{ "cells": [ { "cell_type": "markdown", "metadata": {}, "source": [ "
Peter Norvig, Oct 2017
Last update: Jan 2024
\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. In this notebook I track [my cycling performance](https://www.strava.com/athletes/575579) against 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 68 miles or more on 68 different days. So 68 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 the total **hours** on the bike, distance traveled in **miles**, and total **feet** climbed. Then there are some columns that are dervided from these: **mph** is **miles / hour**; **vam** is vertical meters ascended per hour (or **feet × 0.3048 / hours**); **fpmi** is **feet / miles**; **pct** is the grade in percent (or **feet × 100 / miles / 5280**), and finally **kms** and **meters** are the metric equivalents of **miles** and **feet**.\n" ] }, { "cell_type": "code", "execution_count": 1, "metadata": {}, "outputs": [ { "data": { "text/html": [ "
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yearhoursmilesfeetmphvamfpmipctkmsmeters
2023541.68631624310011.66137.038.00.7310162.4474097.0
2022532.93602836232311.31207.060.01.149699.05110436.0
2021490.53606419663412.36122.032.00.619756.9859934.0
2020438.8853419477712.1766.018.00.348593.6728888.0
2019476.32601614979712.6396.025.00.479679.7445658.0
2018475.93610115864212.82102.026.00.499816.5148354.0
2017567.33735620209612.97109.027.00.5211835.8061599.0
2016486.38633920145313.03126.032.00.6010199.4561403.0
2015419.95545220985912.98152.038.00.738772.2763965.0
2014191.03246911848112.92189.048.00.913972.6236113.0
\n", "
" ], "text/plain": [ " year hours miles feet mph vam fpmi pct kms meters\n", " 2023 541.68 6316 243100 11.66 137.0 38.0 0.73 10162.44 74097.0\n", " 2022 532.93 6028 362323 11.31 207.0 60.0 1.14 9699.05 110436.0\n", " 2021 490.53 6064 196634 12.36 122.0 32.0 0.61 9756.98 59934.0\n", " 2020 438.88 5341 94777 12.17 66.0 18.0 0.34 8593.67 28888.0\n", " 2019 476.32 6016 149797 12.63 96.0 25.0 0.47 9679.74 45658.0\n", " 2018 475.93 6101 158642 12.82 102.0 26.0 0.49 9816.51 48354.0\n", " 2017 567.33 7356 202096 12.97 109.0 27.0 0.52 11835.80 61599.0\n", " 2016 486.38 6339 201453 13.03 126.0 32.0 0.60 10199.45 61403.0\n", " 2015 419.95 5452 209859 12.98 152.0 38.0 0.73 8772.27 63965.0\n", " 2014 191.03 2469 118481 12.92 189.0 48.0 0.91 3972.62 36113.0" ] }, "execution_count": 1, "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 per day basis, assuming I ride 6 days a week:" ] }, { "cell_type": "code", "execution_count": 2, "metadata": {}, "outputs": [ { "data": { "text/html": [ "
\n", "\n", "\n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", "
yearhoursmilesfeetmphvamfpmipctkmsmeters
20231.720.2779.211.66137.038.00.7332.6237.5
20221.719.31161.311.31207.060.01.1431.1354.0
20211.619.4630.212.36122.032.00.6131.3192.1
20201.417.1303.812.1766.018.00.3427.592.6
20191.519.3480.112.6396.025.00.4731.0146.3
20181.519.6508.512.82102.026.00.4931.5155.0
20171.823.6647.712.97109.027.00.5237.9197.4
20161.620.3645.713.03126.032.00.6032.7196.8
20151.317.5672.612.98152.038.00.7328.1205.0
20140.67.9379.712.92189.048.00.9112.7115.7
\n", "
" ], "text/plain": [ " year hours miles feet mph vam fpmi pct kms meters\n", " 2023 1.7 20.2 779.2 11.66 137.0 38.0 0.73 32.6 237.5\n", " 2022 1.7 19.3 1161.3 11.31 207.0 60.0 1.14 31.1 354.0\n", " 2021 1.6 19.4 630.2 12.36 122.0 32.0 0.61 31.3 192.1\n", " 2020 1.4 17.1 303.8 12.17 66.0 18.0 0.34 27.5 92.6\n", " 2019 1.5 19.3 480.1 12.63 96.0 25.0 0.47 31.0 146.3\n", " 2018 1.5 19.6 508.5 12.82 102.0 26.0 0.49 31.5 155.0\n", " 2017 1.8 23.6 647.7 12.97 109.0 27.0 0.52 37.9 197.4\n", " 2016 1.6 20.3 645.7 13.03 126.0 32.0 0.60 32.7 196.8\n", " 2015 1.3 17.5 672.6 12.98 152.0 38.0 0.73 28.1 205.0\n", " 2014 0.6 7.9 379.7 12.92 189.0 48.0 0.91 12.7 115.7" ] }, "execution_count": 2, "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 the [Kármán line](https://en.wikipedia.org/wiki/K%C3%A1rm%C3%A1n_line) is 100 kilometers; in 2022 I surpassed 100 kilometers of climbing (over 1,100 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), [Statshunter](https://www.statshunters.com/), [RideEveryTile](https://rideeverytile.com/), and [SquadRats](https://squadrats.com/map) 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 tiles). \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 into my main cluster (such as connecting San Francisco and Marin). I have a [separate page](???) documenting my explorations, but here are a few key points along the way:" ] }, { "cell_type": "code", "execution_count": 3, "metadata": {}, "outputs": [ { "data": { "text/html": [ "\n", "\n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", "
 datesquareclustertotalcomment
04/28/20241412753382Livermore
02/25/20241411963279Expanding through Santa Cruz and to the South
01/01/20241410563105Start of this year
12/08/20231410423084Benicia ride connects East Bay and Napa clusters
11/05/2023149322914Alum Rock ride gets 14x14 max square
06/30/2023136892640Rides in east Bay fill in holes
04/14/2023136302595Black Sands Beach low-tide hike connects Marin to max cluster
03/04/2023135832574Almaden rides connects Gilroy to max cluster
10/22/2022133962495Alviso levees to get to 13x13 max square
10/16/2022123932492Milpitas ride connects East Bay to max cluster
09/08/2022113002487First started tracking tiles
\n" ], "text/plain": [ "" ] }, "execution_count": 3, "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 percent of roads/trails that I have traveled on for each place (specified by **county** and city **name**), as well as the **total** miles of road in the place, the miles I have **done**, and the amount I need to hit the **next badge**. " ] }, { "cell_type": "code", "execution_count": 4, "metadata": {}, "outputs": [ { "data": { "text/html": [ "
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pctcountynametotaldoneto next badge
100.0%SMCLos Trancos Woods5.35.3
100.0%SMCLos Trancos OSP0.30.3
100.0%SMCLadera8.18.1
100.0%SMCKensington Square0.60.6
100.0%SMCMenlo Oaks3.53.5
100.0%SMCNorth Fair Oaks26.727
100.0%SMCWest Menlo Park11.211
100.0%SMCSequoia Tract11.011
99.9%SCCLoyola18.318
99.9%SMCPalomar Park4.04.0
99.9%SMCEmerald Lake Hills24.625
99.8%SMCAtherton56.356
99.8%SMCWindy Hill Preserve4.14.1
99.7%SMCEast Palo Alto48.348
99.7%SMCMenlo Park139.5139
99.6%SMCSky Londa11.812
99.6%SCCLos Altos138.2138
99.5%SMCPortola Valley48.248
99.4%SMCWoodside75.275
99.3%SCCMountain View208.1207
99.3%SMCRedwood City240.5239
99.2%SCCLos Altos Hills91.391
99.2%SMCSan Carlos99.098
99.0%SCCPalo Alto297.2294
93.5%SMCSan Mateo Highlands18.0171.0 mi to 99%
90.9%SMCBurleigh Murray Park2.11.90.2 mi to 99%
90.4%SMCFoster City150.013613 mi to 99%
86.8%SCCFoothills Preserve1.11.00.0 mi to 90%
76.4%SMCSkyline Ridge OSP0.80.60.1 mi to 90%
74.1%SCCSan Francisco Bay Trail260.819341 mi to 90%
73.2%CCCRosie Riveter Park5.54.00.9 mi to 90%
71.5%SMCBurlingame Hills6.04.31.1 mi to 90%
66.7%SMCCoal Creek Preserve3.92.60.9 mi to 90%
63.5%---San Mateo County2814.01,787746 mi to 90%
