 25%\n",
      "SFC   6.0% Central Waterfront              0.6/10 mi   1.9 mi for 25%\n",
      "---   5.1% Sonoma County                251/4,895 mi   973 mi for 25%\n",
      "---   4.8% Napa County                   78/1,609 mi   324 mi for 25%\n",
      "MAR   3.7% San Rafael                     9.6/260 mi    55 mi for 25%\n",
      "---   2.0% Contra Costa County          122/5,945 mi 1,364 mi for 25%\n",
      "---   1.7% California                 6,450/0.38M mi 1,090 mi for 2%\n",
      "---   0.1% USA                         6,840/6.4M mi 5,973 mi for 0.2%\n",
      "--- 0.017% Earth                        7,202/42M mi 1,192 mi for 0.02%\n"
     ]
    }
   ],
   "source": [
    "wandering(by='pct')"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "As part of my wandering, in April 2022 I was able to get to 25% of every city that  rings the San Francisco Bay and is below San Francisco or  Oakland (see map [with](ring2.jpeg) or [without](ring1.jpeg) roads traveled; as soon as you get 25% of a city, it lights up with a color).\n",
    "\n",
    "I live at the border of Santa Clara County (SCC) and San Mateo County (SMC), so I ride in both. Wandrer.earth says that Jason Molenda is a whopping 1,700 miles ahead of me in SMC and Megan Gardner is 1,000 miles ahead of me in SCC. Barry Mann is the leader in both total miles in the two counties and average percent. Kudos to all of them! However, I do occupy a small section of the [Pareto front](https://en.wikipedia.org/wiki/Pareto_front) for the two counties together: no single rider on wandrer.earth has done more than me in *both* counties. Here are the leaders (as of September 2023), where the dotted line indicates the five riders on the Pareto front."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 96,
   "metadata": {},
   "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>Name</th>\n",
       "      <th>Initials</th>\n",
       "      <th>SMC %</th>\n",
       "      <th>SCC %</th>\n",
       "      <th>SMC miles</th>\n",
       "      <th>SCC miles</th>\n",
       "      <th>Total miles</th>\n",
       "      <th>Avg %</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th></th>\n",
       "      <td>Barry Mann</td>\n",
       "      <td>BM</td>\n",
       "      <td>76.97</td>\n",
       "      <td>30.21</td>\n",
       "      <td>2166</td>\n",
       "      <td>2287</td>\n",
       "      <td>4453</td>\n",
       "      <td>53.590</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th></th>\n",
       "      <td>Megan Gardner</td>\n",
       "      <td>MG</td>\n",
       "      <td>97.62</td>\n",
       "      <td>8.69</td>\n",
       "      <td>2747</td>\n",
       "      <td>658</td>\n",
       "      <td>3405</td>\n",
       "      <td>53.155</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th></th>\n",
       "      <td>Peter Norvig</td>\n",
       "      <td>PN</td>\n",
       "      <td>61.56</td>\n",
       "      <td>32.80</td>\n",
       "      <td>1732</td>\n",
       "      <td>2483</td>\n",
       "      <td>4215</td>\n",
       "      <td>47.180</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th></th>\n",
       "      <td>Matthew Ring</td>\n",
       "      <td>MR</td>\n",
       "      <td>78.85</td>\n",
       "      <td>1.48</td>\n",
       "      <td>2219</td>\n",
       "      <td>112</td>\n",
       "      <td>2331</td>\n",
       "      <td>40.165</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th></th>\n",
       "      <td>Brian Feinberg</td>\n",
       "      <td>BF</td>\n",
       "      <td>32.50</td>\n",
       "      <td>43.68</td>\n",
       "      <td>915</td>\n",
       "      <td>3306</td>\n",
       "      <td>4221</td>\n",
       "      <td>38.090</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th></th>\n",
       "      <td>Jason Molenda</td>\n",
       "      <td>JM</td>\n",
       "      <td>7.13</td>\n",
       "      <td>55.39</td>\n",
       "      <td>201</td>\n",
       "      <td>4192</td>\n",
       "      <td>4393</td>\n",
       "      <td>31.260</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th></th>\n",
       "      <td>Elliot  Hoff</td>\n",
       "      <td>EF</td>\n",
       "      <td>52.88</td>\n",
       "      <td>8.14</td>\n",
       "      <td>1488</td>\n",
       "      <td>616</td>\n",
       "      <td>2104</td>\n",
       "      <td>30.510</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th></th>\n",
       "      <td>Jim Brooks</td>\n",
       "      <td>JB</td>\n",
       "      <td>4.23</td>\n",
       "      <td>44.36</td>\n",
       "      <td>119</td>\n",
       "      <td>3358</td>\n",
       "      <td>3477</td>\n",
       "      <td>24.295</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "            Name Initials  SMC %  SCC %  SMC miles  SCC miles  Total miles  \\\n",
       "      Barry Mann       BM  76.97  30.21       2166       2287         4453   \n",
       "   Megan Gardner       MG  97.62   8.69       2747        658         3405   \n",
       "    Peter Norvig       PN  61.56  32.80       1732       2483         4215   \n",
       "    Matthew Ring       MR  78.85   1.48       2219        112         2331   \n",
       "  Brian Feinberg       BF  32.50  43.68        915       3306         4221   \n",
       "   Jason Molenda       JM   7.13  55.39        201       4192         4393   \n",
       "    Elliot  Hoff       EF  52.88   8.14       1488        616         2104   \n",
       "      Jim Brooks       JB   4.23  44.36        119       3358         3477   \n",
       "\n",
       "   Avg %  \n",
       "  53.590  \n",
       "  53.155  \n",
       "  47.180  \n",
       "  40.165  \n",
       "  38.090  \n",
       "  31.260  \n",
       "  30.510  \n",
       "  24.295  "
      ]
     },
     "execution_count": 96,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 864x432 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "pareto_front(leaders)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# Eddington Number\n",
    "\n",
    "The British physicist [Sir Arthur Eddington](https://en.wikipedia.org/wiki/Arthur_Eddington), a contemporary of Einstein, was a pre-Strava bicyclist who favored this metric:\n",
    "\n",
    "> Your [**Eddington Number**](https://www.triathlete.com/2011/04/training/measuring-bike-miles-eddington-number_301789) is the largest integer **e** such that you have cycled at least **e** miles on at least **e** days.\n",
    "\n",
    "My Eddington number progress over the years, in both kilometers and miles:"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 97,
   "metadata": {},
   "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>year</th>\n",
       "      <th>Ed_km</th>\n",
       "      <th>Ed_mi</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th></th>\n",
       "      <td>2023</td>\n",
       "      <td>101</td>\n",
       "      <td>67</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th></th>\n",
       "      <td>2022</td>\n",
       "      <td>96</td>\n",
       "      <td>66</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th></th>\n",
       "      <td>2021</td>\n",
       "      <td>93</td>\n",
       "      <td>65</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th></th>\n",
       "      <td>2020</td>\n",
       "      <td>87</td>\n",
       "      <td>62</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th></th>\n",
       "      <td>2019</td>\n",
       "      <td>80</td>\n",
       "      <td>56</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th></th>\n",
       "      <td>2018</td>\n",
       "      <td>77</td>\n",
       "      <td>54</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th></th>\n",
       "      <td>2017</td>\n",
       "      <td>73</td>\n",
       "      <td>51</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th></th>\n",
       "      <td>2016</td>\n",
       "      <td>67</td>\n",
       "      <td>47</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th></th>\n",
       "      <td>2015</td>\n",
       "      <td>61</td>\n",
       "      <td>42</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th></th>\n",
       "      <td>2014</td>\n",
       "      <td>46</td>\n",
       "      <td>35</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "  year  Ed_km  Ed_mi\n",
       "  2023    101     67\n",
       "  2022     96     66\n",
       "  2021     93     65\n",
       "  2020     87     62\n",
       "  2019     80     56\n",
       "  2018     77     54\n",
       "  2017     73     51\n",
       "  2016     67     47\n",
       "  2015     61     42\n",
       "  2014     46     35"
      ]
     },
     "execution_count": 97,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "Ed_progress(rides)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "My current Eddington Number is **101** in kilometers and **67** in miles: I've ridden at least 67 miles on at least 67 days (but not 68 miles on 68 days). My number is above [the median for Strava](https://swinny.net/Cycling/-4687-Calculate-your-Eddington-Number), but not nearly as good as Eddington himself: his number was **84** in miles when he died at age 62, and his roads, bicycles, and navigation aids were not nearly as nice as mine, so bravo zulu to him. "
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "How many more rides will I need to reach higher Eddington numbers? I call that the *Eddington Gap*:"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 98,
   "metadata": {},
   "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>kms</th>\n",
       "      <th>km rides</th>\n",
       "      <th>kms gap</th>\n",
       "      <th>miles</th>\n",
       "      <th>miles rides</th>\n",
       "      <th>miles gap</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th></th>\n",
       "      <td>100</td>\n",
       "      <td>107</td>\n",
       "      <td>-7</td>\n",
       "      <td>67</td>\n",
       "      <td>74</td>\n",
       "      <td>-7</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th></th>\n",
       "      <td>101</td>\n",
       "      <td>105</td>\n",
       "      <td>-4</td>\n",
       "      <td>68</td>\n",
       "      <td>67</td>\n",
       "      <td>1</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th></th>\n",
       "      <td>102</td>\n",
       "      <td>99</td>\n",
       "      <td>3</td>\n",
       "      <td>69</td>\n",
       "      <td>54</td>\n",
       "      <td>15</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th></th>\n",
       "      <td>103</td>\n",
       "      <td>97</td>\n",
       "      <td>6</td>\n",
       "      <td>70</td>\n",
       "      <td>44</td>\n",
       "      <td>26</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th></th>\n",
       "      <td>104</td>\n",
       "      <td>91</td>\n",
       "      <td>13</td>\n",
       "      <td>71</td>\n",
       "      <td>37</td>\n",
       "      <td>34</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th></th>\n",
       "      <td>105</td>\n",
       "      <td>86</td>\n",
       "      <td>19</td>\n",
       "      <td>72</td>\n",
       "      <td>35</td>\n",
       "      <td>37</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th></th>\n",
       "      <td>106</td>\n",
       "      <td>83</td>\n",
       "      <td>23</td>\n",
       "      <td>73</td>\n",
       "      <td>32</td>\n",
       "      <td>41</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th></th>\n",
       "      <td>107</td>\n",
       "      <td>76</td>\n",
       "      <td>31</td>\n",
       "      <td>74</td>\n",
       "      <td>31</td>\n",
       "      <td>43</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th></th>\n",
       "      <td>108</td>\n",
       "      <td>73</td>\n",
       "      <td>35</td>\n",
       "      <td>75</td>\n",
       "      <td>24</td>\n",
       "      <td>51</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th></th>\n",
       "      <td>109</td>\n",
       "      <td>68</td>\n",
       "      <td>41</td>\n",
       "      <td>76</td>\n",
       "      <td>23</td>\n",
       "      <td>53</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th></th>\n",
       "      <td>110</td>\n",
       "      <td>61</td>\n",
       "      <td>49</td>\n",
       "      <td>77</td>\n",
       "      <td>21</td>\n",
       "      <td>56</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "  kms  km rides  kms gap  miles  miles rides  miles gap\n",
       "  100       107       -7     67           74         -7\n",
       "  101       105       -4     68           67          1\n",
       "  102        99        3     69           54         15\n",
       "  103        97        6     70           44         26\n",
       "  104        91       13     71           37         34\n",
       "  105        86       19     72           35         37\n",
       "  106        83       23     73           32         41\n",
       "  107        76       31     74           31         43\n",
       "  108        73       35     75           24         51\n",
       "  109        68       41     76           23         53\n",
       "  110        61       49     77           21         56"
      ]
     },
     "execution_count": 98,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "Ed_gaps(rides)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "I need three 102-km rides to improve from 101 to 102; In miles, I need one 68-mile ride to improve from 67 to 68.\n",
    "\n",
    "Here are some properties of Eddington numbers:\n",
    "- Your Eddington number is monotonic: it can never decrease over time. \n",
    "- To improve from an Eddington number of *n* to *n* + 1 can take as few as 1 ride, or as many as *n* + 1 rides.\n",
    "  + *Suppose you have done 9 rides, each of exactly 10 miles. Your Eddington number is 9.*\n",
    "  + *You would need 1 ride of 10 miles to improve from a number of 9 to 10.*\n",
    "  + *You would then need 11 rides of 11 miles to improve from a number 10 to 11.*\n",
    "- Your metric Eddington number will always be greater than or equal to your imperial Eddington number.\n",
    "- Your metric Eddington number will never be more than 1.609344 times your  imperial Eddington number.\n",
    "- Of two riders, it is possible that one has a higher metric number and the other a higher imperial number.\n",
    "\n",
    "*Note:* the definition of Eddington Number seems precise, but what exactly does ***day*** mean? The New Oxford dictionary has three senses:\n",
    "\n",
    "1. *a period of 24 hours;*\n",
    "2. *a unit of time, reckoned from one midnight to the next;*\n",
    "3. *the part of a day when it is light.* \n",
    "\n",
    "I originally assumed sense 2, but I wanted to accept sense 1 for what [bikepackers](https://bikepacking.com/) call a [sub-24-hour overnight](https://oneofsevenproject.com/s24o-bikepacking-guide/) (S24O): a ride to a camping site in the afternoon, pitching a tent for the night, and returning back home the next morning.  And then COVID struck, the camping sites closed, so why not allow an S24O where I sleep in my own home? I realize Eddington had a lot more hardships than we have (World War I, the 1918 pandemic, and World War II, for example), but I hope he would approve of this modest accomodation on my part."
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# Hill-Index: Speed versus Grade on Short Climbs\n",
    "\n",
    "The Eddington number reminds me of the [**h-index**](https://en.wikipedia.org/wiki/H-index) metric for scientific publications. I invented another metric:\n",
    "\n",
    "> *Your **hill-index** is the maximum integer **h** where you can regularly climb an **h** percent grade at **h** miles per hour.*\n",
    "\n",
    "I'll plot grade versus speed for segments (not rides) with two best-fit curves: a blue quadratic and an orange cubic. I'll also superimpose a red dotted line where grade = speed."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 99,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 864x432 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "show('pct', 'mph', segments[segments.pct > 2], \n",
    "     'Miles per hour versus segment grade in percent')\n",
    "plt.plot((2, 6, 7), (2, 6, 7), 'ro:');"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Both  best-fit curves are above the red circle at 6% and below the red circle for 7%, so  **my hill-index is 6**. We also see that I can cruise at 14 mph on a 2% grade, but only about 7 mph at 6% grade, and around 5.5 mph on 8% grades."
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    " # Speed versus Grade on Long Rides\n",
    "\n",
    "The plot above tell me how fast I should expect to climb a particular hill, but what about average time on longer rides? Here's a plot of my speed versus steepness (measured in feet climbed per mile rather than in percent)."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 100,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 864x432 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "show('fpm', 'mph', rides, 'Speed (miles per hour) versus Ride Grade (feet per mile)')"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "So, I average a little under 14 mph when the overall route is fairly flat, with a lot of variability, depending more on my level of effort (and maybe the wind) than on the grade of the road. But when the grade is steeper than 50 ft/mile, my speed falls off quickly: down to 12mph at 80 ft/mile;  11 mph at 100 ft/mile; and around 10 mph at 120 ft/mile. Note that 120 ft/mile is only 2.3% grade, but if you figure a typical route is 1/3 up, 1/3 down, and 1/3 flat, then that's 7% average grade on the up part.\n",
    "\n",
    "I can use this to predict the time of a ride.  For example, if I'm in  La Honda and want to get to Pescadero, which  way is faster: the [coast route](https://www.google.com/maps/dir/La+Honda,+California/Pescadero,+California/@37.2905834,-122.3896683,12z/data=!4m19!4m18!1m10!1m1!1s0x808faed4dc6265bd:0x51a109d3306a7219!2m2!1d-122.274227!2d37.3190255!3m4!1m2!1d-122.4039496!2d37.3116594!3s0x808f062b7d7585e7:0x942480c22f110b74!1m5!1m1!1s0x808f00b4b613c4c1:0x43c609077878b77!2m2!1d-122.3830152!2d37.2551636!3e1) (15.7 miles, 361 ft climb), or the  [creek route](https://www.google.com/maps/dir/La+Honda,+California/Pescadero,+California/@37.2905834,-122.3896683,12z/data=!4m19!4m18!1m10!1m1!1s0x808faed4dc6265bd:0x51a109d3306a7219!2m2!1d-122.274227!2d37.3190255!3m4!1m2!1d-122.3658887!2d37.2538867!3s0x808f00acf265bd43:0xb7e2a0c9ee355c3a!1m5!1m1!1s0x808f00b4b613c4c1:0x43c609077878b77!2m2!1d-122.3830152!2d37.2551636!3e1) (13.5 miles, 853 ft climb)? We can estimate:"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 101,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "'Coast: 70 min, Creek: 64 min.'"