59.5%SMCRussian Ridge Preserve12.27.33.7 mi to 90%
59.3%SMCMontara27.8168.5 mi to 90%
56.2%SMCBurlingame88.45030 mi to 90%
54.7%SMCBelmont98.15435 mi to 90%
53.3%SCCSunnyvale357.0190131 mi to 90%
52.8%SCCCupertino172.09164 mi to 90%
52.4%SCCMonte Sereno20.4117.7 mi to 90%
52.3%SMCHillsborough85.34532 mi to 90%
51.8%SMCSan Mateo256.013398 mi to 90%
51.5%SMCHalf Moon Bay State Beach4.42.31.7 mi to 90%
51.2%SMCLong Ridge Preserve11.05.64.3 mi to 90%
51.2%SCCCastle Rock State Park11.25.74.3 mi to 90%
51.0%ALANewark147.07557 mi to 90%
50.4%SCCSaratoga180.09171 mi to 90%
50.2%SMCBrisbane40.92116 mi to 90%
47.7%SCCEdenvale30.0140.7 mi to 50%
47.3%NSWBarangaroo1.70.80.0 mi to 50%
47.2%SCCGardner23.4110.7 mi to 50%
43.9%SFCPresidio Terrace2.81.20.2 mi to 50%
43.6%SMCEl Granada49.2213.1 mi to 50%
43.6%SMCMoss Beach19.78.61.3 mi to 50%
43.3%ALAHayward Acres3.51.50.2 mi to 50%
42.6%SMCMillbrae65.0284.8 mi to 50%
40.8%ALASan Lorenzo55.5235.1 mi to 50%
39.6%SFCLincoln Park4.51.80.5 mi to 50%
39.5%SCCCommunications Hill27.8112.9 mi to 50%
39.0%SMCPurisima Creek Preserve16.56.41.8 mi to 50%
38.9%SMCColma13.75.31.5 mi to 50%
38.7%MARMt Tamalpais State Park31.7123.6 mi to 50%
38.2%SMCBroadmoor8.83.41.0 mi to 50%
37.4%SFCSouth Beach4.81.80.6 mi to 50%
37.1%MARMuir Beach4.61.70.6 mi to 50%
36.8%SCCSpartan Keyes64.3248.5 mi to 50%
36.8%SFCLake Street3.91.40.5 mi to 50%
36.7%SCCMilpitas224.08230 mi to 50%
36.1%ALAAshland35.1134.9 mi to 50%
36.0%SCCWillow Glen81.62911 mi to 50%
34.8%SCCSanta Clara348.012153 mi to 50%
34.7%MASMIT9.63.31.5 mi to 50%
34.3%NSWMillers Point3.21.10.5 mi to 50%
33.7%SCCParkview42.5146.9 mi to 50%
33.6%SMCHalf Moon Bay68.02311 mi to 50%
33.6%SCCLos Gatos148.05024 mi to 50%
33.2%SMCPacifica150.95025 mi to 50%
33.0%SCCSeven Trees40.9137.0 mi to 50%
33.0%---Santa Clara County7569.02,4981,287 mi to 50%
32.9%ALAFremont780.2257133 mi to 50%
32.9%ALAUnion City208.86936 mi to 50%
32.9%MARStinson Beach11.23.71.9 mi to 50%
32.7%ALAHayward444.514577 mi to 50%
32.7%SCCBranham44.0147.6 mi to 50%
31.9%MARMarin Headlands GGNRA65.72112 mi to 50%
31.5%SCCSan Martin35.3116.5 mi to 50%
31.0%SMCSan Bruno114.03522 mi to 50%
30.9%SCCWillow Glen South63.32012 mi to 50%
30.7%SCCForest of Nisene Marks SP44.0148.5 mi to 50%
30.1%SMCButano State Park15.24.63.0 mi to 50%
29.6%SMCSouth San Francisco185.35538 mi to 50%
29.4%SFCGolden Gate Park40.8128.4 mi to 50%
29.3%SFCSeacliff4.11.20.8 mi to 50%
29.3%SCCCampbell119.03525 mi to 50%
29.2%NSWDawes Point1.80.50.4 mi to 50%
28.2%ALAFairview34.49.77.5 mi to 50%
28.0%SCCSan Jose2618.7733576 mi to 50%
27.8%ALACherryland20.95.84.6 mi to 50%
27.7%ALASan Leandro230.66451 mi to 50%
27.4%SMCDaly City148.14133 mi to 50%
26.8%CALMokelumne Hill14.73.93.4 mi to 50%
26.7%SFCPresidio National Park43.51210 mi to 50%
26.4%SCCGilroy188.95045 mi to 50%
26.1%ALACastro Valley192.55046 mi to 50%
25.6%SMCBay Area Ridge Trail395.610197 mi to 50%
23.6%SONGuerneville22.75.40.3 mi to 25%
21.6%SFCPresidio Heights6.51.40.2 mi to 25%
20.6%SFCPanhandle7.31.50.3 mi to 25%
18.2%SFCBalboa Terrace3.40.60.2 mi to 25%
18.2%SFCPolk Gulch4.00.70.3 mi to 25%
18.0%SFCCole Valley1.70.30.1 mi to 25%
17.8%SONHealdsburg53.79.63.9 mi to 25%
17.0%SONBodega Bay28.94.92.3 mi to 25%
16.6%---Alameda County5818.0965490 mi to 25%
15.9%SFCForest Hill6.11.00.6 mi to 25%
15.5%SFCNorthern Waterfront5.60.90.5 mi to 25%
15.4%SFCAquatic Park Fort Mason6.41.00.6 mi to 25%
15.2%SFCLittle Hollywood3.70.60.4 mi to 25%
14.2%SFCClarendon Heights6.00.90.6 mi to 25%
13.8%SFCFisherman's Wharf6.20.90.7 mi to 25%
13.2%SFCSutro Heights7.10.90.8 mi to 25%
13.0%SFCAshbury Heights3.70.50.4 mi to 25%
12.9%MARCorte Madera51.06.66.2 mi to 25%
12.9%MARSausalito32.74.24.0 mi to 25%
12.3%SFCDogpatch5.10.60.6 mi to 25%
12.2%ALAAlameda206.72526 mi to 25%
11.9%SFCCow Hollow12.01.41.6 mi to 25%
10.9%---Marin County2333.0255328 mi to 25%
10.7%SFCPacific Heights18.01.92.6 mi to 25%
10.7%SFCGolden Gate Heights17.81.92.5 mi to 25%
10.2%SFCFinancial District9.41.01.4 mi to 25%
9.3%---San Francisco County1217.0113192 mi to 25%
9.1%MARMill Valley92.28.415 mi to 25%
8.9%---Napa County1609.0143259 mi to 25%
8.6%SFCMission Bay13.81.22.3 mi to 25%
7.7%ALAEmeryville28.12.24.9 mi to 25%
7.6%ALABerkeley260.32045 mi to 25%
7.1%---Santa Cruz County2718.0194486 mi to 25%
6.8%ALAAlbany42.72.97.8 mi to 25%
6.2%MASCambridge180.81134 mi to 25%
6.0%SFCCentral Waterfront10.20.61.9 mi to 25%
5.1%---Sonoma County4895.0251973 mi to 25%
3.8%---Contra Costa County5945.02261,260 mi to 25%
3.7%MARSan Rafael260.09.655 mi to 25%
1.8%---California377037.06,719822 mi to 2%
0.113%---USA6406754.07,2675,546 mi to 0.2%
0.017%---Earth41974536.07,1591,236 mi to 0.02%
\n", "
" ], "text/plain": [ " pct county name total done \\\n", " 100.0% SMC Los Trancos Woods 5.3 5.3 \n", " 100.0% SMC Los Trancos OSP 0.3 0.3 \n", " 100.0% SMC Ladera 8.1 8.1 \n", " 100.0% SMC Kensington Square 0.6 0.6 \n", " 100.0% SMC Menlo Oaks 3.5 3.5 \n", " 100.0% SMC North Fair Oaks 26.7 27 \n", " 100.0% SMC West Menlo Park 11.2 11 \n", " 100.0% SMC Sequoia Tract 11.0 11 \n", " 99.9% SCC Loyola 18.3 18 \n", " 99.9% SMC Palomar Park 4.0 4.0 \n", " 99.9% SMC Emerald Lake Hills 24.6 25 \n", " 99.8% SMC Atherton 56.3 56 \n", " 99.8% SMC Windy Hill Preserve 4.1 4.1 \n", " 99.7% SMC East Palo Alto 48.3 48 \n", " 99.7% SMC Menlo Park 139.5 139 \n", " 99.6% SMC Sky Londa 11.8 12 \n", " 99.6% SCC Los Altos 138.2 138 \n", " 99.5% SMC Portola Valley 48.2 48 \n", " 99.4% SMC Woodside 75.2 75 \n", " 99.3% SCC Mountain View 208.1 207 \n", " 99.3% SMC Redwood City 240.5 239 \n", " 99.2% SCC Los Altos Hills 91.3 91 \n", " 99.2% SMC San Carlos 99.0 98 \n", " 99.0% SCC Palo Alto 297.2 294 \n", " 93.5% SMC San Mateo Highlands 18.0 17 \n", " 90.9% SMC Burleigh Murray Park 2.1 1.9 \n", " 90.4% SMC Foster City 150.0 136 \n", " 86.8% SCC Foothills Preserve 1.1 1.0 \n", " 76.4% SMC Skyline Ridge OSP 0.8 0.6 \n", " 74.1% SCC San Francisco Bay Trail 260.8 193 \n", " 73.2% CCC Rosie Riveter Park 5.5 4.0 \n", " 71.5% SMC Burlingame Hills 6.0 4.3 \n", " 66.7% SMC Coal Creek Preserve 3.9 2.6 \n", " 63.5% --- San Mateo County 2814.0 1,787 \n", " 59.5% SMC Russian Ridge Preserve 12.2 7.3 \n", " 59.3% SMC Montara 27.8 16 \n", " 56.2% SMC Burlingame 88.4 50 \n", " 54.7% SMC Belmont 98.1 54 \n", " 53.3% SCC Sunnyvale 357.0 190 \n", " 52.8% SCC Cupertino 172.0 91 \n", " 52.4% SCC Monte Sereno 20.4 11 \n", " 52.3% SMC Hillsborough 85.3 45 \n", " 51.8% SMC San Mateo 256.0 133 \n", " 51.5% SMC Half Moon Bay State Beach 4.4 2.3 \n", " 51.2% SMC Long Ridge Preserve 11.0 5.6 \n", " 51.2% SCC Castle Rock State Park 11.2 5.7 \n", " 51.0% ALA Newark 147.0 75 \n", " 50.4% SCC Saratoga 180.0 91 \n", " 50.2% SMC Brisbane 40.9 21 \n", " 47.7% SCC Edenvale 30.0 14 \n", " 47.3% NSW Barangaroo 1.7 0.8 \n", " 47.2% SCC Gardner 23.4 11 \n", " 43.9% SFC Presidio Terrace 2.8 1.2 \n", " 43.6% SMC El Granada 49.2 21 \n", " 43.6% SMC Moss Beach 19.7 8.6 \n", " 43.3% ALA Hayward Acres 3.5 1.5 \n", " 42.6% SMC Millbrae 65.0 28 \n", " 40.8% ALA San Lorenzo 55.5 23 \n", " 39.6% SFC Lincoln