      ]
     },
     "execution_count": 101,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "f'Coast: {estimate(15.7, 361)} min, Creek: {estimate(13.5, 853)} min.'"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "This predicts the shorter but steeper creek route would be about 6 minutes faster (whereas Google Maps predicts the creek route would be 80 minutes, 2 more than the coast route—I guess Google lacks confidence in my climbing ability).  This is all good to know, but other factors (like the scenery and whether I want to stop at the San Gregorio store) are probably more important in making the choice."
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# VAM\n",
    "\n",
    "Climbing speed measured by vertical ascent in meters per hour is known as [VAM](https://en.wikipedia.org/wiki/VAM_%28bicycling%29), which stands for *velocità ascensionale media* (for native Campagnolo speakers) or *vertical ascent in meters* (for SRAM) or 平均上昇率 (for Shimano), and sometimes by Vm/h. The theory is that for fairly steep climbs, most of your power is going into lifting against gravity, so your VAM should be about constant no matter what the grade. (For flatish climbs power is spent on wind and rolling resistance, and for the very steepest of climbs, in my experience,  power goes largely to cursing *sotto voce*, as they say in Italian.) \n",
    "\n",
    "Here's a plot of my VAM versus grade over short segments:"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 102,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 864x432 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "show('pct', 'vam', segments, 'VAM (vertical meters per hour) versus segment grade in percent')"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Champion cyclists can do over 1800 meters/hour over a 10 km climb, and can sustain [1400 meters/hour for 7 hours](https://www.strava.com/activities/4996833865).  My VAM numbers range mostly from 400 to 900 meters/hour, but I can sustain the higher numbers for only a couple of minutes:"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 103,
   "metadata": {},
   "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>title</th>\n",
       "      <th>hours</th>\n",
       "      <th>miles</th>\n",
       "      <th>feet</th>\n",
       "      <th>mph</th>\n",
       "      <th>vam</th>\n",
       "      <th>fpm</th>\n",
       "      <th>pct</th>\n",
       "      <th>kms</th>\n",
       "      <th>km_up</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>14</th>\n",
       "      <td>Camaritas climb</td>\n",
       "      <td>0.01</td>\n",
       "      <td>0.10</td>\n",
       "      <td>48</td>\n",
       "      <td>10.00</td>\n",
       "      <td>1463.0</td>\n",
       "      <td>480.0</td>\n",
       "      <td>9.09</td>\n",
       "      <td>0.16</td>\n",
       "      <td>0.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>71</th>\n",
       "      <td>Paloma Climb</td>\n",
       "      <td>0.02</td>\n",
       "      <td>0.14</td>\n",
       "      <td>82</td>\n",
       "      <td>7.00</td>\n",
       "      <td>1250.0</td>\n",
       "      <td>586.0</td>\n",
       "      <td>11.09</td>\n",
       "      <td>0.23</td>\n",
       "      <td>0.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>55</th>\n",
       "      <td>Klamath Dr.</td>\n",
       "      <td>0.02</td>\n",
       "      <td>0.12</td>\n",
       "      <td>77</td>\n",
       "      <td>6.00</td>\n",
       "      <td>1173.0</td>\n",
       "      <td>642.0</td>\n",
       "      <td>12.15</td>\n",
       "      <td>0.19</td>\n",
       "      <td>0.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>28</th>\n",
       "      <td>Entrance Way Hill Repeats</td>\n",
       "      <td>0.02</td>\n",
       "      <td>0.10</td>\n",
       "      <td>76</td>\n",
       "      <td>5.00</td>\n",
       "      <td>1158.0</td>\n",
       "      <td>760.0</td>\n",
       "      <td>14.39</td>\n",
       "      <td>0.16</td>\n",
       "      <td>0.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>25</th>\n",
       "      <td>Davenport Kicker</td>\n",
       "      <td>0.02</td>\n",
       "      <td>0.24</td>\n",
       "      <td>74</td>\n",
       "      <td>12.00</td>\n",
       "      <td>1128.0</td>\n",
       "      <td>308.0</td>\n",
       "      <td>5.84</td>\n",
       "      <td>0.39</td>\n",
       "      <td>0.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>121</th>\n",
       "      <td>Valparaiso steep</td>\n",
       "      <td>0.04</td>\n",
       "      <td>0.18</td>\n",
       "      <td>145</td>\n",
       "      <td>4.50</td>\n",
       "      <td>1105.0</td>\n",
       "      <td>806.0</td>\n",
       "      <td>15.26</td>\n",
       "      <td>0.29</td>\n",
       "      <td>0.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>42</th>\n",
       "      <td>Invernes to Firecrest Climb</td>\n",
       "      <td>0.04</td>\n",
       "      <td>0.28</td>\n",
       "      <td>143</td>\n",
       "      <td>7.00</td>\n",
       "      <td>1090.0</td>\n",
       "      <td>511.0</td>\n",
       "      <td>9.67</td>\n",
       "      <td>0.45</td>\n",
       "      <td>0.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>54</th>\n",
       "      <td>Kings Mountain final sprint</td>\n",
       "      <td>0.04</td>\n",
       "      <td>0.31</td>\n",
       "      <td>135</td>\n",
       "      <td>7.75</td>\n",
       "      <td>1029.0</td>\n",
       "      <td>435.0</td>\n",
       "      <td>8.25</td>\n",
       "      <td>0.50</td>\n",
       "      <td>0.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>57</th>\n",
       "      <td>Limantour Spit</td>\n",
       "      <td>0.09</td>\n",
       "      <td>0.47</td>\n",
       "      <td>303</td>\n",
       "      <td>5.22</td>\n",
       "      <td>1026.0</td>\n",
       "      <td>645.0</td>\n",
       "      <td>12.21</td>\n",
       "      <td>0.76</td>\n",
       "      <td>0.1</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>115</th>\n",
       "      <td>Tunitas flattens</td>\n",
       "      <td>0.05</td>\n",
       "      <td>0.42</td>\n",
       "      <td>166</td>\n",
       "      <td>8.40</td>\n",
       "      <td>1012.0</td>\n",
       "      <td>395.0</td>\n",
       "      <td>7.49</td>\n",
       "      <td>0.68</td>\n",
       "      <td>0.1</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>116</th>\n",
       "      <td>Tunitas flattens</td>\n",
       "      <td>0.05</td>\n",
       "      <td>0.42</td>\n",
       "      <td>166</td>\n",
       "      <td>8.40</td>\n",
       "      <td>1012.0</td>\n",
       "      <td>395.0</td>\n",
       "      <td>7.49</td>\n",
       "      <td>0.68</td>\n",
       "      <td>0.1</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>21</th>\n",
       "      <td>Cemetery Sprint</td>\n",
       "      <td>0.01</td>\n",
       "      <td>0.08</td>\n",
       "      <td>33</td>\n",
       "      <td>8.00</td>\n",
       "      <td>1006.0</td>\n",
       "      <td>412.0</td>\n",
       "      <td>7.81</td>\n",
       "      <td>0.13</td>\n",
       "      <td>0.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>93</th>\n",
       "      <td>Skyline Bump at OLH</td>\n",
       "      <td>0.02</td>\n",
       "      <td>0.21</td>\n",
       "      <td>63</td>\n",
       "      <td>10.50</td>\n",
       "      <td>960.0</td>\n",
       "      <td>300.0</td>\n",
       "      <td>5.68</td>\n",
       "      <td>0.34</td>\n",
       "      <td>0.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>56</th>\n",
       "      <td>Laning Bump</td>\n",
       "      <td>0.03</td>\n",
       "      <td>0.24</td>\n",
       "      <td>94</td>\n",
       "      <td>8.00</td>\n",
       "      <td>955.0</td>\n",
       "      <td>392.0</td>\n",
       "      <td>7.42</td>\n",
       "      <td>0.39</td>\n",
       "      <td>0.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>29</th>\n",
       "      <td>Faught Turn</td>\n",
       "      <td>0.02</td>\n",
       "      <td>0.22</td>\n",
       "      <td>60</td>\n",
       "      <td>11.00</td>\n",
       "      <td>914.0</td>\n",
       "      <td>273.0</td>\n",
       "      <td>5.17</td>\n",
       "      <td>0.35</td>\n",
       "      <td>0.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>131</th>\n",
       "      <td>Westridge 3min</td>\n",
       "      <td>0.08</td>\n",
       "      <td>0.37</td>\n",
       "      <td>240</td>\n",
       "      <td>4.62</td>\n",
       "      <td>914.0</td>\n",
       "      <td>649.0</td>\n",
       "      <td>12.29</td>\n",
       "      <td>0.60</td>\n",
       "      <td>0.1</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>122</th>\n",
       "      <td>Valparaiso steep</td>\n",
       "      <td>0.05</td>\n",
       "      <td>0.18</td>\n",
       "      <td>145</td>\n",
       "      <td>3.60</td>\n",
       "      <td>884.0</td>\n",
       "      <td>806.0</td>\n",
       "      <td>15.26</td>\n",
       "      <td>0.29</td>\n",
       "      <td>0.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>92</th>\n",
       "      <td>Sharon Park steep part</td>\n",
       "      <td>0.03</td>\n",
       "      <td>0.21</td>\n",
       "      <td>86</td>\n",
       "      <td>7.00</td>\n",
       "      <td>874.0</td>\n",
       "      <td>410.0</td>\n",
       "      <td>7.76</td>\n",
       "      <td>0.34</td>\n",
       "      <td>0.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>69</th>\n",
       "      <td>Old La Honda Mile 1</td>\n",
       "      <td>0.13</td>\n",
       "      <td>0.99</td>\n",
       "      <td>370</td>\n",
       "      <td>7.62</td>\n",
       "      <td>868.0</td>\n",
       "      <td>374.0</td>\n",
       "      <td>7.08</td>\n",
       "      <td>1.59</td>\n",
       "      <td>0.1</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>43</th>\n",
       "      <td>Joaquin</td>\n",
       "      <td>0.09</td>\n",
       "      <td>0.33</td>\n",
       "      <td>254</td>\n",
       "      <td>3.67</td>\n",
       "      <td>860.0</td>\n",
       "      <td>770.0</td>\n",
       "      <td>14.58</td>\n",
       "      <td>0.53</td>\n",
       "      <td>0.1</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "                           title  hours  miles  feet    mph     vam    fpm  \\\n",
       "14               Camaritas climb   0.01   0.10    48  10.00  1463.0  480.0   \n",
       "71                  Paloma Climb   0.02   0.14    82   7.00  1250.0  586.0   \n",
       "55                   Klamath Dr.   0.02   0.12    77   6.00  1173.0  642.0   \n",
       "28     Entrance Way Hill Repeats   0.02   0.10    76   5.00  1158.0  760.0   \n",
       "25              Davenport Kicker   0.02   0.24    74  12.00  1128.0  308.0   \n",
       "121             Valparaiso steep   0.04   0.18   145   4.50  1105.0  806.0   \n",
       "42   Invernes to Firecrest Climb   0.04   0.28   143   7.00  1090.0  511.0   \n",
       "54   Kings Mountain final sprint   0.04   0.31   135   7.75  1029.0  435.0   \n",
       "57                Limantour Spit   0.09   0.47   303   5.22  1026.0  645.0   \n",
       "115             Tunitas flattens   0.05   0.42   166   8.40  1012.0  395.0   \n",
       "116             Tunitas flattens   0.05   0.42   166   8.40  1012.0  395.0   \n",
       "21               Cemetery Sprint   0.01   0.08    33   8.00  1006.0  412.0   \n",
       "93           Skyline Bump at OLH   0.02   0.21    63  10.50   960.0  300.0   \n",
       "56                   Laning Bump   0.03   0.24    94   8.00   955.0  392.0   \n",
       "29                   Faught Turn   0.02   0.22    60  11.00   914.0  273.0   \n",
       "131               Westridge 3min   0.08   0.37   240   4.62   914.0  649.0   \n",
       "122             Valparaiso steep   0.05   0.18   145   3.60   884.0  806.0   \n",
       "92        Sharon Park steep part   0.03   0.21    86   7.00   874.0  410.0   \n",
       "69           Old La Honda Mile 1   0.13   0.99   370   7.62   868.0  374.0   \n",
       "43                       Joaquin   0.09   0.33   254   3.67   860.0  770.0   \n",
       "\n",
       "       pct   kms  km_up  \n",
       "14    9.09  0.16    0.0  \n",
       "71   11.09  0.23    0.0  \n",
       "55   12.15  0.19    0.0  \n",
       "28   14.39  0.16    0.0  \n",
       "25    5.84  0.39    0.0  \n",
       "121  15.26  0.29    0.0  \n",
       "42    9.67  0.45    0.0  \n",
       "54    8.25  0.50    0.0  \n",
       "57   12.21  0.76    0.1  \n",
       "115   7.49  0.68    0.1  \n",
       "116   7.49  0.68    0.1  \n",
       "21    7.81  0.13    0.0  \n",
       "93    5.68  0.34    0.0  \n",
       "56    7.42  0.39    0.0  \n",
       "29    5.17  0.35    0.0  \n",
       "131  12.29  0.60    0.1  \n",
       "122  15.26  0.29    0.0  \n",
       "92    7.76  0.34    0.0  \n",
       "69    7.08  1.59    0.1  \n",
       "43   14.58  0.53    0.1  "
      ]
     },
     "execution_count": 103,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "top(segments, 'vam')"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "On segments that are at least a kilometer long my VAM tops out at about 800 meters/hour:"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 104,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
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       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>title</th>\n",
       "      <th>hours</th>\n",
       "      <th>miles</th>\n",
       "      <th>feet</th>\n",
       "      <th>mph</th>\n",
       "      <th>vam</th>\n",
       "      <th>fpm</th>\n",
       "      <th>pct</th>\n",
       "      <th>kms</th>\n",
       "      <th>km_up</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>69</th>\n",
       "      <td>Old La Honda Mile 1</td>\n",
       "      <td>0.13</td>\n",
       "      <td>0.99</td>\n",
       "      <td>370</td>\n",
       "      <td>7.62</td>\n",
       "      <td>868.0</td>\n",
       "      <td>374.0</td>\n",
       "      <td>7.08</td>\n",
       "      <td>1.59</td>\n",
       "      <td>0.1</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>129</th>\n",
       "      <td>Westridge</td>\n",
       "      <td>0.14</td>\n",
       "      <td>0.68</td>\n",
       "      <td>385</td>\n",
       "      <td>4.86</td>\n",
       "      <td>838.0</td>\n",
       "      <td>566.0</td>\n",
       "      <td>10.72</td>\n",
       "      <td>1.09</td>\n",
       "      <td>0.1</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>67</th>\n",
       "      <td>Old La Honda (Bridge to Stop)</td>\n",
       "      <td>0.48</td>\n",
       "      <td>3.33</td>\n",
       "      <td>1255</td>\n",
       "      <td>6.94</td>\n",
       "      <td>797.0</td>\n",
       "      <td>377.0</td>\n",
       "      <td>7.14</td>\n",
       "      <td>5.36</td>\n",
       "      <td>0.4</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>68</th>\n",
       "      <td>Old La Honda (Bridge to Stop)</td>\n",
       "      <td>0.51</td>\n",
       "      <td>3.33</td>\n",
       "      <td>1255</td>\n",
       "      <td>6.53</td>\n",
       "      <td>750.0</td>\n",
       "      <td>377.0</td>\n",
       "      <td>7.14</td>\n",
       "      <td>5.36</td>\n",
       "      <td>0.4</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>130</th>\n",
       "      <td>Westridge</td>\n",
       "      <td>0.16</td>\n",
       "      <td>0.68</td>\n",
       "      <td>385</td>\n",
       "      <td>4.25</td>\n",
       "      <td>733.0</td>\n",
       "      <td>566.0</td>\n",
       "      <td>10.72</td>\n",
       "      <td>1.09</td>\n",
       "      <td>0.1</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>119</th>\n",
       "      <td>Tunitas steep</td>\n",
       "      <td>0.25</td>\n",
       "      <td>1.20</td>\n",
       "      <td>599</td>\n",
       "      <td>4.80</td>\n",
       "      <td>730.0</td>\n",
       "      <td>499.0</td>\n",
       "      <td>9.45</td>\n",
       "      <td>1.93</td>\n",
       "      <td>0.2</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>70</th>\n",
       "      <td>Old La Honda Mile 1</td>\n",
       "      <td>0.16</td>\n",
       "      <td>0.99</td>\n",
       "      <td>370</td>\n",
       "      <td>6.19</td>\n",
       "      <td>705.0</td>\n",
       "      <td>374.0</td>\n",
       "      <td>7.08</td>\n",
       "      <td>1.59</td>\n",
       "      <td>0.1</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>139</th>\n",
       "      <td>Woodside Climb</td>\n",
       "      <td>0.13</td>\n",
       "      <td>1.71</td>\n",
       "      <td>295</td>\n",
       "      <td>13.15</td>\n",
       "      <td>692.0</td>\n",
       "      <td>173.0</td>\n",
       "      <td>3.27</td>\n",
       "      <td>2.75</td>\n",
       "      <td>0.1</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>40</th>\n",
       "      <td>Huddart</td>\n",
       "      <td>0.17</td>\n",
       "      <td>0.92</td>\n",
       "      <td>385</td>\n",
       "      <td>5.41</td>\n",
       "      <td>690.0</td>\n",
       "      <td>418.0</td>\n",
       "      <td>7.93</td>\n",
       "      <td>1.48</td>\n",
       "      <td>0.1</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>111</th>\n",
       "      <td>Top of Groton Rd heading west</td>\n",
       "      <td>0.13</td>\n",
       "      <td>0.92</td>\n",
       "      <td>291</td>\n",
       "      <td>7.08</td>\n",
       "      <td>682.0</td>\n",
       "      <td>316.0</td>\n",
       "      <td>5.99</td>\n",
       "      <td>1.48</td>\n",
       "      <td>0.1</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>125</th>\n",
       "      <td>Watts (Sonoma)</td>\n",
       "      <td>0.14</td>\n",
       "      <td>1.20</td>\n",
       "      <td>313</td>\n",
       "      <td>8.57</td>\n",
       "      <td>681.0</td>\n",
       "      <td>261.0</td>\n",
       "      <td>4.94</td>\n",
       "      <td>1.93</td>\n",
       "      <td>0.1</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>120</th>\n",
       "      <td>Tunitas steep</td>\n",
       "      <td>0.27</td>\n",
       "      <td>1.20</td>\n",
       "      <td>599</td>\n",
       "      <td>4.44</td>\n",
       "      <td>676.0</td>\n",
       "      <td>499.0</td>\n",
       "      <td>9.45</td>\n",
       "      <td>1.93</td>\n",
       "      <td>0.2</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>19</th>\n",
       "      <td>Canon to No Cycling</td>\n",
       "      <td>0.09</td>\n",
       "      <td>0.75</td>\n",
       "      <td>198</td>\n",
       "      <td>8.33</td>\n",
       "      <td>671.0</td>\n",
       "      <td>264.0</td>\n",
       "      <td>5.00</td>\n",
       "      <td>1.21</td>\n",
       "      <td>0.1</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>20</th>\n",
       "      <td>Canon to No Cycling</td>\n",
       "      <td>0.09</td>\n",
       "      <td>0.75</td>\n",
       "      <td>198</td>\n",
       "      <td>8.33</td>\n",
       "      <td>671.0</td>\n",
       "      <td>264.0</td>\n",
       "      <td>5.00</td>\n",
       "      <td>1.21</td>\n",
       "      <td>0.1</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>23</th>\n",
       "      <td>Coe Second Switchback to flat</td>\n",
       "      <td>0.22</td>\n",
       "      <td>1.00</td>\n",
       "      <td>483</td>\n",
       "      <td>4.55</td>\n",
       "      <td>669.0</td>\n",
       "      <td>483.0</td>\n",
       "      <td>9.15</td>\n",
       "      <td>1.61</td>\n",
       "      <td>0.1</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>60</th>\n",
       "      <td>Lower Redwood Gulch</td>\n",
       "      <td>0.22</td>\n",
       "      <td>1.03</td>\n",
       "      <td>474</td>\n",
       "      <td>4.68</td>\n",
       "      <td>657.0</td>\n",
       "      <td>460.0</td>\n",
       "      <td>8.72</td>\n",
       "      <td>1.66</td>\n",
       "      <td>0.1</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>59</th>\n",
       "      <td>Lobitas Creek</td>\n",
       "      <td>0.20</td>\n",
       "      <td>0.96</td>\n",
       "      <td>430</td>\n",
       "      <td>4.80</td>\n",
       "      <td>655.0</td>\n",
       "      <td>448.0</td>\n",
       "      <td>8.48</td>\n",
       "      <td>1.54</td>\n",
       "      <td>0.1</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>126</th>\n",
       "      <td>West Alpine switchback</td>\n",
       "      <td>0.15</td>\n",
       "      <td>0.78</td>\n",
       "      <td>322</td>\n",
       "      <td>5.20</td>\n",
       "      <td>654.0</td>\n",
       "      <td>413.0</td>\n",
       "      <td>7.82</td>\n",
       "      <td>1.26</td>\n",
       "      <td>0.1</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>45</th>\n",
       "      <td>Kaboom Portola Rd</td>\n",
       "      <td>0.05</td>\n",
       "      <td>0.67</td>\n",
       "      <td>102</td>\n",
       "      <td>13.40</td>\n",
       "      <td>622.0</td>\n",
       "      <td>152.0</td>\n",
       "      <td>2.88</td>\n",
       "      <td>1.08</td>\n",
       "      <td>0.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>41</th>\n",
       "      <td>Huddart</td>\n",
       "      <td>0.19</td>\n",
       "      <td>0.92</td>\n",
       "      <td>385</td>\n",
       "      <td>4.84</td>\n",
       "      <td>618.0</td>\n",
       "      <td>418.0</td>\n",
       "      <td>7.93</td>\n",
       "      <td>1.48</td>\n",
       "      <td>0.1</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "                             title  hours  miles  feet    mph    vam    fpm  \\\n",
       "69             Old La Honda Mile 1   0.13   0.99   370   7.62  868.0  374.0   \n",
       "129                      Westridge   0.14   0.68   385   4.86  838.0  566.0   \n",
       "67   Old La Honda (Bridge to Stop)   0.48   3.33  1255   6.94  797.0  377.0   \n",
       "68   Old La Honda (Bridge to Stop)   0.51   3.33  1255   6.53  750.0  377.0   \n",
       "130                      Westridge   0.16   0.68   385   4.25  733.0  566.0   \n",
       "119                  Tunitas steep   0.25   1.20   599   4.80  730.0  499.0   \n",
       "70             Old La Honda Mile 1   0.16   0.99   370   6.19  705.0  374.0   \n",
       "139                 Woodside Climb   0.13   1.71   295  13.15  692.0  173.0   \n",
       "40                         Huddart   0.17   0.92   385   5.41  690.0  418.0   \n",
       "111  Top of Groton Rd heading west   0.13   0.92   291   7.08  682.0  316.0   \n",
       "125                 Watts (Sonoma)   0.14   1.20   313   8.57  681.0  261.0   \n",
       "120                  Tunitas steep   0.27   1.20   599   4.44  676.0  499.0   \n",
       "19             Canon to No Cycling   0.09   0.75   198   8.33  671.0  264.0   \n",
       "20             Canon to No Cycling   0.09   0.75   198   8.33  671.0  264.0   \n",
       "23   Coe Second Switchback to flat   0.22   1.00   483   4.55  669.0  483.0   \n",
       "60             Lower Redwood Gulch   0.22   1.03   474   4.68  657.0  460.0   \n",
       "59                   Lobitas Creek   0.20   0.96   430   4.80  655.0  448.0   \n",
       "126         West Alpine switchback   0.15   0.78   322   5.20  654.0  413.0   \n",
       "45               Kaboom Portola Rd   0.05   0.67   102  13.40  622.0  152.0   \n",
       "41                         Huddart   0.19   0.92   385   4.84  618.0  418.0   \n",
       "\n",
       "       pct   kms  km_up  \n",
       "69    7.08  1.59    0.1  \n",
       "129  10.72  1.09    0.1  \n",
       "67    7.14  5.36    0.4  \n",
       "68    7.14  5.36    0.4  \n",
       "130  10.72  1.09    0.1  \n",
       "119   9.45  1.93    0.2  \n",
       "70    7.08  1.59    0.1  \n",
       "139   3.27  2.75    0.1  \n",
       "40    7.93  1.48    0.1  \n",
       "111   5.99  1.48    0.1  \n",
       "125   4.94  1.93    0.1  \n",
       "120   9.45  1.93    0.2  \n",
       "19    5.00  1.21    0.1  \n",
       "20    5.00  1.21    0.1  \n",
       "23    9.15  1.61    0.1  \n",
       "60    8.72  1.66    0.1  \n",
       "59    8.48  1.54    0.1  \n",
       "126   7.82  1.26    0.1  \n",
       "45    2.88  1.08    0.0  \n",
       "41    7.93  1.48    0.1  "
      ]
     },
     "execution_count": 104,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "top(segments[segments.kms >= 1], 'vam')"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "I can also look at VAM numbers for complete rides. I would expect the ride VAM to be half the segment VAM (or less) since most of my rides are circuits where I return to the start, and thus no more than half the ride is climbing. Sure enough, the best I can do is about 400 meters/hour:"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 105,
   "metadata": {},
   "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>date</th>\n",
       "      <th>year</th>\n",
       "      <th>title</th>\n",
       "      <th>hours</th>\n",
       "      <th>miles</th>\n",
       "      <th>feet</th>\n",
       "      <th>mph</th>\n",
       "      <th>vam</th>\n",
       "      <th>fpm</th>\n",
       "      <th>pct</th>\n",
       "      <th>kms</th>\n",
       "      <th>km_up</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th></th>\n",
       "      <td>Sun, 11/29</td>\n",
       "      <td>2015</td>\n",
       "      <td>Mt. Hamilton</td>\n",
       "      <td>3.68</td>\n",
       "      <td>37.00</td>\n",
       "      <td>4902</td>\n",
       "      <td>10.05</td>\n",
       "      <td>406.0</td>\n",
       "      <td>132.0</td>\n",
       "      <td>2.51</td>\n",
       "      <td>59.53</td>\n",
       "      <td>1.5</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th></th>\n",
       "      <td>Fri, 4/2</td>\n",
       "      <td>2021</td>\n",
       "      <td>Everesting 5: climb 2×(OLH + WOLH)</td>\n",
       "      <td>3.27</td>\n",
       "      <td>31.48</td>\n",
       "      <td>4344</td>\n",
       "      <td>9.63</td>\n",
       "      <td>405.0</td>\n",
       "      <td>138.0</td>\n",
       "      <td>2.61</td>\n",
       "      <td>50.65</td>\n",
       "      <td>1.3</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th></th>\n",
       "      <td>Tue, 3/30</td>\n",
       "      <td>2021</td>\n",
       "      <td>Everesting 2: Kings + WOLH + OLH</td>\n",
       "      <td>3.34</td>\n",
       "      <td>35.99</td>\n",
       "      <td>4377</td>\n",
       "      <td>10.78</td>\n",
       "      <td>399.0</td>\n",
       "      <td>122.0</td>\n",
       "      <td>2.30</td>\n",
       "      <td>57.91</td>\n",
       "      <td>1.3</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th></th>\n",
       "      <td>Mon, 3/29</td>\n",
       "      <td>2021</td>\n",
       "      <td>Everesting 1: Mt Diablo</td>\n",
       "      <td>2.60</td>\n",
       "      <td>22.22</td>\n",
       "      <td>3406</td>\n",
       "      <td>8.55</td>\n",
       "      <td>399.0</td>\n",
       "      <td>153.0</td>\n",
       "      <td>2.90</td>\n",
       "      <td>35.75</td>\n",
       "      <td>1.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th></th>\n",
       "      <td>Sat, 11/25</td>\n",
       "      <td>2017</td>\n",
       "      <td>Mt. Hamilton</td>\n",
       "      <td>3.69</td>\n",
       "      <td>36.65</td>\n",
       "      <td>4806</td>\n",
       "      <td>9.93</td>\n",
       "      <td>397.0</td>\n",
       "      <td>131.0</td>\n",
       "      <td>2.48</td>\n",
       "      <td>58.97</td>\n",
       "      <td>1.5</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th></th>\n",
       "      <td>Sun, 12/1</td>\n",
       "      <td>2013</td>\n",
       "      <td>Mt. Hamilton</td>\n",
       "      <td>3.78</td>\n",
       "      <td>37.56</td>\n",
       "      <td>4921</td>\n",
       "      <td>9.94</td>\n",
       "      <td>397.0</td>\n",
       "      <td>131.0</td>\n",
       "      <td>2.48</td>\n",
       "      <td>60.43</td>\n",
       "      <td>1.5</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th></th>\n",
       "      <td>Fri, 10/30</td>\n",
       "      <td>2015</td>\n",
       "      <td>OLH / West Alpine</td>\n",
       "      <td>3.48</td>\n",
       "      <td>39.51</td>\n",
       "      <td>4505</td>\n",
       "      <td>11.35</td>\n",
       "      <td>395.0</td>\n",
       "      <td>114.0</td>\n",
       "      <td>2.16</td>\n",
       "      <td>63.57</td>\n",
       "      <td>1.4</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th></th>\n",
       "      <td>Sat, 4/26</td>\n",
       "      <td>2014</td>\n",
       "      <td>OLH / Tunitas Creek</td>\n",
       "      <td>5.26</td>\n",
       "      <td>58.69</td>\n",
       "      <td>6742</td>\n",
       "      <td>11.16</td>\n",
       "      <td>391.0</td>\n",
       "      <td>115.0</td>\n",
       "      <td>2.18</td>\n",
       "      <td>94.43</td>\n",
       "      <td>2.1</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th></th>\n",
       "      <td>Sat, 4/18</td>\n",
       "      <td>2015</td>\n",
       "      <td>Tunitas + Lobitos Creeks</td>\n",
       "      <td>5.24</td>\n",
       "      <td>61.27</td>\n",
       "      <td>6611</td>\n",
       "      <td>11.69</td>\n",
       "      <td>385.0</td>\n",
       "      <td>108.0</td>\n",
       "      <td>2.04</td>\n",
       "      <td>98.58</td>\n",
       "      <td>2.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th></th>\n",
       "      <td>Wed, 10/14</td>\n",
       "      <td>2015</td>\n",
       "      <td>Half Moon Bay</td>\n",
       "      <td>6.13</td>\n",
       "      <td>72.97</td>\n",
       "      <td>7644</td>\n",
       "      <td>11.90</td>\n",
       "      <td>380.0</td>\n",
       "      <td>105.0</td>\n",
       "      <td>1.98</td>\n",
       "      <td>117.41</td>\n",
       "      <td>2.3</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th></th>\n",
       "      <td>Sat, 7/25</td>\n",
       "      <td>2015</td>\n",
       "      <td>Palo Alto, California</td>\n",
       "      <td>4.04</td>\n",
       "      <td>43.62</td>\n",
       "      <td>4819</td>\n",
       "      <td>10.80</td>\n",
       "      <td>364.0</td>\n",
       "      <td>110.0</td>\n",
       "      <td>2.09</td>\n",
       "      <td>70.18</td>\n",
       "      <td>1.5</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th></th>\n",
       "      <td>Sun, 6/4</td>\n",
       "      <td>2017</td>\n",
       "      <td>Sequoia Challenge</td>\n",
       "      <td>6.29</td>\n",
       "      <td>66.52</td>\n",
       "      <td>7520</td>\n",
       "      <td>10.58</td>\n",
       "      <td>364.0</td>\n",
       "      <td>113.0</td>\n",
       "      <td>2.14</td>\n",
       "      <td>107.03</td>\n",
       "      <td>2.3</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th></th>\n",
       "      <td>Sat, 10/11</td>\n",