Park 4.5 1.8 \n", " 39.5% SCC Communications Hill 27.8 11 \n", " 39.0% SMC Purisima Creek Preserve 16.5 6.4 \n", " 38.9% SMC Colma 13.7 5.3 \n", " 38.7% MAR Mt Tamalpais State Park 31.7 12 \n", " 38.2% SMC Broadmoor 8.8 3.4 \n", " 37.4% SFC South Beach 4.8 1.8 \n", " 37.1% MAR Muir Beach 4.6 1.7 \n", " 36.8% SCC Spartan Keyes 64.3 24 \n", " 36.8% SFC Lake Street 3.9 1.4 \n", " 36.7% SCC Milpitas 224.0 82 \n", " 36.1% ALA Ashland 35.1 13 \n", " 36.0% SCC Willow Glen 81.6 29 \n", " 34.8% SCC Santa Clara 348.0 121 \n", " 34.7% MAS MIT 9.6 3.3 \n", " 34.3% NSW Millers Point 3.2 1.1 \n", " 33.7% SCC Parkview 42.5 14 \n", " 33.6% SMC Half Moon Bay 68.0 23 \n", " 33.6% SCC Los Gatos 148.0 50 \n", " 33.2% SMC Pacifica 150.9 50 \n", " 33.0% SCC Seven Trees 40.9 13 \n", " 33.0% --- Santa Clara County 7569.0 2,498 \n", " 32.9% ALA Fremont 780.2 257 \n", " 32.9% ALA Union City 208.8 69 \n", " 32.9% MAR Stinson Beach 11.2 3.7 \n", " 32.7% ALA Hayward 444.5 145 \n", " 32.7% SCC Branham 44.0 14 \n", " 31.9% MAR Marin Headlands GGNRA 65.7 21 \n", " 31.5% SCC San Martin 35.3 11 \n", " 31.0% SMC San Bruno 114.0 35 \n", " 30.9% SCC Willow Glen South 63.3 20 \n", " 30.7% SCC Forest of Nisene Marks SP 44.0 14 \n", " 30.1% SMC Butano State Park 15.2 4.6 \n", " 29.6% SMC South San Francisco 185.3 55 \n", " 29.4% SFC Golden Gate Park 40.8 12 \n", " 29.3% SFC Seacliff 4.1 1.2 \n", " 29.3% SCC Campbell 119.0 35 \n", " 29.2% NSW Dawes Point 1.8 0.5 \n", " 28.2% ALA Fairview 34.4 9.7 \n", " 28.0% SCC San Jose 2618.7 733 \n", " 27.8% ALA Cherryland 20.9 5.8 \n", " 27.7% ALA San Leandro 230.6 64 \n", " 27.4% SMC Daly City 148.1 41 \n", " 26.8% CAL Mokelumne Hill 14.7 3.9 \n", " 26.7% SFC Presidio National Park 43.5 12 \n", " 26.4% SCC Gilroy 188.9 50 \n", " 26.1% ALA Castro Valley 192.5 50 \n", " 25.6% SMC Bay Area Ridge Trail 395.6 101 \n", " 23.6% SON Guerneville 22.7 5.4 \n", " 21.6% SFC Presidio Heights 6.5 1.4 \n", " 20.6% SFC Panhandle 7.3 1.5 \n", " 18.2% SFC Balboa Terrace 3.4 0.6 \n", " 18.2% SFC Polk Gulch 4.0 0.7 \n", " 18.0% SFC Cole Valley 1.7 0.3 \n", " 17.8% SON Healdsburg 53.7 9.6 \n", " 17.0% SON Bodega Bay 28.9 4.9 \n", " 16.6% --- Alameda County 5818.0 965 \n", " 15.9% SFC Forest Hill 6.1 1.0 \n", " 15.5% SFC Northern Waterfront 5.6 0.9 \n", " 15.4% SFC Aquatic Park Fort Mason 6.4 1.0 \n", " 15.2% SFC Little Hollywood 3.7 0.6 \n", " 14.2% SFC Clarendon Heights 6.0 0.9 \n", " 13.8% SFC Fisherman's Wharf 6.2 0.9 \n", " 13.2% SFC Sutro Heights 7.1 0.9 \n", " 13.0% SFC Ashbury Heights 3.7 0.5 \n", " 12.9% MAR Corte Madera 51.0 6.6 \n", " 12.9% MAR Sausalito 32.7 4.2 \n", " 12.3% SFC Dogpatch 5.1 0.6 \n", " 12.2% ALA Alameda 206.7 25 \n", " 11.9% SFC Cow Hollow 12.0 1.4 \n", " 10.9% --- Marin County 2333.0 255 \n", " 10.7% SFC Pacific Heights 18.0 1.9 \n", " 10.7% SFC Golden Gate Heights 17.8 1.9 \n", " 10.2% SFC Financial District 9.4 1.0 \n", " 9.3% --- San Francisco County 1217.0 113 \n", " 9.1% MAR Mill Valley 92.2 8.4 \n", " 8.9% --- Napa County 1609.0 143 \n", " 8.6% SFC Mission Bay 13.8 1.2 \n", " 7.7% ALA Emeryville 28.1 2.2 \n", " 7.6% ALA Berkeley 260.3 20 \n", " 7.1% --- Santa Cruz County 2718.0 194 \n", " 6.8% ALA Albany 42.7 2.9 \n", " 6.2% MAS Cambridge 180.8 11 \n", " 6.0% SFC Central Waterfront 10.2 0.6 \n", " 5.1% --- Sonoma County 4895.0 251 \n", " 3.8% --- Contra Costa County 5945.0 226 \n", " 3.7% MAR San Rafael 260.0 9.6 \n", " 1.8% --- California 377037.0 6,719 \n", " 0.113% --- USA 6406754.0 7,267 \n", " 0.017% --- Earth 41974536.0 7,159 \n", "\n", " to next badge \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " 1.0 mi to 99% \n", " 0.2 mi to 99% \n", " 13 mi to 99% \n", " 0.0 mi to 90% \n", " 0.1 mi to 90% \n", " 41 mi to 90% \n", " 0.9 mi to 90% \n", " 1.1 mi to 90% \n", " 0.9 mi to 90% \n", " 746 mi to 90% \n", " 3.7 mi to 90% \n", " 8.5 mi to 90% \n", " 30 mi to 90% \n", " 35 mi to 90% \n", " 131 mi to 90% \n", " 64 mi to 90% \n", " 7.7 mi to 90% \n", " 32 mi to 90% \n", " 98 mi to 90% \n", " 1.7 mi to 90% \n", " 4.3 mi to 90% \n", " 4.3 mi to 90% \n", " 57 mi to 90% \n", " 71 mi to 90% \n", " 16 mi to 90% \n", " 0.7 mi to 50% \n", " 0.0 mi to 50% \n", " 0.7 mi to 50% \n", " 0.2 mi to 50% \n", " 3.1 mi to 50% \n", " 1.3 mi to 50% \n", " 0.2 mi to 50% \n", " 4.8 mi to 50% \n", " 5.1 mi to 50% \n", " 0.5 mi to 50% \n", " 2.9 mi to 50% \n", " 1.8 mi to 50% \n", " 1.5 mi to 50% \n", " 3.6 mi to 50% \n", " 1.0 mi to 50% \n", " 0.6 mi to 50% \n", " 0.6 mi to 50% \n", " 8.5 mi to 50% \n", " 0.5 mi to 50% \n", " 30 mi to 50% \n", " 4.9 mi to 50% \n", " 11 mi to 50% \n", " 53 mi to 50% \n", " 1.5 mi to 50% \n", " 0.5 mi to 50% \n", " 6.9 mi to 50% \n", " 11 mi to 50% \n", " 24 mi to 50% \n", " 25 mi to 50% \n", " 7.0 mi to 50% \n", " 1,287 mi to 50% \n", " 133 mi to 50% \n", " 36 mi to 50% \n", " 1.9 mi to 50% \n", " 77 mi to 50% \n", " 7.6 mi to 50% \n", " 12 mi to 50% \n", " 6.5 mi to 50% \n", " 22 mi to 50% \n", " 12 mi to 50% \n", " 8.5 mi to 50% \n", " 3.0 mi to 50% \n", " 38 mi to 50% \n", " 8.4 mi to 50% \n", " 0.8 mi to 50% \n", " 25 mi to 50% \n", " 0.4 mi to 50% \n", " 7.5 mi to 50% \n", " 576 mi to 50% \n", " 4.6 mi to 50% \n", " 51 mi to 50% \n", " 33 mi to 50% \n", " 3.4 mi to 50% \n", " 10 mi to 50% \n", " 45 mi to 50% \n", " 46 mi to 50% \n", " 97 mi to 50% \n", " 0.3 mi to 25% \n", " 0.2 mi to 25% \n", " 0.3 mi to 25% \n", " 0.2 mi to 25% \n", " 0.3 mi to 25% \n", " 0.1 mi to 25% \n", " 3.9 mi to 25% \n", " 2.3 mi to 25% \n", " 490 mi to 25% \n", " 0.6 mi to 25% \n", " 0.5 mi to 25% \n", " 0.6 mi to 25% \n", " 0.4 mi to 25% \n", " 0.6 mi to 25% \n", " 0.7 mi to 25% \n", " 0.8 mi to 25% \n", " 0.4 mi to 25% \n", " 6.2 mi to 25% \n", " 4.0 mi to 25% \n", " 0.6 mi to 25% \n", " 26 mi to 25% \n", " 1.6 mi to 25% \n", " 328 mi to 25% \n", " 2.6 mi to 25% \n", " 2.5 mi to 25% \n", " 1.4 mi to 25% \n", " 192 mi to 25% \n", " 15 mi to 25% \n", " 259 mi to 25% \n", " 2.3 mi to 25% \n", " 4.9 mi to 25% \n", " 45 mi to 25% \n", " 486 mi to 25% \n", " 7.8 mi to 25% \n", " 34 mi to 25% \n", " 1.9 mi to 25% \n", " 973 mi to 25% \n", " 1,260 mi to 25% \n", " 55 mi to 25% \n", " 822 mi to 2% \n", " 5,546 mi to 0.2% \n", " 1,236 mi to 0.02% " ] }, "execution_count": 4, "metadata": {}, "output_type": "execute_result" } ], "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 SCC and Megan Gardner is 1,000 miles ahead of me in SMC. Barry Mann is the leader in total miles in the two counties, and Megan leads in 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 December 2023), where the dotted line indicates the Pareto front." ] }, { "cell_type": "code", "execution_count": 5, "metadata": {}, "outputs": [ { "data": { "text/html": [ "
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NameInitialsSMC %SCC %SMC milesSCC milesTotal milesAvg %
Megan GardnerMG99.4013.627971029382656.50
Barry MannBM77.4030.421782301447953.90
Peter NorvigPN65.1035.318322672450450.20
Brian FeinbergBF32.5044.09153330424538.25
Jason MolendaJM7.5656.22134254446731.88
\n", "