       "      <td>2014</td>\n",
       "      <td>OLH / Tunitas</td>\n",
       "      <td>5.09</td>\n",
       "      <td>58.29</td>\n",
       "      <td>6044</td>\n",
       "      <td>11.45</td>\n",
       "      <td>362.0</td>\n",
       "      <td>104.0</td>\n",
       "      <td>1.96</td>\n",
       "      <td>93.79</td>\n",
       "      <td>1.8</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th></th>\n",
       "      <td>Sat, 8/13</td>\n",
       "      <td>2016</td>\n",
       "      <td>Petaluma / Point Reyes</td>\n",
       "      <td>4.50</td>\n",
       "      <td>54.75</td>\n",
       "      <td>5286</td>\n",
       "      <td>12.17</td>\n",
       "      <td>358.0</td>\n",
       "      <td>97.0</td>\n",
       "      <td>1.83</td>\n",
       "      <td>88.09</td>\n",
       "      <td>1.6</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th></th>\n",
       "      <td>Fri, 8/28</td>\n",
       "      <td>2015</td>\n",
       "      <td>Pescadaro via OLH</td>\n",
       "      <td>5.31</td>\n",
       "      <td>66.01</td>\n",
       "      <td>6137</td>\n",
       "      <td>12.43</td>\n",
       "      <td>352.0</td>\n",
       "      <td>93.0</td>\n",
       "      <td>1.76</td>\n",
       "      <td>106.21</td>\n",
       "      <td>1.9</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th></th>\n",
       "      <td>Sun, 4/4</td>\n",
       "      <td>2021</td>\n",
       "      <td>Everesting 7: Mill Creek / Morrison Canyon</td>\n",
       "      <td>3.08</td>\n",
       "      <td>29.38</td>\n",
       "      <td>3517</td>\n",
       "      <td>9.54</td>\n",
       "      <td>348.0</td>\n",
       "      <td>120.0</td>\n",
       "      <td>2.27</td>\n",
       "      <td>47.27</td>\n",
       "      <td>1.1</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th></th>\n",
       "      <td>Wed, 6/18</td>\n",
       "      <td>2014</td>\n",
       "      <td>Sierra to the Sea Day 4</td>\n",
       "      <td>4.96</td>\n",
       "      <td>57.64</td>\n",
       "      <td>5561</td>\n",
       "      <td>11.62</td>\n",
       "      <td>342.0</td>\n",
       "      <td>96.0</td>\n",
       "      <td>1.83</td>\n",
       "      <td>92.74</td>\n",
       "      <td>1.7</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th></th>\n",
       "      <td>Sun, 6/3</td>\n",
       "      <td>2018</td>\n",
       "      <td>The Sequoia</td>\n",
       "      <td>5.97</td>\n",
       "      <td>64.92</td>\n",
       "      <td>6677</td>\n",
       "      <td>10.87</td>\n",
       "      <td>341.0</td>\n",
       "      <td>103.0</td>\n",
       "      <td>1.95</td>\n",
       "      <td>104.46</td>\n",
       "      <td>2.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th></th>\n",
       "      <td>Sat, 5/9</td>\n",
       "      <td>2015</td>\n",
       "      <td>OLH</td>\n",
       "      <td>2.50</td>\n",
       "      <td>32.33</td>\n",
       "      <td>2788</td>\n",
       "      <td>12.93</td>\n",
       "      <td>340.0</td>\n",
       "      <td>86.0</td>\n",
       "      <td>1.63</td>\n",
       "      <td>52.02</td>\n",
       "      <td>0.8</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th></th>\n",
       "      <td>Sat, 9/12</td>\n",
       "      <td>2015</td>\n",
       "      <td>Morning Ride</td>\n",
       "      <td>3.10</td>\n",
       "      <td>38.20</td>\n",
       "      <td>3342</td>\n",
       "      <td>12.32</td>\n",
       "      <td>329.0</td>\n",
       "      <td>87.0</td>\n",
       "      <td>1.66</td>\n",
       "      <td>61.46</td>\n",
       "      <td>1.0</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "        date  year                                       title  hours  miles  \\\n",
       "  Sun, 11/29  2015                                Mt. Hamilton   3.68  37.00   \n",
       "    Fri, 4/2  2021          Everesting 5: climb 2×(OLH + WOLH)   3.27  31.48   \n",
       "   Tue, 3/30  2021            Everesting 2: Kings + WOLH + OLH   3.34  35.99   \n",
       "   Mon, 3/29  2021                     Everesting 1: Mt Diablo   2.60  22.22   \n",
       "  Sat, 11/25  2017                                Mt. Hamilton   3.69  36.65   \n",
       "   Sun, 12/1  2013                                Mt. Hamilton   3.78  37.56   \n",
       "  Fri, 10/30  2015                           OLH / West Alpine   3.48  39.51   \n",
       "   Sat, 4/26  2014                         OLH / Tunitas Creek   5.26  58.69   \n",
       "   Sat, 4/18  2015                    Tunitas + Lobitos Creeks   5.24  61.27   \n",
       "  Wed, 10/14  2015                               Half Moon Bay   6.13  72.97   \n",
       "   Sat, 7/25  2015                       Palo Alto, California   4.04  43.62   \n",
       "    Sun, 6/4  2017                           Sequoia Challenge   6.29  66.52   \n",
       "  Sat, 10/11  2014                               OLH / Tunitas   5.09  58.29   \n",
       "   Sat, 8/13  2016                      Petaluma / Point Reyes   4.50  54.75   \n",
       "   Fri, 8/28  2015                           Pescadaro via OLH   5.31  66.01   \n",
       "    Sun, 4/4  2021  Everesting 7: Mill Creek / Morrison Canyon   3.08  29.38   \n",
       "   Wed, 6/18  2014                     Sierra to the Sea Day 4   4.96  57.64   \n",
       "    Sun, 6/3  2018                                 The Sequoia   5.97  64.92   \n",
       "    Sat, 5/9  2015                                         OLH   2.50  32.33   \n",
       "   Sat, 9/12  2015                                Morning Ride   3.10  38.20   \n",
       "\n",
       "  feet    mph    vam    fpm   pct     kms  km_up  \n",
       "  4902  10.05  406.0  132.0  2.51   59.53    1.5  \n",
       "  4344   9.63  405.0  138.0  2.61   50.65    1.3  \n",
       "  4377  10.78  399.0  122.0  2.30   57.91    1.3  \n",
       "  3406   8.55  399.0  153.0  2.90   35.75    1.0  \n",
       "  4806   9.93  397.0  131.0  2.48   58.97    1.5  \n",
       "  4921   9.94  397.0  131.0  2.48   60.43    1.5  \n",
       "  4505  11.35  395.0  114.0  2.16   63.57    1.4  \n",
       "  6742  11.16  391.0  115.0  2.18   94.43    2.1  \n",
       "  6611  11.69  385.0  108.0  2.04   98.58    2.0  \n",
       "  7644  11.90  380.0  105.0  1.98  117.41    2.3  \n",
       "  4819  10.80  364.0  110.0  2.09   70.18    1.5  \n",
       "  7520  10.58  364.0  113.0  2.14  107.03    2.3  \n",
       "  6044  11.45  362.0  104.0  1.96   93.79    1.8  \n",
       "  5286  12.17  358.0   97.0  1.83   88.09    1.6  \n",
       "  6137  12.43  352.0   93.0  1.76  106.21    1.9  \n",
       "  3517   9.54  348.0  120.0  2.27   47.27    1.1  \n",
       "  5561  11.62  342.0   96.0  1.83   92.74    1.7  \n",
       "  6677  10.87  341.0  103.0  1.95  104.46    2.0  \n",
       "  2788  12.93  340.0   86.0  1.63   52.02    0.8  \n",
       "  3342  12.32  329.0   87.0  1.66   61.46    1.0  "
      ]
     },
     "execution_count": 105,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "top(rides, 'vam')"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# Exploring the Data\n",
    "\n",
    "\n",
    "Some more ways to look at the data, both rides and segments."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 106,
   "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>hours</th>\n",
       "      <th>miles</th>\n",
       "      <th>feet</th>\n",
       "      <th>mph</th>\n",
       "      <th>vam</th>\n",
       "      <th>fpm</th>\n",
       "      <th>pct</th>\n",
       "      <th>kms</th>\n",
       "      <th>km_up</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>count</th>\n",
       "      <td>533.000000</td>\n",
       "      <td>533.000000</td>\n",
       "      <td>533.000000</td>\n",
       "      <td>533.000000</td>\n",
       "      <td>533.000000</td>\n",
       "      <td>533.000000</td>\n",
       "      <td>533.000000</td>\n",
       "      <td>533.000000</td>\n",
       "      <td>533.000000</td>\n",
       "      <td>533.000000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>mean</th>\n",
       "      <td>2016.881801</td>\n",
       "      <td>3.331951</td>\n",
       "      <td>42.545122</td>\n",
       "      <td>1798.016886</td>\n",
       "      <td>12.976660</td>\n",
       "      <td>157.172608</td>\n",
       "      <td>41.409006</td>\n",
       "      <td>0.784090</td>\n",
       "      <td>68.454972</td>\n",
       "      <td>0.549719</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>std</th>\n",
       "      <td>2.425411</td>\n",
       "      <td>1.440025</td>\n",
       "      <td>17.205043</td>\n",
       "      <td>1476.608108</td>\n",
       "      <td>1.314215</td>\n",
       "      <td>89.830439</td>\n",
       "      <td>27.233909</td>\n",
       "      <td>0.515731</td>\n",
       "      <td>27.682874</td>\n",
       "      <td>0.451922</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>min</th>\n",
       "      <td>2012.000000</td>\n",
       "      <td>1.540000</td>\n",
       "      <td>20.960000</td>\n",
       "      <td>68.000000</td>\n",
       "      <td>8.550000</td>\n",
       "      <td>10.000000</td>\n",
       "      <td>3.000000</td>\n",
       "      <td>0.050000</td>\n",
       "      <td>33.720000</td>\n",
       "      <td>0.000000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>25%</th>\n",
       "      <td>2015.000000</td>\n",
       "      <td>2.210000</td>\n",
       "      <td>28.870000</td>\n",
       "      <td>725.000000</td>\n",
       "      <td>12.160000</td>\n",
       "      <td>80.000000</td>\n",
       "      <td>19.000000</td>\n",
       "      <td>0.370000</td>\n",
       "      <td>46.450000</td>\n",
       "      <td>0.200000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>50%</th>\n",
       "      <td>2017.000000</td>\n",
       "      <td>2.850000</td>\n",
       "      <td>36.650000</td>\n",
       "      <td>1355.000000</td>\n",
       "      <td>13.120000</td>\n",
       "      <td>152.000000</td>\n",
       "      <td>36.000000</td>\n",
       "      <td>0.690000</td>\n",
       "      <td>58.970000</td>\n",
       "      <td>0.400000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>75%</th>\n",
       "      <td>2018.000000</td>\n",
       "      <td>4.220000</td>\n",
       "      <td>54.650000</td>\n",
       "      <td>2300.000000</td>\n",
       "      <td>13.770000</td>\n",
       "      <td>218.000000</td>\n",
       "      <td>56.000000</td>\n",
       "      <td>1.070000</td>\n",
       "      <td>87.930000</td>\n",
       "      <td>0.700000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>max</th>\n",
       "      <td>2023.000000</td>\n",
       "      <td>8.140000</td>\n",
       "      <td>102.410000</td>\n",
       "      <td>7644.000000</td>\n",
       "      <td>16.750000</td>\n",
       "      <td>406.000000</td>\n",
       "      <td>153.000000</td>\n",
       "      <td>2.900000</td>\n",
       "      <td>164.780000</td>\n",
       "      <td>2.300000</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "              year       hours       miles         feet         mph  \\\n",
       "count   533.000000  533.000000  533.000000   533.000000  533.000000   \n",
       "mean   2016.881801    3.331951   42.545122  1798.016886   12.976660   \n",
       "std       2.425411    1.440025   17.205043  1476.608108    1.314215   \n",
       "min    2012.000000    1.540000   20.960000    68.000000    8.550000   \n",
       "25%    2015.000000    2.210000   28.870000   725.000000   12.160000   \n",
       "50%    2017.000000    2.850000   36.650000  1355.000000   13.120000   \n",
       "75%    2018.000000    4.220000   54.650000  2300.000000   13.770000   \n",
       "max    2023.000000    8.140000  102.410000  7644.000000   16.750000   \n",
       "\n",
       "              vam         fpm         pct         kms       km_up  \n",
       "count  533.000000  533.000000  533.000000  533.000000  533.000000  \n",
       "mean   157.172608   41.409006    0.784090   68.454972    0.549719  \n",
       "std     89.830439   27.233909    0.515731   27.682874    0.451922  \n",
       "min     10.000000    3.000000    0.050000   33.720000    0.000000  \n",
       "25%     80.000000   19.000000    0.370000   46.450000    0.200000  \n",
       "50%    152.000000   36.000000    0.690000   58.970000    0.400000  \n",
       "75%    218.000000   56.000000    1.070000   87.930000    0.700000  \n",
       "max    406.000000  153.000000    2.900000  164.780000    2.300000  "
      ]
     },
     "execution_count": 106,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "rides.describe() # Summary statistics for the rides"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 107,
   "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>hours</th>\n",
       "      <th>miles</th>\n",
       "      <th>feet</th>\n",
       "      <th>mph</th>\n",
       "      <th>vam</th>\n",
       "      <th>fpm</th>\n",
       "      <th>pct</th>\n",
       "      <th>kms</th>\n",
       "      <th>km_up</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>count</th>\n",
       "      <td>141.000000</td>\n",
       "      <td>141.000000</td>\n",
       "      <td>141.000000</td>\n",
       "      <td>141.000000</td>\n",
       "      <td>141.000000</td>\n",
       "      <td>141.000000</td>\n",
       "      <td>141.000000</td>\n",
       "      <td>141.000000</td>\n",
       "      <td>141.000000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>mean</th>\n",
       "      <td>0.141702</td>\n",
       "      <td>0.932979</td>\n",
       "      <td>268.978723</td>\n",
       "      <td>7.444539</td>\n",
       "      <td>641.893617</td>\n",
       "      <td>353.503546</td>\n",
       "      <td>6.694894</td>\n",
       "      <td>1.501064</td>\n",
       "      <td>0.073050</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>std</th>\n",
       "      <td>0.173711</td>\n",
       "      <td>0.989832</td>\n",
       "      <td>295.060659</td>\n",
       "      <td>3.557336</td>\n",
       "      <td>211.923595</td>\n",
       "      <td>186.816320</td>\n",
       "      <td>3.537974</td>\n",
       "      <td>1.592267</td>\n",
       "      <td>0.101334</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>min</th>\n",
       "      <td>0.010000</td>\n",
       "      <td>0.080000</td>\n",
       "      <td>21.000000</td>\n",
       "      <td>2.120000</td>\n",
       "      <td>111.000000</td>\n",
       "      <td>18.000000</td>\n",
       "      <td>0.350000</td>\n",
       "      <td>0.130000</td>\n",
       "      <td>0.000000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>25%</th>\n",
       "      <td>0.050000</td>\n",
       "      <td>0.330000</td>\n",
       "      <td>104.000000</td>\n",
       "      <td>4.830000</td>\n",
       "      <td>503.000000</td>\n",
       "      <td>219.000000</td>\n",
       "      <td>4.140000</td>\n",
       "      <td>0.530000</td>\n",
       "      <td>0.000000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>50%</th>\n",
       "      <td>0.090000</td>\n",
       "      <td>0.600000</td>\n",
       "      <td>166.000000</td>\n",
       "      <td>6.190000</td>\n",
       "      <td>630.000000</td>\n",
       "      <td>333.000000</td>\n",
       "      <td>6.300000</td>\n",
       "      <td>0.970000</td>\n",
       "      <td>0.100000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>75%</th>\n",
       "      <td>0.150000</td>\n",
       "      <td>1.190000</td>\n",
       "      <td>303.000000</td>\n",
       "      <td>9.800000</td>\n",
       "      <td>724.000000</td>\n",
       "      <td>462.000000</td>\n",
       "      <td>8.760000</td>\n",
       "      <td>1.910000</td>\n",
       "      <td>0.100000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>max</th>\n",
       "      <td>1.390000</td>\n",
       "      <td>7.380000</td>\n",
       "      <td>1887.000000</td>\n",
       "      <td>19.790000</td>\n",
       "      <td>1463.000000</td>\n",
       "      <td>839.000000</td>\n",
       "      <td>15.890000</td>\n",
       "      <td>11.870000</td>\n",
       "      <td>0.600000</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "            hours       miles         feet         mph          vam  \\\n",
       "count  141.000000  141.000000   141.000000  141.000000   141.000000   \n",
       "mean     0.141702    0.932979   268.978723    7.444539   641.893617   \n",
       "std      0.173711    0.989832   295.060659    3.557336   211.923595   \n",
       "min      0.010000    0.080000    21.000000    2.120000   111.000000   \n",
       "25%      0.050000    0.330000   104.000000    4.830000   503.000000   \n",
       "50%      0.090000    0.600000   166.000000    6.190000   630.000000   \n",
       "75%      0.150000    1.190000   303.000000    9.800000   724.000000   \n",
       "max      1.390000    7.380000  1887.000000   19.790000  1463.000000   \n",
       "\n",
       "              fpm         pct         kms       km_up  \n",
       "count  141.000000  141.000000  141.000000  141.000000  \n",
       "mean   353.503546    6.694894    1.501064    0.073050  \n",
       "std    186.816320    3.537974    1.592267    0.101334  \n",
       "min     18.000000    0.350000    0.130000    0.000000  \n",
       "25%    219.000000    4.140000    0.530000    0.000000  \n",
       "50%    333.000000    6.300000    0.970000    0.100000  \n",
       "75%    462.000000    8.760000    1.910000    0.100000  \n",
       "max    839.000000   15.890000   11.870000    0.600000  "
      ]
     },
     "execution_count": 107,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "segments.describe() # Summary statistics for the segments"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 108,
   "metadata": {},
   "outputs": [
    {
     "data": {
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       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>date</th>\n",
       "      <th>year</th>\n",
       "      <th>title</th>\n",
       "      <th>hours</th>\n",
       "      <th>miles</th>\n",
       "      <th>feet</th>\n",
       "      <th>mph</th>\n",
       "      <th>vam</th>\n",
       "      <th>fpm</th>\n",
       "      <th>pct</th>\n",
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       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th></th>\n",
       "      <td>Sun, 5/22</td>\n",
       "      <td>2016</td>\n",
       "      <td>Canada</td>\n",
       "      <td>2.19</td>\n",
       "      <td>36.68</td>\n",
       "      <td>1332</td>\n",
       "      <td>16.75</td>\n",
       "      <td>185.0</td>\n",
       "      <td>36.0</td>\n",
       "      <td>0.69</td>\n",
       "      <td>59.02</td>\n",
       "      <td>0.4</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th></th>\n",
       "      <td>Wed, 9/13</td>\n",
       "      <td>2017</td>\n",
       "      <td>Healdburg / Jimtown</td>\n",
       "      <td>2.13</td>\n",
       "      <td>34.45</td>\n",
       "      <td>912</td>\n",
       "      <td>16.17</td>\n",
       "      <td>131.0</td>\n",
       "      <td>26.0</td>\n",
       "      <td>0.50</td>\n",
       "      <td>55.43</td>\n",
       "      <td>0.3</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th></th>\n",
       "      <td>Sat, 1/25</td>\n",
       "      <td>2014</td>\n",
       "      <td>Woodside</td>\n",
       "      <td>1.56</td>\n",
       "      <td>25.08</td>\n",
       "      <td>1243</td>\n",
       "      <td>16.08</td>\n",
       "      <td>243.0</td>\n",
       "      <td>50.0</td>\n",
       "      <td>0.94</td>\n",
       "      <td>40.35</td>\n",
       "      <td>0.4</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th></th>\n",
       "      <td>Sat, 4/11</td>\n",
       "      <td>2015</td>\n",
       "      <td>Woodside</td>\n",
       "      <td>1.54</td>\n",
       "      <td>24.73</td>\n",
       "      <td>1035</td>\n",
       "      <td>16.06</td>\n",
       "      <td>205.0</td>\n",
       "      <td>42.0</td>\n",
       "      <td>0.79</td>\n",
       "      <td>39.79</td>\n",
       "      <td>0.3</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th></th>\n",
       "      <td>Sun, 7/11</td>\n",
       "      <td>2021</td>\n",
       "      <td>San Jose</td>\n",
       "      <td>4.10</td>\n",
       "      <td>65.10</td>\n",
       "      <td>1086</td>\n",
       "      <td>15.88</td>\n",
       "      <td>81.0</td>\n",
       "      <td>17.0</td>\n",
       "      <td>0.32</td>\n",
       "      <td>104.75</td>\n",
       "      <td>0.3</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th></th>\n",
       "      <td>Sun, 1/18</td>\n",
       "      <td>2015</td>\n",
       "      <td>Woodside</td>\n",
       "      <td>1.64</td>\n",
       "      <td>26.02</td>\n",
       "      <td>1257</td>\n",
       "      <td>15.87</td>\n",
       "      <td>234.0</td>\n",
       "      <td>48.0</td>\n",
       "      <td>0.91</td>\n",
       "      <td>41.87</td>\n",
       "      <td>0.4</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th></th>\n",
       "      <td>Fri, 6/24</td>\n",
       "      <td>2016</td>\n",
       "      <td>Foothill Expway</td>\n",
       "      <td>1.59</td>\n",
       "      <td>25.11</td>\n",
       "      <td>623</td>\n",
       "      <td>15.79</td>\n",
       "      <td>119.0</td>\n",
       "      <td>25.0</td>\n",
       "      <td>0.47</td>\n",
       "      <td>40.40</td>\n",
       "      <td>0.2</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th></th>\n",
       "      <td>Sun, 1/26</td>\n",
       "      <td>2014</td>\n",
       "      <td>Canada Rd</td>\n",
       "      <td>2.10</td>\n",
       "      <td>33.12</td>\n",
       "      <td>1446</td>\n",
       "      <td>15.77</td>\n",
       "      <td>210.0</td>\n",
       "      <td>44.0</td>\n",
       "      <td>0.83</td>\n",
       "      <td>53.29</td>\n",
       "      <td>0.4</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th></th>\n",
       "      <td>Fri, 1/6</td>\n",
       "      <td>2012</td>\n",
       "      <td>Omarama to Wanaka New Zealand</td>\n",
       "      <td>4.48</td>\n",
       "      <td>70.35</td>\n",
       "      <td>3262</td>\n",
       "      <td>15.70</td>\n",
       "      <td>222.0</td>\n",
       "      <td>46.0</td>\n",
       "      <td>0.88</td>\n",
       "      <td>113.19</td>\n",
       "      <td>1.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th></th>\n",
       "      <td>Sun, 4/12</td>\n",
       "      <td>2015</td>\n",
       "      <td>Palo Alto Cycling</td>\n",
       "      <td>2.03</td>\n",
       "      <td>31.76</td>\n",
       "      <td>1210</td>\n",
       "      <td>15.65</td>\n",
       "      <td>182.0</td>\n",
       "      <td>38.0</td>\n",
       "      <td>0.72</td>\n",
       "      <td>51.10</td>\n",
       "      <td>0.4</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th></th>\n",
       "      <td>Sun, 10/15</td>\n",
       "      <td>2017</td>\n",
       "      <td>Los Gatos</td>\n",
       "      <td>2.86</td>\n",
       "      <td>44.71</td>\n",
       "      <td>1437</td>\n",
       "      <td>15.63</td>\n",
       "      <td>153.0</td>\n",
       "      <td>32.0</td>\n",
       "      <td>0.61</td>\n",
       "      <td>71.94</td>\n",
       "      <td>0.4</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th></th>\n",
       "      <td>Sun, 8/5</td>\n",
       "      <td>2018</td>\n",
       "      <td>Bike Ride Northwest Day 1</td>\n",
       "      <td>3.58</td>\n",
       "      <td>55.77</td>\n",
       "      <td>1824</td>\n",
       "      <td>15.58</td>\n",
       "      <td>155.0</td>\n",
       "      <td>33.0</td>\n",
       "      <td>0.62</td>\n",
       "      <td>89.73</td>\n",
       "      <td>0.6</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th></th>\n",
       "      <td>Sun, 2/28</td>\n",
       "      <td>2016</td>\n",
       "      <td>Woodside Loop</td>\n",
       "      <td>1.73</td>\n",
       "      <td>26.93</td>\n",
       "      <td>843</td>\n",
       "      <td>15.57</td>\n",
       "      <td>149.0</td>\n",
       "      <td>31.0</td>\n",
       "      <td>0.59</td>\n",
       "      <td>43.33</td>\n",
       "      <td>0.3</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th></th>\n",
       "      <td>Sun, 6/26</td>\n",
       "      <td>2016</td>\n",
       "      <td>Los Gatos</td>\n",
       "      <td>3.28</td>\n",
       "      <td>50.78</td>\n",
       "      <td>1181</td>\n",
       "      <td>15.48</td>\n",
       "      <td>110.0</td>\n",
       "      <td>23.0</td>\n",
       "      <td>0.44</td>\n",
       "      <td>81.71</td>\n",
       "      <td>0.4</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th></th>\n",
       "      <td>Mon, 1/19</td>\n",
       "      <td>2015</td>\n",
       "      <td>Canada Rd, etc.</td>\n",
       "      <td>2.95</td>\n",
       "      <td>45.64</td>\n",
       "      <td>1836</td>\n",
       "      <td>15.47</td>\n",
       "      <td>190.0</td>\n",
       "      <td>40.0</td>\n",
       "      <td>0.76</td>\n",
       "      <td>73.43</td>\n",
       "      <td>0.6</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th></th>\n",
       "      <td>Sun, 1/19</td>\n",
       "      <td>2014</td>\n",
       "      <td>Palo Alto, CA</td>\n",
       "      <td>1.62</td>\n",
       "      <td>25.01</td>\n",
       "      <td>1201</td>\n",
       "      <td>15.44</td>\n",
       "      <td>226.0</td>\n",
       "      <td>48.0</td>\n",
       "      <td>0.91</td>\n",
       "      <td>40.24</td>\n",
       "      <td>0.4</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th></th>\n",
       "      <td>Sun, 12/6</td>\n",
       "      <td>2015</td>\n",
       "      <td>Canada Rd</td>\n",
       "      <td>2.25</td>\n",
       "      <td>34.67</td>\n",
       "      <td>1237</td>\n",
       "      <td>15.41</td>\n",
       "      <td>168.0</td>\n",
       "      <td>36.0</td>\n",
       "      <td>0.68</td>\n",
       "      <td>55.78</td>\n",
       "      <td>0.4</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th></th>\n",
       "      <td>Tue, 6/18</td>\n",
       "      <td>2013</td>\n",
       "      <td>work etc (headwinds)</td>\n",
       "      <td>2.06</td>\n",
       "      <td>31.48</td>\n",
       "      <td>809</td>\n",
       "      <td>15.28</td>\n",
       "      <td>120.0</td>\n",
       "      <td>26.0</td>\n",
       "      <td>0.49</td>\n",
       "      <td>50.65</td>\n",
       "      <td>0.2</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th></th>\n",
       "      <td>Fri, 9/23</td>\n",
       "      <td>2016</td>\n",
       "      <td>Los Gatos</td>\n",
       "      <td>2.89</td>\n",
       "      <td>43.93</td>\n",
       "      <td>1339</td>\n",
       "      <td>15.20</td>\n",
       "      <td>141.0</td>\n",
       "      <td>30.0</td>\n",
       "      <td>0.58</td>\n",
       "      <td>70.68</td>\n",
       "      <td>0.4</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th></th>\n",
       "      <td>Sat, 7/9</td>\n",
       "      <td>2016</td>\n",
       "      <td>Santa Cruz</td>\n",
       "      <td>3.84</td>\n",
       "      <td>58.23</td>\n",
       "      <td>4042</td>\n",
       "      <td>15.16</td>\n",
       "      <td>321.0</td>\n",
       "      <td>69.0</td>\n",
       "      <td>1.31</td>\n",
       "      <td>93.69</td>\n",
       "      <td>1.2</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "        date  year                          title  hours  miles  feet    mph  \\\n",
       "   Sun, 5/22  2016                         Canada   2.19  36.68  1332  16.75   \n",
       "   Wed, 9/13  2017            Healdburg / Jimtown   2.13  34.45   912  16.17   \n",
       "   Sat, 1/25  2014                       Woodside   1.56  25.08  1243  16.08   \n",
       "   Sat, 4/11  2015                       Woodside   1.54  24.73  1035  16.06   \n",
       "   Sun, 7/11  2021                       San Jose   4.10  65.10  1086  15.88   \n",
       "   Sun, 1/18  2015                       Woodside   1.64  26.02  1257  15.87   \n",
       "   Fri, 6/24  2016                Foothill Expway   1.59  25.11   623  15.79   \n",
       "   Sun, 1/26  2014                      Canada Rd   2.10  33.12  1446  15.77   \n",
       "    Fri, 1/6  2012  Omarama to Wanaka New Zealand   4.48  70.35  3262  15.70   \n",
       "   Sun, 4/12  2015              Palo Alto Cycling   2.03  31.76  1210  15.65   \n",
       "  Sun, 10/15  2017                      Los Gatos   2.86  44.71  1437  15.63   \n",
       "    Sun, 8/5  2018      Bike Ride Northwest Day 1   3.58  55.77  1824  15.58   \n",
       "   Sun, 2/28  2016                  Woodside Loop   1.73  26.93   843  15.57   \n",
       "   Sun, 6/26  2016                      Los Gatos   3.28  50.78  1181  15.48   \n",
       "   Mon, 1/19  2015                Canada Rd, etc.   2.95  45.64  1836  15.47   \n",
       "   Sun, 1/19  2014                  Palo Alto, CA   1.62  25.01  1201  15.44   \n",
       "   Sun, 12/6  2015                      Canada Rd   2.25  34.67  1237  15.41   \n",
       "   Tue, 6/18  2013           work etc (headwinds)   2.06  31.48   809  15.28   \n",
       "   Fri, 9/23  2016                      Los Gatos   2.89  43.93  1339  15.20   \n",
       "    Sat, 7/9  2016                     Santa Cruz   3.84  58.23  4042  15.16   \n",
       "\n",
       "    vam   fpm   pct     kms  km_up  \n",
       "  185.0  36.0  0.69   59.02    0.4  \n",
       "  131.0  26.0  0.50   55.43    0.3  \n",
       "  243.0  50.0  0.94   40.35    0.4  \n",
       "  205.0  42.0  0.79   39.79    0.3  \n",
       "   81.0  17.0  0.32  104.75    0.3  \n",
       "  234.0  48.0  0.91   41.87    0.4  \n",
       "  119.0  25.0  0.47   40.40    0.2  \n",
       "  210.0  44.0  0.83   53.29    0.4  \n",
       "  222.0  46.0  0.88  113.19    1.0  \n",
       "  182.0  38.0  0.72   51.10    0.4  \n",
       "  153.0  32.0  0.61   71.94    0.4  \n",
       "  155.0  33.0  0.62   89.73    0.6  \n",
       "  149.0  31.0  0.59   43.33    0.3  \n",
       "  110.0  23.0  0.44   81.71    0.4  \n",
       "  190.0  40.0  0.76   73.43    0.6  \n",
       "  226.0  48.0  0.91   40.24    0.4  \n",
       "  168.0  36.0  0.68   55.78    0.4  \n",
       "  120.0  26.0  0.49   50.65    0.2  \n",
       "  141.0  30.0  0.58   70.68    0.4  \n",
       "  321.0  69.0  1.31   93.69    1.2  "
      ]
     },
     "execution_count": 108,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "top(rides, 'mph') # Fastest rides (of more than 20 miles)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 109,
   "metadata": {},
   "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",
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       "        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>title</th>\n",
       "      <th>hours</th>\n",
       "      <th>miles</th>\n",