" ], "text/plain": [ " Name Initials SMC % SCC % SMC miles SCC miles Total miles \\\n", " Megan Gardner MG 99.40 13.6 2797 1029 3826 \n", " Barry Mann BM 77.40 30.4 2178 2301 4479 \n", " Peter Norvig PN 65.10 35.3 1832 2672 4504 \n", " Brian Feinberg BF 32.50 44.0 915 3330 4245 \n", " Jason Molenda JM 7.56 56.2 213 4254 4467 \n", "\n", " Avg % \n", " 56.50 \n", " 53.90 \n", " 50.20 \n", " 38.25 \n", " 31.88 " ] }, "execution_count": 5, "metadata": {}, "output_type": "execute_result" }, { "data": { "image/png": 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\n", 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" ] }, "metadata": { "needs_background": "light" }, "output_type": "display_data" } ], "source": [ "pareto_front(leaders)" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "# Eddington Number\n", "\n", "The physicist/bicyclist [Sir Arthur Eddington](https://en.wikipedia.org/wiki/Arthur_Eddington), a contemporary of Einstein defined the [**Eddington Number**](https://www.triathlete.com/2011/04/training/measuring-bike-miles-eddington-number_301789) as 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": 6, "metadata": {}, "outputs": [ { "data": { "text/html": [ "
\n", "\n", "\n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", "
yearEd_kmEd_mi
202410368
202310167
20229666
20219365
20208762
20198056
20187754
20177351
20166747
20156142
20144635
\n", "
" ], "text/plain": [ " year Ed_km Ed_mi\n", " 2024 103 68\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": 6, "metadata": {}, "output_type": "execute_result" } ], "source": [ "Ed_progress(rides)" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "My current Eddington Number is **103** in kilometers and **68** in miles (I've ridden at least 68 miles on at least 68 days, but not 69 miles on 69 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, weather, bicycles, and navigation aids were not nearly as nice as mine, so hip hip and 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": 7, "metadata": {}, "outputs": [ { "data": { "text/html": [ "
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kmskms gapmilesmiles gap
1047699
105137021
106177131
107257234
108297338
109357440
110437548
111517651
112627754
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" ], "text/plain": [ " kms kms gap miles miles gap\n", " 104 7 69 9\n", " 105 13 70 21\n", " 106 17 71 31\n", " 107 25 72 34\n", " 108 29 73 38\n", " 109 35 74 40\n", " 110 43 75 48\n", " 111 51 76 51\n", " 112 62 77 54" ] }, "execution_count": 7, "metadata": {}, "output_type": "execute_result" } ], "source": [ "Ed_gaps(rides)" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "I need 7 rides of 104 kms or 9 rides of 69 miles to increase my Eddington numbers. Why so many? Apparently, I had a lot of rides that were about 103.5 kms, and a bunch of other rides that were about 68.5 miles.\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": 8, "metadata": {}, "outputs": [ { "data": { "image/png": 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\n", 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" ] }, "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": 9, "metadata": {}, "outputs": [ { "data": { "image/png": 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\n", "text/plain": [ "
" ] }, "metadata": { "needs_background": "light" }, "output_type": "display_data" } ], "source": [ "show('fpmi', '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": 10, "metadata": {}, "outputs": [ { "data": { "text/plain": [ "'Coast: 70 min, Creek: 64 min.'" ] }, "execution_count": 10, "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 is measured by [VAM](https://en.wikipedia.org/wiki/VAM_%28bicycling%29), which stands for *velocità ascensionale media* (for native Campagnolo speakers) or *vertical ascent in meters per hour* (for SRAM) or 平均上昇率 (for Shimano), or *Vm/h* (for physicists). 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 segments 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": 11, "metadata": {}, "outputs": [ { "data": { "image/png": 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\n", "text/plain": [ "
" ] }, "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 800 meters/hour, and I can sustain the higher numbers for only a couple of minutes:" ] }, { "cell_type": "code", "execution_count": 12, "metadata": {}, "outputs": [ { "data": { "text/html": [ "
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titlehoursmilesfeetmphvamfpmipctkmsmeters
Camaritas climb0.010.104810.001463.0480.09.090.1615.0
Paloma Climb0.020.14827.001250.0586.011.090.2325.0
Klamath Dr.0.020.12776.001173.0642.012.150.1923.0
Entrance Way Hill Repeats0.020.10765.001158.0760.014.390.1623.0
Davenport Kicker0.020.247412.001128.0308.05.840.3923.0
Valparaiso steep0.040.181454.501105.0806.015.260.2944.0
Invernes to Firecrest Climb0.040.281437.001090.0511.09.670.4544.0
Kings Mountain final sprint0.040.311357.751029.0435.08.250.5041.0
Limantour Spit0.090.473035.221026.0645.012.210.7692.0
Tunitas flattens0.050.421668.401012.0395.07.490.6851.0
Tunitas flattens0.050.421668.401012.0395.07.490.6851.0
Cemetery Sprint0.010.08338.001006.0412.07.810.1310.0
Skyline Bump at OLH0.020.216310.50960.0300.05.680.3419.0
Laning Bump0.030.24948.00955.0392.07.420.3929.0
Faught Turn0.020.226011.00914.0273.05.170.3518.0
Westridge 3min0.080.372404.62914.0649.012.290.6073.0
Valparaiso steep0.050.181453.60884.0806.015.260.2944.0
Sharon Park steep part0.030.21867.00874.0410.07.760.3426.0
Old La Honda Mile 10.130.993707.62868.0374.07.081.59113.0
Joaquin0.090.332543.67860.0770.014.580.5377.0
\n", "
" ], "text/plain": [ " title hours miles feet mph vam fpmi \\\n", " Camaritas climb 0.01 0.10 48 10.00 1463.0 480.0 \n", " Paloma Climb 0.02 0.14 82 7.00 1250.0 586.0 \n", " Klamath Dr. 0.02 0.12 77 6.00 1173.0 642.0 \n", " Entrance Way Hill Repeats 0.02 0.10 76 5.00 1158.0 760.0 \n", " Davenport Kicker 0.02 0.24 74 12.00 1128.0 308.0 \n", " Valparaiso steep 0.04 0.18 145 4.50 1105.0 806.0 \n", " Invernes to Firecrest Climb 0.04 0.28 143 7.00 1090.0 511.0 \n", " Kings Mountain final sprint 0.04 0.31 135 7.75 1029.0 435.0 \n", " Limantour Spit 0.09 0.47 303 5.22 1026.0 645.0 \n", " Tunitas flattens 0.05 0.42 166 8.40 1012.0 395.0 \n", " Tunitas flattens 0.05 0.42 166 8.40 1012.0 395.0 \n", " Cemetery Sprint 0.01 0.08 33 8.00 1006.0 412.0 \n", " Skyline Bump at OLH 0.02 0.21 63 10.50 960.0 300.0 \n", " Laning Bump 0.03 0.24 94 8.00 955.0 392.0 \n", " Faught Turn 0.02 0.22 60 11.00 914.0 273.0 \n", " Westridge 3min 0.08 0.37 240 4.62 914.0 649.0 \n", " Valparaiso steep 0.05 0.18 145 3.60 884.0 806.0 \n", " Sharon Park steep part 0.03 0.21 86 7.00 874.0 410.0 \n", " Old La Honda Mile 1 0.13 0.99 370 7.62 868.0 374.0 \n", " Joaquin 0.09 0.33 254 3.67 860.0 770.0 \n", "\n", " pct kms meters \n", " 9.09 0.16 15.0 \n", " 11.09 0.23 25.0 \n", " 12.15 0.19 23.0 \n", " 14.39 0.16 23.0 \n", " 5.84 0.39 23.0 \n", " 15.26 0.29 44.0 \n", " 9.67 0.45 44.0 \n", " 8.25 0.50 41.0 \n", " 12.21 0.76 92.0 \n", " 7.49 0.68 51.0 \n", " 7.49 0.68 51.0 \n", " 7.81 0.13 10.0 \n", " 5.68 0.34 19.0 \n", " 7.42 0.39 29.0 \n", " 5.17 0.35 18.0 \n", " 12.29 0.60 73.0 \n", " 15.26 0.29 44.0 \n", " 7.76 0.34 26.0 \n", " 7.08 1.59 113.0 \n", " 14.58 0.53 77.0 " ] }, "execution_count": 12, "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": 13, "metadata": {}, "outputs": [ { "data": { "text/html": [ "