       "      <th>feet</th>\n",
       "      <th>mph</th>\n",
       "      <th>vam</th>\n",
       "      <th>fpm</th>\n",
       "      <th>pct</th>\n",
       "      <th>kms</th>\n",
       "      <th>km_up</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>76</th>\n",
       "      <td>PCH Pescadero to Bean Hollow</td>\n",
       "      <td>0.14</td>\n",
       "      <td>2.77</td>\n",
       "      <td>51</td>\n",
       "      <td>19.79</td>\n",
       "      <td>111.0</td>\n",
       "      <td>18.0</td>\n",
       "      <td>0.35</td>\n",
       "      <td>4.46</td>\n",
       "      <td>0.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>36</th>\n",
       "      <td>Highway 1  Cascanoa to Cascade</td>\n",
       "      <td>0.09</td>\n",
       "      <td>1.61</td>\n",
       "      <td>89</td>\n",
       "      <td>17.89</td>\n",
       "      <td>301.0</td>\n",
       "      <td>55.0</td>\n",
       "      <td>1.05</td>\n",
       "      <td>2.59</td>\n",
       "      <td>0.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>123</th>\n",
       "      <td>Vickrey Fruitvale</td>\n",
       "      <td>0.06</td>\n",
       "      <td>0.99</td>\n",
       "      <td>68</td>\n",
       "      <td>16.50</td>\n",
       "      <td>345.0</td>\n",
       "      <td>69.0</td>\n",
       "      <td>1.30</td>\n",
       "      <td>1.59</td>\n",
       "      <td>0.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>39</th>\n",
       "      <td>Highway 9 Mantalvo</td>\n",
       "      <td>0.03</td>\n",
       "      <td>0.45</td>\n",
       "      <td>35</td>\n",
       "      <td>15.00</td>\n",
       "      <td>356.0</td>\n",
       "      <td>78.0</td>\n",
       "      <td>1.47</td>\n",
       "      <td>0.72</td>\n",
       "      <td>0.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>38</th>\n",
       "      <td>Highway 9 Mantalvo</td>\n",
       "      <td>0.03</td>\n",
       "      <td>0.45</td>\n",
       "      <td>35</td>\n",
       "      <td>15.00</td>\n",
       "      <td>356.0</td>\n",
       "      <td>78.0</td>\n",
       "      <td>1.47</td>\n",
       "      <td>0.72</td>\n",
       "      <td>0.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>109</th>\n",
       "      <td>The Boneyard</td>\n",
       "      <td>0.10</td>\n",
       "      <td>1.48</td>\n",
       "      <td>135</td>\n",
       "      <td>14.80</td>\n",
       "      <td>411.0</td>\n",
       "      <td>91.0</td>\n",
       "      <td>1.73</td>\n",
       "      <td>2.38</td>\n",
       "      <td>0.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>124</th>\n",
       "      <td>Vickrey Fruitvale</td>\n",
       "      <td>0.07</td>\n",
       "      <td>0.99</td>\n",
       "      <td>68</td>\n",
       "      <td>14.14</td>\n",
       "      <td>296.0</td>\n",
       "      <td>69.0</td>\n",
       "      <td>1.30</td>\n",
       "      <td>1.59</td>\n",
       "      <td>0.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>90</th>\n",
       "      <td>Sand Hill Alpine to 280</td>\n",
       "      <td>0.12</td>\n",
       "      <td>1.67</td>\n",
       "      <td>180</td>\n",
       "      <td>13.92</td>\n",
       "      <td>457.0</td>\n",
       "      <td>108.0</td>\n",
       "      <td>2.04</td>\n",
       "      <td>2.69</td>\n",
       "      <td>0.1</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>15</th>\n",
       "      <td>Canada to College</td>\n",
       "      <td>0.10</td>\n",
       "      <td>1.37</td>\n",
       "      <td>119</td>\n",
       "      <td>13.70</td>\n",
       "      <td>363.0</td>\n",
       "      <td>87.0</td>\n",
       "      <td>1.65</td>\n",
       "      <td>2.20</td>\n",
       "      <td>0.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>30</th>\n",
       "      <td>Foothill Homestead</td>\n",
       "      <td>0.09</td>\n",
       "      <td>1.22</td>\n",
       "      <td>126</td>\n",
       "      <td>13.56</td>\n",
       "      <td>427.0</td>\n",
       "      <td>103.0</td>\n",
       "      <td>1.96</td>\n",
       "      <td>1.96</td>\n",
       "      <td>0.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>110</th>\n",
       "      <td>The Boneyard</td>\n",
       "      <td>0.11</td>\n",
       "      <td>1.48</td>\n",
       "      <td>135</td>\n",
       "      <td>13.45</td>\n",
       "      <td>374.0</td>\n",
       "      <td>91.0</td>\n",
       "      <td>1.73</td>\n",
       "      <td>2.38</td>\n",
       "      <td>0.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>45</th>\n",
       "      <td>Kaboom Portola Rd</td>\n",
       "      <td>0.05</td>\n",
       "      <td>0.67</td>\n",
       "      <td>102</td>\n",
       "      <td>13.40</td>\n",
       "      <td>622.0</td>\n",
       "      <td>152.0</td>\n",
       "      <td>2.88</td>\n",
       "      <td>1.08</td>\n",
       "      <td>0.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>139</th>\n",
       "      <td>Woodside Climb</td>\n",
       "      <td>0.13</td>\n",
       "      <td>1.71</td>\n",
       "      <td>295</td>\n",
       "      <td>13.15</td>\n",
       "      <td>692.0</td>\n",
       "      <td>173.0</td>\n",
       "      <td>3.27</td>\n",
       "      <td>2.75</td>\n",
       "      <td>0.1</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>91</th>\n",
       "      <td>Sand Hill Alpine to 280</td>\n",
       "      <td>0.13</td>\n",
       "      <td>1.67</td>\n",
       "      <td>180</td>\n",
       "      <td>12.85</td>\n",
       "      <td>422.0</td>\n",
       "      <td>108.0</td>\n",
       "      <td>2.04</td>\n",
       "      <td>2.69</td>\n",
       "      <td>0.1</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>Alpine Westridge</td>\n",
       "      <td>0.06</td>\n",
       "      <td>0.76</td>\n",
       "      <td>99</td>\n",
       "      <td>12.67</td>\n",
       "      <td>503.0</td>\n",
       "      <td>130.0</td>\n",
       "      <td>2.47</td>\n",
       "      <td>1.22</td>\n",
       "      <td>0.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>Alpine Westridge</td>\n",
       "      <td>0.06</td>\n",
       "      <td>0.76</td>\n",
       "      <td>99</td>\n",
       "      <td>12.67</td>\n",
       "      <td>503.0</td>\n",
       "      <td>130.0</td>\n",
       "      <td>2.47</td>\n",
       "      <td>1.22</td>\n",
       "      <td>0.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>98</th>\n",
       "      <td>Stanford Ave</td>\n",
       "      <td>0.05</td>\n",
       "      <td>0.63</td>\n",
       "      <td>85</td>\n",
       "      <td>12.60</td>\n",
       "      <td>518.0</td>\n",
       "      <td>135.0</td>\n",
       "      <td>2.56</td>\n",
       "      <td>1.01</td>\n",
       "      <td>0.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>16</th>\n",
       "      <td>Canada to College</td>\n",
       "      <td>0.11</td>\n",
       "      <td>1.37</td>\n",
       "      <td>119</td>\n",
       "      <td>12.45</td>\n",
       "      <td>330.0</td>\n",
       "      <td>87.0</td>\n",
       "      <td>1.65</td>\n",
       "      <td>2.20</td>\n",
       "      <td>0.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>88</th>\n",
       "      <td>Sand Hill 280 to horse</td>\n",
       "      <td>0.04</td>\n",
       "      <td>0.49</td>\n",
       "      <td>95</td>\n",
       "      <td>12.25</td>\n",
       "      <td>724.0</td>\n",
       "      <td>194.0</td>\n",
       "      <td>3.67</td>\n",
       "      <td>0.79</td>\n",
       "      <td>0.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>100</th>\n",
       "      <td>Stevens Country Park</td>\n",
       "      <td>0.10</td>\n",
       "      <td>1.22</td>\n",
       "      <td>112</td>\n",
       "      <td>12.20</td>\n",
       "      <td>341.0</td>\n",
       "      <td>92.0</td>\n",
       "      <td>1.74</td>\n",
       "      <td>1.96</td>\n",
       "      <td>0.0</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "                              title  hours  miles  feet    mph    vam    fpm  \\\n",
       "76     PCH Pescadero to Bean Hollow   0.14   2.77    51  19.79  111.0   18.0   \n",
       "36   Highway 1  Cascanoa to Cascade   0.09   1.61    89  17.89  301.0   55.0   \n",
       "123               Vickrey Fruitvale   0.06   0.99    68  16.50  345.0   69.0   \n",
       "39               Highway 9 Mantalvo   0.03   0.45    35  15.00  356.0   78.0   \n",
       "38               Highway 9 Mantalvo   0.03   0.45    35  15.00  356.0   78.0   \n",
       "109                    The Boneyard   0.10   1.48   135  14.80  411.0   91.0   \n",
       "124               Vickrey Fruitvale   0.07   0.99    68  14.14  296.0   69.0   \n",
       "90          Sand Hill Alpine to 280   0.12   1.67   180  13.92  457.0  108.0   \n",
       "15                Canada to College   0.10   1.37   119  13.70  363.0   87.0   \n",
       "30               Foothill Homestead   0.09   1.22   126  13.56  427.0  103.0   \n",
       "110                    The Boneyard   0.11   1.48   135  13.45  374.0   91.0   \n",
       "45                Kaboom Portola Rd   0.05   0.67   102  13.40  622.0  152.0   \n",
       "139                  Woodside Climb   0.13   1.71   295  13.15  692.0  173.0   \n",
       "91          Sand Hill Alpine to 280   0.13   1.67   180  12.85  422.0  108.0   \n",
       "1                  Alpine Westridge   0.06   0.76    99  12.67  503.0  130.0   \n",
       "2                  Alpine Westridge   0.06   0.76    99  12.67  503.0  130.0   \n",
       "98                     Stanford Ave   0.05   0.63    85  12.60  518.0  135.0   \n",
       "16                Canada to College   0.11   1.37   119  12.45  330.0   87.0   \n",
       "88           Sand Hill 280 to horse   0.04   0.49    95  12.25  724.0  194.0   \n",
       "100            Stevens Country Park   0.10   1.22   112  12.20  341.0   92.0   \n",
       "\n",
       "      pct   kms  km_up  \n",
       "76   0.35  4.46    0.0  \n",
       "36   1.05  2.59    0.0  \n",
       "123  1.30  1.59    0.0  \n",
       "39   1.47  0.72    0.0  \n",
       "38   1.47  0.72    0.0  \n",
       "109  1.73  2.38    0.0  \n",
       "124  1.30  1.59    0.0  \n",
       "90   2.04  2.69    0.1  \n",
       "15   1.65  2.20    0.0  \n",
       "30   1.96  1.96    0.0  \n",
       "110  1.73  2.38    0.0  \n",
       "45   2.88  1.08    0.0  \n",
       "139  3.27  2.75    0.1  \n",
       "91   2.04  2.69    0.1  \n",
       "1    2.47  1.22    0.0  \n",
       "2    2.47  1.22    0.0  \n",
       "98   2.56  1.01    0.0  \n",
       "16   1.65  2.20    0.0  \n",
       "88   3.67  0.79    0.0  \n",
       "100  1.74  1.96    0.0  "
      ]
     },
     "execution_count": 109,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "top(segments, 'mph') # Fastest segments (there are no descent segments in the database)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 110,
   "metadata": {},
   "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>title</th>\n",
       "      <th>hours</th>\n",
       "      <th>miles</th>\n",
       "      <th>feet</th>\n",
       "      <th>mph</th>\n",
       "      <th>vam</th>\n",
       "      <th>fpm</th>\n",
       "      <th>pct</th>\n",
       "      <th>kms</th>\n",
       "      <th>km_up</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>128</th>\n",
       "      <td>West Alpine full</td>\n",
       "      <td>1.39</td>\n",
       "      <td>7.38</td>\n",
       "      <td>1887</td>\n",
       "      <td>5.31</td>\n",
       "      <td>414.0</td>\n",
       "      <td>256.0</td>\n",
       "      <td>4.84</td>\n",
       "      <td>11.87</td>\n",
       "      <td>0.6</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>51</th>\n",
       "      <td>Kings Greer to Skyline</td>\n",
       "      <td>0.78</td>\n",
       "      <td>3.92</td>\n",
       "      <td>1536</td>\n",
       "      <td>5.03</td>\n",
       "      <td>600.0</td>\n",
       "      <td>392.0</td>\n",
       "      <td>7.42</td>\n",
       "      <td>6.31</td>\n",
       "      <td>0.5</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>52</th>\n",
       "      <td>Kings Greer to Skyline</td>\n",
       "      <td>0.81</td>\n",
       "      <td>3.92</td>\n",
       "      <td>1536</td>\n",
       "      <td>4.84</td>\n",
       "      <td>578.0</td>\n",
       "      <td>392.0</td>\n",
       "      <td>7.42</td>\n",
       "      <td>6.31</td>\n",
       "      <td>0.5</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>67</th>\n",
       "      <td>Old La Honda (Bridge to Stop)</td>\n",
       "      <td>0.48</td>\n",
       "      <td>3.33</td>\n",
       "      <td>1255</td>\n",
       "      <td>6.94</td>\n",
       "      <td>797.0</td>\n",
       "      <td>377.0</td>\n",
       "      <td>7.14</td>\n",
       "      <td>5.36</td>\n",
       "      <td>0.4</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>68</th>\n",
       "      <td>Old La Honda (Bridge to Stop)</td>\n",
       "      <td>0.51</td>\n",
       "      <td>3.33</td>\n",
       "      <td>1255</td>\n",
       "      <td>6.53</td>\n",
       "      <td>750.0</td>\n",
       "      <td>377.0</td>\n",
       "      <td>7.14</td>\n",
       "      <td>5.36</td>\n",
       "      <td>0.4</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>Alma Mountain Charlie</td>\n",
       "      <td>0.53</td>\n",
       "      <td>3.12</td>\n",
       "      <td>875</td>\n",
       "      <td>5.89</td>\n",
       "      <td>503.0</td>\n",
       "      <td>280.0</td>\n",
       "      <td>5.31</td>\n",
       "      <td>5.02</td>\n",
       "      <td>0.3</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>47</th>\n",
       "      <td>Kings half way</td>\n",
       "      <td>0.46</td>\n",
       "      <td>2.89</td>\n",
       "      <td>820</td>\n",
       "      <td>6.28</td>\n",
       "      <td>543.0</td>\n",
       "      <td>284.0</td>\n",
       "      <td>5.37</td>\n",
       "      <td>4.65</td>\n",
       "      <td>0.2</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>48</th>\n",
       "      <td>Kings half way</td>\n",
       "      <td>0.50</td>\n",
       "      <td>2.89</td>\n",
       "      <td>820</td>\n",
       "      <td>5.78</td>\n",
       "      <td>500.0</td>\n",
       "      <td>284.0</td>\n",
       "      <td>5.37</td>\n",
       "      <td>4.65</td>\n",
       "      <td>0.2</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>5</th>\n",
       "      <td>Alpine Portola to top Joaquin</td>\n",
       "      <td>0.57</td>\n",
       "      <td>3.52</td>\n",
       "      <td>801</td>\n",
       "      <td>6.18</td>\n",
       "      <td>428.0</td>\n",
       "      <td>228.0</td>\n",
       "      <td>4.31</td>\n",
       "      <td>5.66</td>\n",
       "      <td>0.2</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>6</th>\n",
       "      <td>Alpine Portola to top Joaquin</td>\n",
       "      <td>0.58</td>\n",
       "      <td>3.52</td>\n",
       "      <td>801</td>\n",
       "      <td>6.07</td>\n",
       "      <td>421.0</td>\n",
       "      <td>228.0</td>\n",
       "      <td>4.31</td>\n",
       "      <td>5.66</td>\n",
       "      <td>0.2</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>120</th>\n",
       "      <td>Tunitas steep</td>\n",
       "      <td>0.27</td>\n",
       "      <td>1.20</td>\n",
       "      <td>599</td>\n",
       "      <td>4.44</td>\n",
       "      <td>676.0</td>\n",