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titlehoursmilesfeetmphvamfpmipctkmsmeters
Old La Honda Mile 10.130.993707.62868.0374.07.081.59113.0
Westridge0.140.683854.86838.0566.010.721.09117.0
Old La Honda (Bridge to Stop)0.483.3312556.94797.0377.07.145.36383.0
Old La Honda (Bridge to Stop)0.513.3312556.53750.0377.07.145.36383.0
Westridge0.160.683854.25733.0566.010.721.09117.0
Tunitas steep0.251.205994.80730.0499.09.451.93183.0
Old La Honda Mile 10.160.993706.19705.0374.07.081.59113.0
Woodside Climb0.131.7129513.15692.0173.03.272.7590.0
Huddart0.170.923855.41690.0418.07.931.48117.0
Top of Groton Rd heading west0.130.922917.08682.0316.05.991.4889.0
Watts (Sonoma)0.141.203138.57681.0261.04.941.9395.0
Tunitas steep0.271.205994.44676.0499.09.451.93183.0
Canon to No Cycling0.090.751988.33671.0264.05.001.2160.0
Canon to No Cycling0.090.751988.33671.0264.05.001.2160.0
Coe Second Switchback to flat0.221.004834.55669.0483.09.151.61147.0
Lower Redwood Gulch0.221.034744.68657.0460.08.721.66144.0
Lobitas Creek0.200.964304.80655.0448.08.481.54131.0
West Alpine switchback0.150.783225.20654.0413.07.821.2698.0
Kaboom Portola Rd0.050.6710213.40622.0152.02.881.0831.0
Huddart0.190.923854.84618.0418.07.931.48117.0
Kings Greer to Skyline0.783.9215365.03600.0392.07.426.31468.0
Woodside Climb0.151.7129511.40599.0173.03.272.7590.0
Stage Rd0.191.013735.32598.0369.06.991.63114.0
Try not to fall back0.210.714103.38595.0577.010.941.14125.0
Sand Gill Sharon-top0.070.8513612.14592.0160.03.031.3741.0
Sand Gill Sharon-top0.070.8513612.14592.0160.03.031.3741.0
Mt Eden climb0.141.022727.29592.0267.05.051.6483.0
Tunitas lower climb0.221.304215.91583.0324.06.132.09128.0
Kings Greer to Skyline0.813.9215364.84578.0392.07.426.31468.0
Haskins0.301.515665.03575.0375.07.102.43173.0
\n", "
" ], "text/plain": [ " title hours miles feet mph vam fpmi \\\n", " Old La Honda Mile 1 0.13 0.99 370 7.62 868.0 374.0 \n", " Westridge 0.14 0.68 385 4.86 838.0 566.0 \n", " Old La Honda (Bridge to Stop) 0.48 3.33 1255 6.94 797.0 377.0 \n", " Old La Honda (Bridge to Stop) 0.51 3.33 1255 6.53 750.0 377.0 \n", " Westridge 0.16 0.68 385 4.25 733.0 566.0 \n", " Tunitas steep 0.25 1.20 599 4.80 730.0 499.0 \n", " Old La Honda Mile 1 0.16 0.99 370 6.19 705.0 374.0 \n", " Woodside Climb 0.13 1.71 295 13.15 692.0 173.0 \n", " Huddart 0.17 0.92 385 5.41 690.0 418.0 \n", " Top of Groton Rd heading west 0.13 0.92 291 7.08 682.0 316.0 \n", " Watts (Sonoma) 0.14 1.20 313 8.57 681.0 261.0 \n", " Tunitas steep 0.27 1.20 599 4.44 676.0 499.0 \n", " Canon to No Cycling 0.09 0.75 198 8.33 671.0 264.0 \n", " Canon to No Cycling 0.09 0.75 198 8.33 671.0 264.0 \n", " Coe Second Switchback to flat 0.22 1.00 483 4.55 669.0 483.0 \n", " Lower Redwood Gulch 0.22 1.03 474 4.68 657.0 460.0 \n", " Lobitas Creek 0.20 0.96 430 4.80 655.0 448.0 \n", " West Alpine switchback 0.15 0.78 322 5.20 654.0 413.0 \n", " Kaboom Portola Rd 0.05 0.67 102 13.40 622.0 152.0 \n", " Huddart 0.19 0.92 385 4.84 618.0 418.0 \n", " Kings Greer to Skyline 0.78 3.92 1536 5.03 600.0 392.0 \n", " Woodside Climb 0.15 1.71 295 11.40 599.0 173.0 \n", " Stage Rd 0.19 1.01 373 5.32 598.0 369.0 \n", " Try not to fall back 0.21 0.71 410 3.38 595.0 577.0 \n", " Sand Gill Sharon-top 0.07 0.85 136 12.14 592.0 160.0 \n", " Sand Gill Sharon-top 0.07 0.85 136 12.14 592.0 160.0 \n", " Mt Eden climb 0.14 1.02 272 7.29 592.0 267.0 \n", " Tunitas lower climb 0.22 1.30 421 5.91 583.0 324.0 \n", " Kings Greer to Skyline 0.81 3.92 1536 4.84 578.0 392.0 \n", " Haskins 0.30 1.51 566 5.03 575.0 375.0 \n", "\n", " pct kms meters \n", " 7.08 1.59 113.0 \n", " 10.72 1.09 117.0 \n", " 7.14 5.36 383.0 \n", " 7.14 5.36 383.0 \n", " 10.72 1.09 117.0 \n", " 9.45 1.93 183.0 \n", " 7.08 1.59 113.0 \n", " 3.27 2.75 90.0 \n", " 7.93 1.48 117.0 \n", " 5.99 1.48 89.0 \n", " 4.94 1.93 95.0 \n", " 9.45 1.93 183.0 \n", " 5.00 1.21 60.0 \n", " 5.00 1.21 60.0 \n", " 9.15 1.61 147.0 \n", " 8.72 1.66 144.0 \n", " 8.48 1.54 131.0 \n", " 7.82 1.26 98.0 \n", " 2.88 1.08 31.0 \n", " 7.93 1.48 117.0 \n", " 7.42 6.31 468.0 \n", " 3.27 2.75 90.0 \n", " 6.99 1.63 114.0 \n", " 10.94 1.14 125.0 \n", " 3.03 1.37 41.0 \n", " 3.03 1.37 41.0 \n", " 5.05 1.64 83.0 \n", " 6.13 2.09 128.0 \n", " 7.42 6.31 468.0 \n", " 7.10 2.43 173.0 " ] }, "execution_count": 13, "metadata": {}, "output_type": "execute_result" } ], "source": [ "top(segments[segments.kms >= 1], 'vam', n=30)" ] }, { "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": 14, "metadata": {}, "outputs": [ { "data": { "text/html": [ "
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dateyeartitlehoursmilesfeetmphvamfpmipctkmsmeters
Sun, 11/29/20152015Mt. Hamilton3.6837.00490210.05406.0132.02.5159.531494.0
Fri, 4/2/20212021Everesting 5: climb 2×(OLH + WOLH)3.2731.4843449.63405.0138.02.6150.651324.0
Mon, 3/29/20212021Everesting 1: Mt Diablo2.6022.2234068.55399.0153.02.9035.751038.0
Tue, 3/30/20212021Everesting 2: Kings + WOLH + OLH3.3435.99437710.78399.0122.02.3057.911334.0
Sun, 12/1/20132013Mt. Hamilton3.7837.5649219.94397.0131.02.4860.431500.0
Sat, 11/25/20172017Mt. Hamilton3.6936.6548069.93397.0131.02.4858.971465.0
Fri, 10/30/20152015OLH / West Alpine3.4839.51450511.35395.0114.02.1663.571373.0
Sat, 4/26/20142014OLH / Tunitas Creek5.2658.69674211.16391.0115.02.1894.432055.0
Sat, 4/18/20152015Tunitas + Lobitos Creeks5.2461.27661111.69385.0108.02.0498.582015.0
Wed, 10/14/20152015Half Moon Bay6.1372.97764411.90380.0105.01.98117.412330.0
Sun, 6/4/20172017Sequoia Challenge6.2966.52752010.58364.0113.02.14107.032292.0
Sat, 7/25/20152015Palo Alto, California4.0443.62481910.80364.0110.02.0970.181469.0
Sat, 10/11/20142014OLH / Tunitas5.0958.29604411.45362.0104.01.9693.791842.0
Sat, 8/13/20162016Petaluma / Point Reyes4.5054.75528612.17358.097.01.8388.091611.0
Fri, 8/28/20152015Pescadaro via OLH5.3166.01613712.43352.093.01.76106.211871.0
Sun, 4/4/20212021Everesting 7: Mill Creek / Morrison Canyon3.0829.3835179.54348.0120.02.2747.271072.0
Sat, 2/10/20242024Seacliff, etc.4.7263.41536513.43346.085.01.60102.031635.0
Wed, 6/18/20142014Sierra to the Sea Day 44.9657.64556111.62342.096.01.8392.741695.0
Sun, 6/3/20182018The Sequoia5.9764.92667710.87341.0103.01.95104.462035.0
Sat, 5/9/20152015OLH2.5032.33278812.93340.086.01.6352.02850.0
\n", "
" ], "text/plain": [ " date year title hours \\\n", " Sun, 11/29/2015 2015 Mt. Hamilton 3.68 \n", " Fri, 4/2/2021 2021 Everesting 5: climb 2×(OLH + WOLH) 3.27 \n", " Mon, 3/29/2021 2021 Everesting 1: Mt Diablo 2.60 \n", " Tue, 3/30/2021 2021 Everesting 2: Kings + WOLH + OLH 3.34 \n", " Sun, 12/1/2013 2013 Mt. Hamilton 3.78 \n", " Sat, 11/25/2017 2017 Mt. Hamilton 3.69 \n", " Fri, 10/30/2015 2015 OLH / West Alpine 3.48 \n", " Sat, 4/26/2014 2014 OLH / Tunitas Creek 5.26 \n", " Sat, 4/18/2015 2015 Tunitas + Lobitos Creeks 5.24 \n", " Wed, 10/14/2015 2015 Half Moon Bay 6.13 \n", " Sun, 6/4/2017 2017 Sequoia Challenge 6.29 \n", " Sat, 7/25/2015 2015 Palo Alto, California 4.04 \n", " Sat, 10/11/2014 2014 OLH / Tunitas 5.09 \n", " Sat, 8/13/2016 2016 Petaluma / Point Reyes 4.50 \n", " Fri, 8/28/2015 2015 Pescadaro via OLH 5.31 \n", " Sun, 4/4/2021 2021 Everesting 7: Mill Creek / Morrison Canyon 3.08 \n", " Sat, 2/10/2024 2024 Seacliff, etc. 4.72 \n", " Wed, 6/18/2014 2014 Sierra to the Sea Day 4 4.96 \n", " Sun, 6/3/2018 2018 The Sequoia 5.97 \n", " Sat, 5/9/2015 2015 OLH 2.50 \n", "\n", " miles feet mph vam fpmi pct kms meters \n", " 37.00 4902 10.05 406.0 132.0 2.51 59.53 1494.0 \n", " 31.48 4344 9.63 405.0 138.0 2.61 50.65 1324.0 \n", " 22.22 3406 8.55 399.0 153.0 2.90 35.75 1038.0 \n", " 35.99 4377 10.78 399.0 122.0 2.30 57.91 1334.0 \n", " 37.56 4921 9.94 397.0 131.0 2.48 60.43 1500.0 \n", " 36.65 4806 9.93 397.0 131.0 2.48 58.97 1465.0 \n", " 39.51 4505 11.35 395.0 114.0 2.16 63.57 1373.0 \n", " 58.69 6742 11.16 391.0 115.0 2.18 94.43 2055.0 \n", " 61.27 6611 11.69 385.0 108.0 2.04 98.58 2015.0 \n", " 72.97 7644 11.90 380.0 105.0 1.98 117.41 2330.0 \n", " 66.52 7520 10.58 364.0 113.0 2.14 107.03 2292.0 \n", " 43.62 4819 10.80 364.0 110.0 2.09 70.18 1469.0 \n", " 58.29 6044 11.45 362.0 104.0 1.96 93.79 1842.0 \n", " 54.75 5286 12.17 358.0 97.0 1.83 88.09 1611.0 \n", " 66.01 6137 12.43 352.0 93.0 1.76 106.21 1871.0 \n", " 29.38 3517 9.54 348.0 120.0 2.27 47.27 1072.0 \n", " 63.41 5365 13.43 346.0 85.0 1.60 102.03 1635.0 \n", " 57.64 5561 11.62 342.0 96.0 1.83 92.74 1695.0 \n", " 64.92 6677 10.87 341.0 103.0 1.95 104.46 2035.0 \n", " 32.33 2788 12.93 340.0 86.0 1.63 52.02 850.0 " ] }, "execution_count": 14, "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": 15, "metadata": {}, "outputs": [ { "data": { "text/html": [ "
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yearhoursmilesfeetmphvamfpmipctkmsmeters
count541.000000541.000000541.000000541.000000541.000000541.000000541.000000541.000000541.000000541.000000
mean2016.9852133.36388243.0021071822.04621112.985176157.63401141.5009240.78576769.190296555.364140
std2.5516451.45911617.5284751495.0224521.31783289.93797827.2317640.51562728.203336455.678902
min2012.0000001.54000020.96000068.0000008.55000010.0000003.0000000.05000033.72000021.000000
25%2015.0000002.21000029.060000732.00000012.16000081.00000020.0000000.37000046.760000223.000000
50%2017.0000002.87000036.8200001375.00000013.140000152.00000036.0000000.69000059.240000419.000000
75%2018.0000004.38000057.0500002323.00000013.780000218.00000056.0000001.07000091.790000708.000000
max2024.0000008.140000102.4100007644.00000016.750000406.000000153.0000002.900000164.7800002330.000000
\n", "
" ], "text/plain": [ " year hours miles feet mph \\\n", "count 541.000000 541.000000 541.000000 541.000000 541.000000 \n", "mean 2016.985213 3.363882 43.002107 1822.046211 12.985176 \n", "std 2.551645 1.459116 17.528475 1495.022452 1.317832 \n", "min 2012.000000 1.540000 20.960000 68.000000 8.550000 \n", "25% 2015.000000 2.210000 29.060000 732.000000 12.160000 \n", "50% 2017.000000 2.870000 36.820000 1375.000000 13.140000 \n", "75% 2018.000000 4.380000 57.050000 2323.000000 13.780000 \n", "max 2024.000000 8.140000 102.410000 7644.000000 16.750000 \n", "\n", " vam fpmi pct kms meters \n", "count 541.000000 541.000000 541.000000 541.000000 541.000000 \n", "mean 157.634011 41.500924 0.785767 69.190296 555.364140 \n", "std 89.937978 27.231764 0.515627 28.203336 455.678902 \n", "min 10.000000 3.000000 0.050000 33.720000 21.000000 \n", "25% 81.000000 20.000000 0.370000 46.760000 223.000000 \n", "50% 152.000000 36.000000 0.690000 59.240000 419.000000 \n", "75% 218.000000 56.000000 1.070000 91.790000 708.000000 \n", "max 406.000000 153.000000 2.900000 164.780000 2330.000000 " ] }, "execution_count": 15, "metadata": {}, "output_type": "execute_result" } ], "source": [ "rides.describe() # Summary statistics for the rides" ] }, { "cell_type": "code", "execution_count": 16, "metadata": {}, "outputs": [ { "data": { "text/html": [ "
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hoursmilesfeetmphvamfpmipctkmsmeters
count141.000000141.000000141.000000141.000000141.000000141.000000141.000000141.000000141.000000
mean0.1417020.932979268.9787237.444539641.893617353.5035466.6948941.50106481.978723
std0.1737110.989832295.0606593.557336211.923595186.8163203.5379741.59226789.957408
min0.0100000.08000021.0000002.120000111.00000018.0000000.3500000.1300006.000000
25%0.0500000.330000104.0000004.830000503.000000219.0000004.1400000.53000032.000000
50%0.0900000.600000166.0000006.190000630.000000333.0000006.3000000.97000051.000000
75%0.1500001.190000303.0000009.800000724.000000462.0000008.7600001.91000092.000000
max1.3900007.3800001887.00000019.7900001463.000000839.00000015.89000011.870000575.000000
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" ], "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", " fpmi pct kms meters \n", "count 141.000000 141.000000 141.000000 141.000000 \n", "mean 353.503546 6.694894 1.501064 81.978723 \n", "std 186.816320 3.537974 1.592267 89.957408 \n", "min 18.000000 0.350000 0.130000 6.000000 \n", "25% 219.000000 4.140000 0.530000 32.000000 \n", "50% 333.000000 6.300000 0.970000 51.000000 \n", "75% 462.000000 8.760000 1.910000 92.000000 \n", "max 839.000000 15.890000 11.870000 575.000000 " ] }, "execution_count": 16, "metadata": {}, "output_type": "execute_result" } ], "source": [ "segments.describe() # Summary statistics for the segments" ] }, { "cell_type": "code", "execution_count": 17, "metadata": {}, "outputs": [ { "data": { "text/html": [ "
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dateyeartitlehoursmilesfeetmphvamfpmipctkmsmeters
Sun, 5/22/20162016Canada2.1936.68133216.75185.036.00.6959.02406.0
Wed, 9/13/20172017Healdburg / Jimtown2.1334.4591216.17131.026.00.5055.43278.0
Sat, 1/25/20142014Woodside1.5625.08124316.08243.050.00.9440.35379.0
Sat, 4/11/20152015Woodside1.5424.73103516.06205.042.00.7939.79315.0
Mon, 5/27/20242024Saratoga4.8377.25174915.99110.023.00.43124.30533.0
Sun, 7/11/20212021San Jose4.1065.10108615.8881.017.00.32104.75331.0
Sun, 1/18/20152015Woodside1.6426.02125715.87234.048.00.9141.87383.0
Fri, 6/24/20162016Foothill Expway1.5925.1162315.79119.025.00.4740.40190.0
Sun, 1/26/20142014Canada Rd2.1033.12144615.77210.044.00.8353.29441.0
Fri, 1/6/20122012Omarama to Wanaka New Zealand4.4870.35326215.70222.046.00.88113.19994.0
Sun, 4/12/20152015Palo Alto Cycling2.0331.76121015.65182.038.00.7251.10369.0
Sun, 10/15/20172017Los Gatos2.8644.71143715.63153.032.00.6171.94438.0
Sun, 8/5/20182018Bike Ride Northwest Day 13.5855.77182415.58155.033.00.6289.73556.0
Sun, 2/28/20162016Woodside Loop1.7326.9384315.57149.031.00.5943.33257.0
Sun, 6/26/20162016Los Gatos3.2850.78118115.48110.023.00.4481.71360.0
Mon, 1/19/20152015Canada Rd, etc.2.9545.64183615.47190.040.00.7673.43560.0
Sun, 1/19/20142014Palo Alto, CA1.6225.01120115.44226.048.00.9140.24366.0