       "      <td>499.0</td>\n",
       "      <td>9.45</td>\n",
       "      <td>1.93</td>\n",
       "      <td>0.2</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>119</th>\n",
       "      <td>Tunitas steep</td>\n",
       "      <td>0.25</td>\n",
       "      <td>1.20</td>\n",
       "      <td>599</td>\n",
       "      <td>4.80</td>\n",
       "      <td>730.0</td>\n",
       "      <td>499.0</td>\n",
       "      <td>9.45</td>\n",
       "      <td>1.93</td>\n",
       "      <td>0.2</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>34</th>\n",
       "      <td>Haskins</td>\n",
       "      <td>0.30</td>\n",
       "      <td>1.51</td>\n",
       "      <td>566</td>\n",
       "      <td>5.03</td>\n",
       "      <td>575.0</td>\n",
       "      <td>375.0</td>\n",
       "      <td>7.10</td>\n",
       "      <td>2.43</td>\n",
       "      <td>0.2</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>35</th>\n",
       "      <td>Haskins</td>\n",
       "      <td>0.31</td>\n",
       "      <td>1.51</td>\n",
       "      <td>566</td>\n",
       "      <td>4.87</td>\n",
       "      <td>557.0</td>\n",
       "      <td>375.0</td>\n",
       "      <td>7.10</td>\n",
       "      <td>2.43</td>\n",
       "      <td>0.2</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>23</th>\n",
       "      <td>Coe Second Switchback to flat</td>\n",
       "      <td>0.22</td>\n",
       "      <td>1.00</td>\n",
       "      <td>483</td>\n",
       "      <td>4.55</td>\n",
       "      <td>669.0</td>\n",
       "      <td>483.0</td>\n",
       "      <td>9.15</td>\n",
       "      <td>1.61</td>\n",
       "      <td>0.1</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>60</th>\n",
       "      <td>Lower Redwood Gulch</td>\n",
       "      <td>0.22</td>\n",
       "      <td>1.03</td>\n",
       "      <td>474</td>\n",
       "      <td>4.68</td>\n",
       "      <td>657.0</td>\n",
       "      <td>460.0</td>\n",
       "      <td>8.72</td>\n",
       "      <td>1.66</td>\n",
       "      <td>0.1</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>8</th>\n",
       "      <td>Alpine Willowbrook to Joaquin</td>\n",
       "      <td>0.29</td>\n",
       "      <td>2.27</td>\n",
       "      <td>461</td>\n",
       "      <td>7.83</td>\n",
       "      <td>485.0</td>\n",
       "      <td>203.0</td>\n",
       "      <td>3.85</td>\n",
       "      <td>3.65</td>\n",
       "      <td>0.1</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>7</th>\n",
       "      <td>Alpine Willowbrook to Joaquin</td>\n",
       "      <td>0.28</td>\n",
       "      <td>2.27</td>\n",
       "      <td>461</td>\n",
       "      <td>8.11</td>\n",
       "      <td>502.0</td>\n",
       "      <td>203.0</td>\n",
       "      <td>3.85</td>\n",
       "      <td>3.65</td>\n",
       "      <td>0.1</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>59</th>\n",
       "      <td>Lobitas Creek</td>\n",
       "      <td>0.20</td>\n",
       "      <td>0.96</td>\n",
       "      <td>430</td>\n",
       "      <td>4.80</td>\n",
       "      <td>655.0</td>\n",
       "      <td>448.0</td>\n",
       "      <td>8.48</td>\n",
       "      <td>1.54</td>\n",
       "      <td>0.1</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>117</th>\n",
       "      <td>Tunitas lower climb</td>\n",
       "      <td>0.22</td>\n",
       "      <td>1.30</td>\n",
       "      <td>421</td>\n",
       "      <td>5.91</td>\n",
       "      <td>583.0</td>\n",
       "      <td>324.0</td>\n",
       "      <td>6.13</td>\n",
       "      <td>2.09</td>\n",
       "      <td>0.1</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "                             title  hours  miles  feet   mph    vam    fpm  \\\n",
       "128               West Alpine full   1.39   7.38  1887  5.31  414.0  256.0   \n",
       "51          Kings Greer to Skyline   0.78   3.92  1536  5.03  600.0  392.0   \n",
       "52          Kings Greer to Skyline   0.81   3.92  1536  4.84  578.0  392.0   \n",
       "67   Old La Honda (Bridge to Stop)   0.48   3.33  1255  6.94  797.0  377.0   \n",
       "68   Old La Honda (Bridge to Stop)   0.51   3.33  1255  6.53  750.0  377.0   \n",
       "0            Alma Mountain Charlie   0.53   3.12   875  5.89  503.0  280.0   \n",
       "47                  Kings half way   0.46   2.89   820  6.28  543.0  284.0   \n",
       "48                  Kings half way   0.50   2.89   820  5.78  500.0  284.0   \n",
       "5    Alpine Portola to top Joaquin   0.57   3.52   801  6.18  428.0  228.0   \n",
       "6    Alpine Portola to top Joaquin   0.58   3.52   801  6.07  421.0  228.0   \n",
       "120                  Tunitas steep   0.27   1.20   599  4.44  676.0  499.0   \n",
       "119                  Tunitas steep   0.25   1.20   599  4.80  730.0  499.0   \n",
       "34                         Haskins   0.30   1.51   566  5.03  575.0  375.0   \n",
       "35                         Haskins   0.31   1.51   566  4.87  557.0  375.0   \n",
       "23   Coe Second Switchback to flat   0.22   1.00   483  4.55  669.0  483.0   \n",
       "60             Lower Redwood Gulch   0.22   1.03   474  4.68  657.0  460.0   \n",
       "8    Alpine Willowbrook to Joaquin   0.29   2.27   461  7.83  485.0  203.0   \n",
       "7    Alpine Willowbrook to Joaquin   0.28   2.27   461  8.11  502.0  203.0   \n",
       "59                   Lobitas Creek   0.20   0.96   430  4.80  655.0  448.0   \n",
       "117            Tunitas lower climb   0.22   1.30   421  5.91  583.0  324.0   \n",
       "\n",
       "      pct    kms  km_up  \n",
       "128  4.84  11.87    0.6  \n",
       "51   7.42   6.31    0.5  \n",
       "52   7.42   6.31    0.5  \n",
       "67   7.14   5.36    0.4  \n",
       "68   7.14   5.36    0.4  \n",
       "0    5.31   5.02    0.3  \n",
       "47   5.37   4.65    0.2  \n",
       "48   5.37   4.65    0.2  \n",
       "5    4.31   5.66    0.2  \n",
       "6    4.31   5.66    0.2  \n",
       "120  9.45   1.93    0.2  \n",
       "119  9.45   1.93    0.2  \n",
       "34   7.10   2.43    0.2  \n",
       "35   7.10   2.43    0.2  \n",
       "23   9.15   1.61    0.1  \n",
       "60   8.72   1.66    0.1  \n",
       "8    3.85   3.65    0.1  \n",
       "7    3.85   3.65    0.1  \n",
       "59   8.48   1.54    0.1  \n",
       "117  6.13   2.09    0.1  "
      ]
     },
     "execution_count": 110,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "top(segments, 'feet') # Biggest climbing segments"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 111,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
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       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>title</th>\n",
       "      <th>hours</th>\n",
       "      <th>miles</th>\n",
       "      <th>feet</th>\n",
       "      <th>mph</th>\n",
       "      <th>vam</th>\n",
       "      <th>fpm</th>\n",
       "      <th>pct</th>\n",
       "      <th>kms</th>\n",
       "      <th>km_up</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>84</th>\n",
       "      <td>Redwood Gulch hits</td>\n",
       "      <td>0.06</td>\n",
       "      <td>0.18</td>\n",
       "      <td>151</td>\n",
       "      <td>3.00</td>\n",
       "      <td>767.0</td>\n",
       "      <td>839.0</td>\n",
       "      <td>15.89</td>\n",
       "      <td>0.29</td>\n",
       "      <td>0.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>121</th>\n",
       "      <td>Valparaiso steep</td>\n",
       "      <td>0.04</td>\n",
       "      <td>0.18</td>\n",
       "      <td>145</td>\n",
       "      <td>4.50</td>\n",
       "      <td>1105.0</td>\n",
       "      <td>806.0</td>\n",
       "      <td>15.26</td>\n",
       "      <td>0.29</td>\n",
       "      <td>0.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>122</th>\n",
       "      <td>Valparaiso steep</td>\n",
       "      <td>0.05</td>\n",
       "      <td>0.18</td>\n",
       "      <td>145</td>\n",
       "      <td>3.60</td>\n",
       "      <td>884.0</td>\n",
       "      <td>806.0</td>\n",
       "      <td>15.26</td>\n",
       "      <td>0.29</td>\n",
       "      <td>0.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>58</th>\n",
       "      <td>Limantour steepest</td>\n",
       "      <td>0.09</td>\n",
       "      <td>0.20</td>\n",
       "      <td>159</td>\n",
       "      <td>2.22</td>\n",
       "      <td>538.0</td>\n",
       "      <td>795.0</td>\n",
       "      <td>15.06</td>\n",
       "      <td>0.32</td>\n",
       "      <td>0.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>44</th>\n",
       "      <td>Joaquin</td>\n",
       "      <td>0.10</td>\n",
       "      <td>0.33</td>\n",
       "      <td>254</td>\n",
       "      <td>3.30</td>\n",
       "      <td>774.0</td>\n",
       "      <td>770.0</td>\n",
       "      <td>14.58</td>\n",
       "      <td>0.53</td>\n",
       "      <td>0.1</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>43</th>\n",
       "      <td>Joaquin</td>\n",
       "      <td>0.09</td>\n",
       "      <td>0.33</td>\n",
       "      <td>254</td>\n",
       "      <td>3.67</td>\n",
       "      <td>860.0</td>\n",
       "      <td>770.0</td>\n",
       "      <td>14.58</td>\n",
       "      <td>0.53</td>\n",
       "      <td>0.1</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>28</th>\n",
       "      <td>Entrance Way Hill Repeats</td>\n",
       "      <td>0.02</td>\n",
       "      <td>0.10</td>\n",
       "      <td>76</td>\n",
       "      <td>5.00</td>\n",
       "      <td>1158.0</td>\n",
       "      <td>760.0</td>\n",
       "      <td>14.39</td>\n",
       "      <td>0.16</td>\n",
       "      <td>0.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>102</th>\n",
       "      <td>Stirrup Wall</td>\n",
       "      <td>0.06</td>\n",
       "      <td>0.17</td>\n",
       "      <td>125</td>\n",
       "      <td>2.83</td>\n",
       "      <td>635.0</td>\n",
       "      <td>735.0</td>\n",
       "      <td>13.93</td>\n",
       "      <td>0.27</td>\n",
       "      <td>0.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>103</th>\n",
       "      <td>Stirrup Wall</td>\n",
       "      <td>0.08</td>\n",
       "      <td>0.17</td>\n",
       "      <td>125</td>\n",
       "      <td>2.12</td>\n",
       "      <td>476.0</td>\n",
       "      <td>735.0</td>\n",
       "      <td>13.93</td>\n",
       "      <td>0.27</td>\n",
       "      <td>0.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>131</th>\n",
       "      <td>Westridge 3min</td>\n",
       "      <td>0.08</td>\n",
       "      <td>0.37</td>\n",
       "      <td>240</td>\n",
       "      <td>4.62</td>\n",
       "      <td>914.0</td>\n",
       "      <td>649.0</td>\n",
       "      <td>12.29</td>\n",
       "      <td>0.60</td>\n",
       "      <td>0.1</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>132</th>\n",
       "      <td>Westridge 3min</td>\n",
       "      <td>0.09</td>\n",
       "      <td>0.37</td>\n",
       "      <td>240</td>\n",
       "      <td>4.11</td>\n",
       "      <td>813.0</td>\n",
       "      <td>649.0</td>\n",
       "      <td>12.29</td>\n",
       "      <td>0.60</td>\n",
       "      <td>0.1</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>57</th>\n",
       "      <td>Limantour Spit</td>\n",
       "      <td>0.09</td>\n",
       "      <td>0.47</td>\n",
       "      <td>303</td>\n",
       "      <td>5.22</td>\n",
       "      <td>1026.0</td>\n",
       "      <td>645.0</td>\n",
       "      <td>12.21</td>\n",
       "      <td>0.76</td>\n",
       "      <td>0.1</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>55</th>\n",
       "      <td>Klamath Dr.</td>\n",
       "      <td>0.02</td>\n",
       "      <td>0.12</td>\n",
       "      <td>77</td>\n",
       "      <td>6.00</td>\n",
       "      <td>1173.0</td>\n",
       "      <td>642.0</td>\n",
       "      <td>12.15</td>\n",
       "      <td>0.19</td>\n",
       "      <td>0.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>33</th>\n",
       "      <td>green valley kicker</td>\n",
       "      <td>0.08</td>\n",
       "      <td>0.29</td>\n",
       "      <td>178</td>\n",
       "      <td>3.62</td>\n",
       "      <td>678.0</td>\n",
       "      <td>614.0</td>\n",
       "      <td>11.62</td>\n",
       "      <td>0.47</td>\n",
       "      <td>0.1</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>85</th>\n",
       "      <td>Redwood Gulch wall</td>\n",
       "      <td>0.11</td>\n",
       "      <td>0.43</td>\n",
       "      <td>258</td>\n",
       "      <td>3.91</td>\n",
       "      <td>715.0</td>\n",
       "      <td>600.0</td>\n",
       "      <td>11.36</td>\n",
       "      <td>0.69</td>\n",
       "      <td>0.1</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>71</th>\n",
       "      <td>Paloma Climb</td>\n",
       "      <td>0.02</td>\n",
       "      <td>0.14</td>\n",
       "      <td>82</td>\n",
       "      <td>7.00</td>\n",
       "      <td>1250.0</td>\n",
       "      <td>586.0</td>\n",
       "      <td>11.09</td>\n",
       "      <td>0.23</td>\n",
       "      <td>0.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>112</th>\n",
       "      <td>Try not to fall back</td>\n",
       "      <td>0.21</td>\n",
       "      <td>0.71</td>\n",
       "      <td>410</td>\n",
       "      <td>3.38</td>\n",
       "      <td>595.0</td>\n",
       "      <td>577.0</td>\n",
       "      <td>10.94</td>\n",
       "      <td>1.14</td>\n",
       "      <td>0.1</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>129</th>\n",
       "      <td>Westridge</td>\n",
       "      <td>0.14</td>\n",
       "      <td>0.68</td>\n",
       "      <td>385</td>\n",
       "      <td>4.86</td>\n",
       "      <td>838.0</td>\n",
       "      <td>566.0</td>\n",
       "      <td>10.72</td>\n",
       "      <td>1.09</td>\n",
       "      <td>0.1</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>130</th>\n",
       "      <td>Westridge</td>\n",
       "      <td>0.16</td>\n",
       "      <td>0.68</td>\n",
       "      <td>385</td>\n",
       "      <td>4.25</td>\n",
       "      <td>733.0</td>\n",
       "      <td>566.0</td>\n",
       "      <td>10.72</td>\n",
       "      <td>1.09</td>\n",
       "      <td>0.1</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>95</th>\n",
       "      <td>Stair Step</td>\n",
       "      <td>0.09</td>\n",
       "      <td>0.32</td>\n",
       "      <td>175</td>\n",
       "      <td>3.56</td>\n",
       "      <td>593.0</td>\n",
       "      <td>547.0</td>\n",
       "      <td>10.36</td>\n",
       "      <td>0.51</td>\n",
       "      <td>0.1</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "                         title  hours  miles  feet   mph     vam    fpm  \\\n",
       "84          Redwood Gulch hits   0.06   0.18   151  3.00   767.0  839.0   \n",
       "121           Valparaiso steep   0.04   0.18   145  4.50  1105.0  806.0   \n",
       "122           Valparaiso steep   0.05   0.18   145  3.60   884.0  806.0   \n",
       "58          Limantour steepest   0.09   0.20   159  2.22   538.0  795.0   \n",
       "44                     Joaquin   0.10   0.33   254  3.30   774.0  770.0   \n",
       "43                     Joaquin   0.09   0.33   254  3.67   860.0  770.0   \n",