Sun, 12/6/20152015Canada Rd2.2534.67123715.41168.036.00.6855.78377.0
Tue, 6/18/20132013work etc (headwinds)2.0631.4880915.28120.026.00.4950.65247.0
Fri, 9/23/20162016Los Gatos2.8943.93133915.20141.030.00.5870.68408.0
\n", "
" ], "text/plain": [ " date year title hours miles feet \\\n", " Sun, 5/22/2016 2016 Canada 2.19 36.68 1332 \n", " Wed, 9/13/2017 2017 Healdburg / Jimtown 2.13 34.45 912 \n", " Sat, 1/25/2014 2014 Woodside 1.56 25.08 1243 \n", " Sat, 4/11/2015 2015 Woodside 1.54 24.73 1035 \n", " Mon, 5/27/2024 2024 Saratoga 4.83 77.25 1749 \n", " Sun, 7/11/2021 2021 San Jose 4.10 65.10 1086 \n", " Sun, 1/18/2015 2015 Woodside 1.64 26.02 1257 \n", " Fri, 6/24/2016 2016 Foothill Expway 1.59 25.11 623 \n", " Sun, 1/26/2014 2014 Canada Rd 2.10 33.12 1446 \n", " Fri, 1/6/2012 2012 Omarama to Wanaka New Zealand 4.48 70.35 3262 \n", " Sun, 4/12/2015 2015 Palo Alto Cycling 2.03 31.76 1210 \n", " Sun, 10/15/2017 2017 Los Gatos 2.86 44.71 1437 \n", " Sun, 8/5/2018 2018 Bike Ride Northwest Day 1 3.58 55.77 1824 \n", " Sun, 2/28/2016 2016 Woodside Loop 1.73 26.93 843 \n", " Sun, 6/26/2016 2016 Los Gatos 3.28 50.78 1181 \n", " Mon, 1/19/2015 2015 Canada Rd, etc. 2.95 45.64 1836 \n", " Sun, 1/19/2014 2014 Palo Alto, CA 1.62 25.01 1201 \n", " Sun, 12/6/2015 2015 Canada Rd 2.25 34.67 1237 \n", " Tue, 6/18/2013 2013 work etc (headwinds) 2.06 31.48 809 \n", " Fri, 9/23/2016 2016 Los Gatos 2.89 43.93 1339 \n", "\n", " mph vam fpmi pct kms meters \n", " 16.75 185.0 36.0 0.69 59.02 406.0 \n", " 16.17 131.0 26.0 0.50 55.43 278.0 \n", " 16.08 243.0 50.0 0.94 40.35 379.0 \n", " 16.06 205.0 42.0 0.79 39.79 315.0 \n", " 15.99 110.0 23.0 0.43 124.30 533.0 \n", " 15.88 81.0 17.0 0.32 104.75 331.0 \n", " 15.87 234.0 48.0 0.91 41.87 383.0 \n", " 15.79 119.0 25.0 0.47 40.40 190.0 \n", " 15.77 210.0 44.0 0.83 53.29 441.0 \n", " 15.70 222.0 46.0 0.88 113.19 994.0 \n", " 15.65 182.0 38.0 0.72 51.10 369.0 \n", " 15.63 153.0 32.0 0.61 71.94 438.0 \n", " 15.58 155.0 33.0 0.62 89.73 556.0 \n", " 15.57 149.0 31.0 0.59 43.33 257.0 \n", " 15.48 110.0 23.0 0.44 81.71 360.0 \n", " 15.47 190.0 40.0 0.76 73.43 560.0 \n", " 15.44 226.0 48.0 0.91 40.24 366.0 \n", " 15.41 168.0 36.0 0.68 55.78 377.0 \n", " 15.28 120.0 26.0 0.49 50.65 247.0 \n", " 15.20 141.0 30.0 0.58 70.68 408.0 " ] }, "execution_count": 17, "metadata": {}, "output_type": "execute_result" } ], "source": [ "top(rides, 'mph') # Fastest rides (of more than 20 miles, that I sampled into database)" ] }, { "cell_type": "code", "execution_count": 18, "metadata": {}, "outputs": [ { "data": { "text/html": [ "
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titlehoursmilesfeetmphvamfpmipctkmsmeters
PCH Pescadero to Bean Hollow0.142.775119.79111.018.00.354.4616.0
Highway 1 Cascanoa to Cascade0.091.618917.89301.055.01.052.5927.0
Vickrey Fruitvale0.060.996816.50345.069.01.301.5921.0
Highway 9 Mantalvo0.030.453515.00356.078.01.470.7211.0
Highway 9 Mantalvo0.030.453515.00356.078.01.470.7211.0
The Boneyard0.101.4813514.80411.091.01.732.3841.0
Vickrey Fruitvale0.070.996814.14296.069.01.301.5921.0
Sand Hill Alpine to 2800.121.6718013.92457.0108.02.042.6955.0
Canada to College0.101.3711913.70363.087.01.652.2036.0
Foothill Homestead0.091.2212613.56427.0103.01.961.9638.0
The Boneyard0.111.4813513.45374.091.01.732.3841.0
Kaboom Portola Rd0.050.6710213.40622.0152.02.881.0831.0
Woodside Climb0.131.7129513.15692.0173.03.272.7590.0
Sand Hill Alpine to 2800.131.6718012.85422.0108.02.042.6955.0
Alpine Westridge0.060.769912.67503.0130.02.471.2230.0
Alpine Westridge0.060.769912.67503.0130.02.471.2230.0
Stanford Ave0.050.638512.60518.0135.02.561.0126.0
Canada to College0.111.3711912.45330.087.01.652.2036.0
Sand Hill 280 to horse0.040.499512.25724.0194.03.670.7929.0
Stevens Country Park0.101.2211212.20341.092.01.741.9634.0
\n", "
" ], "text/plain": [ " title hours miles feet mph vam fpmi \\\n", " PCH Pescadero to Bean Hollow 0.14 2.77 51 19.79 111.0 18.0 \n", " Highway 1 Cascanoa to Cascade 0.09 1.61 89 17.89 301.0 55.0 \n", " Vickrey Fruitvale 0.06 0.99 68 16.50 345.0 69.0 \n", " Highway 9 Mantalvo 0.03 0.45 35 15.00 356.0 78.0 \n", " Highway 9 Mantalvo 0.03 0.45 35 15.00 356.0 78.0 \n", " The Boneyard 0.10 1.48 135 14.80 411.0 91.0 \n", " Vickrey Fruitvale 0.07 0.99 68 14.14 296.0 69.0 \n", " Sand Hill Alpine to 280 0.12 1.67 180 13.92 457.0 108.0 \n", " Canada to College 0.10 1.37 119 13.70 363.0 87.0 \n", " Foothill Homestead 0.09 1.22 126 13.56 427.0 103.0 \n", " The Boneyard 0.11 1.48 135 13.45 374.0 91.0 \n", " Kaboom Portola Rd 0.05 0.67 102 13.40 622.0 152.0 \n", " Woodside Climb 0.13 1.71 295 13.15 692.0 173.0 \n", " Sand Hill Alpine to 280 0.13 1.67 180 12.85 422.0 108.0 \n", " Alpine Westridge 0.06 0.76 99 12.67 503.0 130.0 \n", " Alpine Westridge 0.06 0.76 99 12.67 503.0 130.0 \n", " Stanford Ave 0.05 0.63 85 12.60 518.0 135.0 \n", " Canada to College 0.11 1.37 119 12.45 330.0 87.0 \n", " Sand Hill 280 to horse 0.04 0.49 95 12.25 724.0 194.0 \n", " Stevens Country Park 0.10 1.22 112 12.20 341.0 92.0 \n", "\n", " pct kms meters \n", " 0.35 4.46 16.0 \n", " 1.05 2.59 27.0 \n", " 1.30 1.59 21.0 \n", " 1.47 0.72 11.0 \n", " 1.47 0.72 11.0 \n", " 1.73 2.38 41.0 \n", " 1.30 1.59 21.0 \n", " 2.04 2.69 55.0 \n", " 1.65 2.20 36.0 \n", " 1.96 1.96 38.0 \n", " 1.73 2.38 41.0 \n", " 2.88 1.08 31.0 \n", " 3.27 2.75 90.0 \n", " 2.04 2.69 55.0 \n", " 2.47 1.22 30.0 \n", " 2.47 1.22 30.0 \n", " 2.56 1.01 26.0 \n", " 1.65 2.20 36.0 \n", " 3.67 0.79 29.0 \n", " 1.74 1.96 34.0 " ] }, "execution_count": 18, "metadata": {}, "output_type": "execute_result" } ], "source": [ "top(segments, 'mph') # Fastest segments (there are no descent segments in the database)" ] }, { "cell_type": "code", "execution_count": 19, "metadata": {}, "outputs": [ { "data": { "text/html": [ "
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titlehoursmilesfeetmphvamfpmipctkmsmeters
West Alpine full1.397.3818875.31414.0256.04.8411.87575.0
Kings Greer to Skyline0.783.9215365.03600.0392.07.426.31468.0
Kings Greer to Skyline0.813.9215364.84578.0392.07.426.31468.0
Old La Honda (Bridge to Stop)0.483.3312556.94797.0377.07.145.36383.0
Old La Honda (Bridge to Stop)0.513.3312556.53750.0377.07.145.36383.0
Alma Mountain Charlie0.533.128755.89503.0280.05.315.02267.0
Kings half way0.462.898206.28543.0284.05.374.65250.0
Kings half way0.502.898205.78500.0284.05.374.65250.0
Alpine Portola to top Joaquin0.573.528016.18428.0228.04.315.66244.0
Alpine Portola to top Joaquin0.583.528016.07421.0228.04.315.66244.0
Tunitas steep0.271.205994.44676.0499.09.451.93183.0
Tunitas steep0.251.205994.80730.0499.09.451.93183.0
Haskins0.301.515665.03575.0375.07.102.43173.0
Haskins0.311.515664.87557.0375.07.102.43173.0
Coe Second Switchback to flat0.221.004834.55669.0483.09.151.61147.0
Lower Redwood Gulch0.221.034744.68657.0460.08.721.66144.0
Alpine Willowbrook to Joaquin0.292.274617.83485.0203.03.853.65141.0
Alpine Willowbrook to Joaquin0.282.274618.11502.0203.03.853.65141.0
Lobitas Creek0.200.964304.80655.0448.08.481.54131.0
Tunitas lower climb0.221.304215.91583.0324.06.132.09128.0