       "28   Entrance Way Hill Repeats   0.02   0.10    76  5.00  1158.0  760.0   \n",
       "102               Stirrup Wall   0.06   0.17   125  2.83   635.0  735.0   \n",
       "103               Stirrup Wall   0.08   0.17   125  2.12   476.0  735.0   \n",
       "131             Westridge 3min   0.08   0.37   240  4.62   914.0  649.0   \n",
       "132             Westridge 3min   0.09   0.37   240  4.11   813.0  649.0   \n",
       "57              Limantour Spit   0.09   0.47   303  5.22  1026.0  645.0   \n",
       "55                 Klamath Dr.   0.02   0.12    77  6.00  1173.0  642.0   \n",
       "33         green valley kicker   0.08   0.29   178  3.62   678.0  614.0   \n",
       "85          Redwood Gulch wall   0.11   0.43   258  3.91   715.0  600.0   \n",
       "71                Paloma Climb   0.02   0.14    82  7.00  1250.0  586.0   \n",
       "112       Try not to fall back   0.21   0.71   410  3.38   595.0  577.0   \n",
       "129                  Westridge   0.14   0.68   385  4.86   838.0  566.0   \n",
       "130                  Westridge   0.16   0.68   385  4.25   733.0  566.0   \n",
       "95                  Stair Step   0.09   0.32   175  3.56   593.0  547.0   \n",
       "\n",
       "       pct   kms  km_up  \n",
       "84   15.89  0.29    0.0  \n",
       "121  15.26  0.29    0.0  \n",
       "122  15.26  0.29    0.0  \n",
       "58   15.06  0.32    0.0  \n",
       "44   14.58  0.53    0.1  \n",
       "43   14.58  0.53    0.1  \n",
       "28   14.39  0.16    0.0  \n",
       "102  13.93  0.27    0.0  \n",
       "103  13.93  0.27    0.0  \n",
       "131  12.29  0.60    0.1  \n",
       "132  12.29  0.60    0.1  \n",
       "57   12.21  0.76    0.1  \n",
       "55   12.15  0.19    0.0  \n",
       "33   11.62  0.47    0.1  \n",
       "85   11.36  0.69    0.1  \n",
       "71   11.09  0.23    0.0  \n",
       "112  10.94  1.14    0.1  \n",
       "129  10.72  1.09    0.1  \n",
       "130  10.72  1.09    0.1  \n",
       "95   10.36  0.51    0.1  "
      ]
     },
     "execution_count": 111,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "top(segments, 'pct') # Steepest climbs"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 112,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
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       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>date</th>\n",
       "      <th>year</th>\n",
       "      <th>title</th>\n",
       "      <th>hours</th>\n",
       "      <th>miles</th>\n",
       "      <th>feet</th>\n",
       "      <th>mph</th>\n",
       "      <th>vam</th>\n",
       "      <th>fpm</th>\n",
       "      <th>pct</th>\n",
       "      <th>kms</th>\n",
       "      <th>km_up</th>\n",
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       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th></th>\n",
       "      <td>Fri, 1/9</td>\n",
       "      <td>2012</td>\n",
       "      <td>Otago Rail Trail Century</td>\n",
       "      <td>7.87</td>\n",
       "      <td>102.41</td>\n",
       "      <td>2286</td>\n",
       "      <td>13.01</td>\n",
       "      <td>89.0</td>\n",
       "      <td>22.0</td>\n",
       "      <td>0.42</td>\n",
       "      <td>164.78</td>\n",
       "      <td>0.7</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th></th>\n",
       "      <td>Sat, 5/7</td>\n",
       "      <td>2022</td>\n",
       "      <td>Wine Country Century</td>\n",
       "      <td>6.65</td>\n",
       "      <td>100.26</td>\n",
       "      <td>5253</td>\n",
       "      <td>15.08</td>\n",
       "      <td>241.0</td>\n",
       "      <td>52.0</td>\n",
       "      <td>0.99</td>\n",
       "      <td>161.32</td>\n",
       "      <td>1.6</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th></th>\n",
       "      <td>Thu, 6/14</td>\n",
       "      <td>2012</td>\n",
       "      <td>Coyote Creek Century with Juliet</td>\n",
       "      <td>8.14</td>\n",
       "      <td>100.07</td>\n",
       "      <td>1513</td>\n",
       "      <td>12.29</td>\n",
       "      <td>57.0</td>\n",
       "      <td>15.0</td>\n",
       "      <td>0.29</td>\n",
       "      <td>161.01</td>\n",
       "      <td>0.5</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th></th>\n",
       "      <td>Sat, 5/13</td>\n",
       "      <td>2017</td>\n",
       "      <td>Morgan Hill iCare Classic</td>\n",
       "      <td>7.46</td>\n",
       "      <td>100.05</td>\n",
       "      <td>4596</td>\n",
       "      <td>13.41</td>\n",
       "      <td>188.0</td>\n",
       "      <td>46.0</td>\n",
       "      <td>0.87</td>\n",
       "      <td>160.98</td>\n",
       "      <td>1.4</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th></th>\n",
       "      <td>Sat, 5/12</td>\n",
       "      <td>2018</td>\n",
       "      <td>ICare Classic, Morgan Hill</td>\n",
       "      <td>6.80</td>\n",
       "      <td>91.29</td>\n",
       "      <td>4160</td>\n",
       "      <td>13.42</td>\n",
       "      <td>186.0</td>\n",
       "      <td>46.0</td>\n",
       "      <td>0.86</td>\n",
       "      <td>146.89</td>\n",
       "      <td>1.3</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th></th>\n",
       "      <td>Sat, 5/6</td>\n",
       "      <td>2017</td>\n",
       "      <td>Wine Country Century</td>\n",
       "      <td>7.26</td>\n",
       "      <td>89.49</td>\n",
       "      <td>5246</td>\n",
       "      <td>12.33</td>\n",
       "      <td>220.0</td>\n",
       "      <td>59.0</td>\n",
       "      <td>1.11</td>\n",
       "      <td>143.99</td>\n",
       "      <td>1.6</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th></th>\n",
       "      <td>Fri, 8/10</td>\n",
       "      <td>2018</td>\n",
       "      <td>Bike Ride Northwest Day 6</td>\n",
       "      <td>6.24</td>\n",
       "      <td>84.70</td>\n",
       "      <td>4380</td>\n",
       "      <td>13.57</td>\n",
       "      <td>214.0</td>\n",
       "      <td>52.0</td>\n",
       "      <td>0.98</td>\n",
       "      <td>136.28</td>\n",
       "      <td>1.3</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th></th>\n",
       "      <td>Fri, 2/28</td>\n",
       "      <td>2020</td>\n",
       "      <td>Sawyer Camp Trail</td>\n",
       "      <td>6.41</td>\n",
       "      <td>84.43</td>\n",
       "      <td>3448</td>\n",
       "      <td>13.17</td>\n",
       "      <td>164.0</td>\n",
       "      <td>41.0</td>\n",
       "      <td>0.77</td>\n",
       "      <td>135.85</td>\n",
       "      <td>1.1</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th></th>\n",
       "      <td>Wed, 6/7</td>\n",
       "      <td>2023</td>\n",
       "      <td>Los Altos</td>\n",
       "      <td>7.05</td>\n",
       "      <td>81.54</td>\n",
       "      <td>2110</td>\n",
       "      <td>11.57</td>\n",
       "      <td>91.0</td>\n",
       "      <td>26.0</td>\n",
       "      <td>0.49</td>\n",
       "      <td>131.20</td>\n",
       "      <td>0.6</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th></th>\n",
       "      <td>Sun, 8/30</td>\n",
       "      <td>2020</td>\n",
       "      <td>Los Gatos</td>\n",
       "      <td>6.36</td>\n",
       "      <td>80.92</td>\n",
       "      <td>2100</td>\n",
       "      <td>12.72</td>\n",
       "      <td>101.0</td>\n",
       "      <td>26.0</td>\n",
       "      <td>0.49</td>\n",
       "      <td>130.20</td>\n",
       "      <td>0.6</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th></th>\n",
       "      <td>Sat, 9/17</td>\n",
       "      <td>2022</td>\n",
       "      <td>San Gregorio / Tunitas</td>\n",
       "      <td>6.56</td>\n",
       "      <td>80.53</td>\n",
       "      <td>6015</td>\n",
       "      <td>12.28</td>\n",
       "      <td>279.0</td>\n",
       "      <td>75.0</td>\n",
       "      <td>1.41</td>\n",
       "      <td>129.57</td>\n",
       "      <td>1.8</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th></th>\n",
       "      <td>Sat, 10/1</td>\n",
       "      <td>2016</td>\n",
       "      <td>Half Moon Bay overnight campout</td>\n",
       "      <td>7.51</td>\n",
       "      <td>80.07</td>\n",
       "      <td>6039</td>\n",
       "      <td>10.66</td>\n",
       "      <td>245.0</td>\n",
       "      <td>75.0</td>\n",
       "      <td>1.43</td>\n",
       "      <td>128.83</td>\n",
       "      <td>1.8</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th></th>\n",
       "      <td>Mon, 10/5</td>\n",
       "      <td>2020</td>\n",
       "      <td>Half way around the bay on bay trail</td>\n",
       "      <td>6.44</td>\n",
       "      <td>80.05</td>\n",
       "      <td>541</td>\n",
       "      <td>12.43</td>\n",
       "      <td>26.0</td>\n",
       "      <td>7.0</td>\n",
       "      <td>0.13</td>\n",
       "      <td>128.80</td>\n",
       "      <td>0.2</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th></th>\n",
       "      <td>Sun, 6/21</td>\n",
       "      <td>2020</td>\n",
       "      <td>Sawyer Camp Trail</td>\n",
       "      <td>6.59</td>\n",
       "      <td>79.78</td>\n",
       "      <td>1738</td>\n",
       "      <td>12.11</td>\n",
       "      <td>80.0</td>\n",
       "      <td>22.0</td>\n",
       "      <td>0.41</td>\n",
       "      <td>128.37</td>\n",
       "      <td>0.5</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th></th>\n",
       "      <td>Thu, 1/5</td>\n",
       "      <td>2012</td>\n",
       "      <td>Tekapo Lake to Omarama New Zealand</td>\n",
       "      <td>5.46</td>\n",
       "      <td>79.42</td>\n",
       "      <td>2145</td>\n",
       "      <td>14.55</td>\n",
       "      <td>120.0</td>\n",
       "      <td>27.0</td>\n",
       "      <td>0.51</td>\n",
       "      <td>127.79</td>\n",
       "      <td>0.7</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th></th>\n",
       "      <td>Tue, 8/7</td>\n",
       "      <td>2018</td>\n",
       "      <td>Bike Ride Northwest Day 3</td>\n",
       "      <td>6.18</td>\n",
       "      <td>78.96</td>\n",
       "      <td>5092</td>\n",
       "      <td>12.78</td>\n",
       "      <td>251.0</td>\n",
       "      <td>64.0</td>\n",
       "      <td>1.22</td>\n",
       "      <td>127.05</td>\n",
       "      <td>1.6</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th></th>\n",
       "      <td>Sun, 6/15</td>\n",
       "      <td>2014</td>\n",
       "      <td>Sierra to the Sea Day 1</td>\n",
       "      <td>5.57</td>\n",
       "      <td>78.53</td>\n",
       "      <td>4777</td>\n",
       "      <td>14.10</td>\n",
       "      <td>261.0</td>\n",
       "      <td>61.0</td>\n",
       "      <td>1.15</td>\n",
       "      <td>126.35</td>\n",
       "      <td>1.5</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th></th>\n",
       "      <td>Sun, 2/7</td>\n",
       "      <td>2021</td>\n",
       "      <td>Saratoga / Campbell</td>\n",
       "      <td>5.89</td>\n",
       "      <td>78.38</td>\n",
       "      <td>2270</td>\n",
       "      <td>13.31</td>\n",
       "      <td>117.0</td>\n",
       "      <td>29.0</td>\n",
       "      <td>0.55</td>\n",
       "      <td>126.11</td>\n",
       "      <td>0.7</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th></th>\n",
       "      <td>Sat, 7/2</td>\n",
       "      <td>2022</td>\n",
       "      <td>Bear Gulch, West Side</td>\n",
       "      <td>6.49</td>\n",
       "      <td>77.73</td>\n",
       "      <td>6991</td>\n",
       "      <td>11.98</td>\n",
       "      <td>328.0</td>\n",
       "      <td>90.0</td>\n",
       "      <td>1.70</td>\n",
       "      <td>125.07</td>\n",
       "      <td>2.1</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th></th>\n",
       "      <td>Sun, 6/2</td>\n",
       "      <td>2019</td>\n",
       "      <td>The Sequoia</td>\n",
       "      <td>6.68</td>\n",
       "      <td>77.51</td>\n",
       "      <td>6467</td>\n",
       "      <td>11.60</td>\n",
       "      <td>295.0</td>\n",
       "      <td>83.0</td>\n",
       "      <td>1.58</td>\n",
       "      <td>124.71</td>\n",
       "      <td>2.0</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "       date  year                                 title  hours   miles  feet  \\\n",
       "   Fri, 1/9  2012              Otago Rail Trail Century   7.87  102.41  2286   \n",
       "   Sat, 5/7  2022                  Wine Country Century   6.65  100.26  5253   \n",
       "  Thu, 6/14  2012      Coyote Creek Century with Juliet   8.14  100.07  1513   \n",
       "  Sat, 5/13  2017             Morgan Hill iCare Classic   7.46  100.05  4596   \n",
       "  Sat, 5/12  2018            ICare Classic, Morgan Hill   6.80   91.29  4160   \n",
       "   Sat, 5/6  2017                  Wine Country Century   7.26   89.49  5246   \n",
       "  Fri, 8/10  2018             Bike Ride Northwest Day 6   6.24   84.70  4380   \n",
       "  Fri, 2/28  2020                     Sawyer Camp Trail   6.41   84.43  3448   \n",
       "   Wed, 6/7  2023                             Los Altos   7.05   81.54  2110   \n",
       "  Sun, 8/30  2020                             Los Gatos   6.36   80.92  2100   \n",
       "  Sat, 9/17  2022                San Gregorio / Tunitas   6.56   80.53  6015   \n",
       "  Sat, 10/1  2016       Half Moon Bay overnight campout   7.51   80.07  6039   \n",
       "  Mon, 10/5  2020  Half way around the bay on bay trail   6.44   80.05   541   \n",
       "  Sun, 6/21  2020                     Sawyer Camp Trail   6.59   79.78  1738   \n",
       "   Thu, 1/5  2012    Tekapo Lake to Omarama New Zealand   5.46   79.42  2145   \n",
       "   Tue, 8/7  2018             Bike Ride Northwest Day 3   6.18   78.96  5092   \n",
       "  Sun, 6/15  2014               Sierra to the Sea Day 1   5.57   78.53  4777   \n",
       "   Sun, 2/7  2021                   Saratoga / Campbell   5.89   78.38  2270   \n",
       "   Sat, 7/2  2022                 Bear Gulch, West Side   6.49   77.73  6991   \n",
       "   Sun, 6/2  2019                           The Sequoia   6.68   77.51  6467   \n",
       "\n",
       "    mph    vam   fpm   pct     kms  km_up  \n",
       "  13.01   89.0  22.0  0.42  164.78    0.7  \n",
       "  15.08  241.0  52.0  0.99  161.32    1.6  \n",
       "  12.29   57.0  15.0  0.29  161.01    0.5  \n",
       "  13.41  188.0  46.0  0.87  160.98    1.4  \n",
       "  13.42  186.0  46.0  0.86  146.89    1.3  \n",
       "  12.33  220.0  59.0  1.11  143.99    1.6  \n",
       "  13.57  214.0  52.0  0.98  136.28    1.3  \n",
       "  13.17  164.0  41.0  0.77  135.85    1.1  \n",
       "  11.57   91.0  26.0  0.49  131.20    0.6  \n",
       "  12.72  101.0  26.0  0.49  130.20    0.6  \n",
       "  12.28  279.0  75.0  1.41  129.57    1.8  \n",
       "  10.66  245.0  75.0  1.43  128.83    1.8  \n",
       "  12.43   26.0   7.0  0.13  128.80    0.2  \n",
       "  12.11   80.0  22.0  0.41  128.37    0.5  \n",
       "  14.55  120.0  27.0  0.51  127.79    0.7  \n",
       "  12.78  251.0  64.0  1.22  127.05    1.6  \n",
       "  14.10  261.0  61.0  1.15  126.35    1.5  \n",
       "  13.31  117.0  29.0  0.55  126.11    0.7  \n",
       "  11.98  328.0  90.0  1.70  125.07    2.1  \n",
       "  11.60  295.0  83.0  1.58  124.71    2.0  "
      ]
     },
     "execution_count": 112,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "top(rides, 'miles') # Longest rides"
   ]
  }
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