\n", "
" ], "text/plain": [ " title hours miles feet mph vam fpmi pct \\\n", " West Alpine full 1.39 7.38 1887 5.31 414.0 256.0 4.84 \n", " Kings Greer to Skyline 0.78 3.92 1536 5.03 600.0 392.0 7.42 \n", " Kings Greer to Skyline 0.81 3.92 1536 4.84 578.0 392.0 7.42 \n", " Old La Honda (Bridge to Stop) 0.48 3.33 1255 6.94 797.0 377.0 7.14 \n", " Old La Honda (Bridge to Stop) 0.51 3.33 1255 6.53 750.0 377.0 7.14 \n", " Alma Mountain Charlie 0.53 3.12 875 5.89 503.0 280.0 5.31 \n", " Kings half way 0.46 2.89 820 6.28 543.0 284.0 5.37 \n", " Kings half way 0.50 2.89 820 5.78 500.0 284.0 5.37 \n", " Alpine Portola to top Joaquin 0.57 3.52 801 6.18 428.0 228.0 4.31 \n", " Alpine Portola to top Joaquin 0.58 3.52 801 6.07 421.0 228.0 4.31 \n", " Tunitas steep 0.27 1.20 599 4.44 676.0 499.0 9.45 \n", " Tunitas steep 0.25 1.20 599 4.80 730.0 499.0 9.45 \n", " Haskins 0.30 1.51 566 5.03 575.0 375.0 7.10 \n", " Haskins 0.31 1.51 566 4.87 557.0 375.0 7.10 \n", " Coe Second Switchback to flat 0.22 1.00 483 4.55 669.0 483.0 9.15 \n", " Lower Redwood Gulch 0.22 1.03 474 4.68 657.0 460.0 8.72 \n", " Alpine Willowbrook to Joaquin 0.29 2.27 461 7.83 485.0 203.0 3.85 \n", " Alpine Willowbrook to Joaquin 0.28 2.27 461 8.11 502.0 203.0 3.85 \n", " Lobitas Creek 0.20 0.96 430 4.80 655.0 448.0 8.48 \n", " Tunitas lower climb 0.22 1.30 421 5.91 583.0 324.0 6.13 \n", "\n", " kms meters \n", " 11.87 575.0 \n", " 6.31 468.0 \n", " 6.31 468.0 \n", " 5.36 383.0 \n", " 5.36 383.0 \n", " 5.02 267.0 \n", " 4.65 250.0 \n", " 4.65 250.0 \n", " 5.66 244.0 \n", " 5.66 244.0 \n", " 1.93 183.0 \n", " 1.93 183.0 \n", " 2.43 173.0 \n", " 2.43 173.0 \n", " 1.61 147.0 \n", " 1.66 144.0 \n", " 3.65 141.0 \n", " 3.65 141.0 \n", " 1.54 131.0 \n", " 2.09 128.0 " ] }, "execution_count": 19, "metadata": {}, "output_type": "execute_result" } ], "source": [ "top(segments, 'feet') # Biggest climbing segments" ] }, { "cell_type": "code", "execution_count": 20, "metadata": {}, "outputs": [ { "data": { "text/html": [ "
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titlehoursmilesfeetmphvamfpmipctkmsmeters
Redwood Gulch hits0.060.181513.00767.0839.015.890.2946.0
Valparaiso steep0.040.181454.501105.0806.015.260.2944.0
Valparaiso steep0.050.181453.60884.0806.015.260.2944.0
Limantour steepest0.090.201592.22538.0795.015.060.3248.0
Joaquin0.100.332543.30774.0770.014.580.5377.0
Joaquin0.090.332543.67860.0770.014.580.5377.0
Entrance Way Hill Repeats0.020.10765.001158.0760.014.390.1623.0
Stirrup Wall0.060.171252.83635.0735.013.930.2738.0
Stirrup Wall0.080.171252.12476.0735.013.930.2738.0
Westridge 3min0.080.372404.62914.0649.012.290.6073.0
Westridge 3min0.090.372404.11813.0649.012.290.6073.0
Limantour Spit0.090.473035.221026.0645.012.210.7692.0
Klamath Dr.0.020.12776.001173.0642.012.150.1923.0
green valley kicker0.080.291783.62678.0614.011.620.4754.0
Redwood Gulch wall0.110.432583.91715.0600.011.360.6979.0
Paloma Climb0.020.14827.001250.0586.011.090.2325.0
Try not to fall back0.210.714103.38595.0577.010.941.14125.0
Westridge0.140.683854.86838.0566.010.721.09117.0
Westridge0.160.683854.25733.0566.010.721.09117.0
Stair Step0.090.321753.56593.0547.010.360.5153.0
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" ], "text/plain": [ " title hours miles feet mph vam fpmi pct \\\n", " Redwood Gulch hits 0.06 0.18 151 3.00 767.0 839.0 15.89 \n", " Valparaiso steep 0.04 0.18 145 4.50 1105.0 806.0 15.26 \n", " Valparaiso steep 0.05 0.18 145 3.60 884.0 806.0 15.26 \n", " Limantour steepest 0.09 0.20 159 2.22 538.0 795.0 15.06 \n", " Joaquin 0.10 0.33 254 3.30 774.0 770.0 14.58 \n", " Joaquin 0.09 0.33 254 3.67 860.0 770.0 14.58 \n", " Entrance Way Hill Repeats 0.02 0.10 76 5.00 1158.0 760.0 14.39 \n", " Stirrup Wall 0.06 0.17 125 2.83 635.0 735.0 13.93 \n", " Stirrup Wall 0.08 0.17 125 2.12 476.0 735.0 13.93 \n", " Westridge 3min 0.08 0.37 240 4.62 914.0 649.0 12.29 \n", " Westridge 3min 0.09 0.37 240 4.11 813.0 649.0 12.29 \n", " Limantour Spit 0.09 0.47 303 5.22 1026.0 645.0 12.21 \n", " Klamath Dr. 0.02 0.12 77 6.00 1173.0 642.0 12.15 \n", " green valley kicker 0.08 0.29 178 3.62 678.0 614.0 11.62 \n", " Redwood Gulch wall 0.11 0.43 258 3.91 715.0 600.0 11.36 \n", " Paloma Climb 0.02 0.14 82 7.00 1250.0 586.0 11.09 \n", " Try not to fall back 0.21 0.71 410 3.38 595.0 577.0 10.94 \n", " Westridge 0.14 0.68 385 4.86 838.0 566.0 10.72 \n", " Westridge 0.16 0.68 385 4.25 733.0 566.0 10.72 \n", " Stair Step 0.09 0.32 175 3.56 593.0 547.0 10.36 \n", "\n", " kms meters \n", " 0.29 46.0 \n", " 0.29 44.0 \n", " 0.29 44.0 \n", " 0.32 48.0 \n", " 0.53 77.0 \n", " 0.53 77.0 \n", " 0.16 23.0 \n", " 0.27 38.0 \n", " 0.27 38.0 \n", " 0.60 73.0 \n", " 0.60 73.0 \n", " 0.76 92.0 \n", " 0.19 23.0 \n", " 0.47 54.0 \n", " 0.69 79.0 \n", " 0.23 25.0 \n", " 1.14 125.0 \n", " 1.09 117.0 \n", " 1.09 117.0 \n", " 0.51 53.0 " ] }, "execution_count": 20, "metadata": {}, "output_type": "execute_result" } ], "source": [ "top(segments, 'pct') # Steepest climbs" ] }, { "cell_type": "code", "execution_count": 21, "metadata": {}, "outputs": [ { "data": { "text/html": [ "
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dateyeartitlehoursmilesfeetmphvamfpmipctkmsmeters
Fri, 1/9/20122012Otago Rail Trail Century7.87102.41228613.0189.022.00.42164.78697.0
Sat, 5/7/20222022Wine Country Century6.65100.26525315.08241.052.00.99161.321601.0
Thu, 6/14/20122012Coyote Creek Century with Juliet8.14100.07151312.2957.015.00.29161.01461.0
Sat, 5/13/20172017Morgan Hill iCare Classic7.46100.05459613.41188.046.00.87160.981401.0
Sat, 3/9/20242024Millbrae / San Bruno / Sawyer Camp Trail / Bay...8.1298.52489612.13184.050.00.94158.521492.0
Sat, 5/12/20182018ICare Classic, Morgan Hill6.8091.29416013.42186.046.00.86146.891268.0
Sat, 5/6/20172017Wine Country Century7.2689.49524612.33220.059.01.11143.991599.0
Fri, 8/10/20182018Bike Ride Northwest Day 66.2484.70438013.57214.052.00.98136.281335.0
Fri, 2/28/20202020Sawyer Camp Trail6.4184.43344813.17164.041.00.77135.851051.0
Wed, 6/7/20232023Los Altos7.0581.54211011.5791.026.00.49131.20643.0
Sun, 8/30/20202020Los Gatos6.3680.92210012.72101.026.00.49130.20640.0
Sat, 9/17/20222022San Gregorio / Tunitas6.5680.53601512.28279.075.01.41129.571833.0
Sat, 10/1/20162016Half Moon Bay overnight campout7.5180.07603910.66245.075.01.43128.831841.0
Mon, 10/5/20202020Half way around the bay on bay trail6.4480.0554112.4326.07.00.13128.80165.0
Sun, 6/21/20202020Sawyer Camp Trail6.5979.78173812.1180.022.00.41128.37530.0
Thu, 1/5/20122012Tekapo Lake to Omarama New Zealand5.4679.42214514.55120.027.00.51127.79654.0
Tue, 8/7/20182018Bike Ride Northwest Day 36.1878.96509212.78251.064.01.22127.051552.0
Sun, 6/15/20142014Sierra to the Sea Day 15.5778.53477714.10261.061.01.15126.351456.0
Sun, 2/7/20212021Saratoga / Campbell5.8978.38227013.31117.029.00.55126.11692.0
Sat, 7/2/20222022Bear Gulch, West Side6.4977.73699111.98328.090.01.70125.072131.0
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" ], "text/plain": [ " date year title \\\n", " Fri, 1/9/2012 2012 Otago Rail Trail Century \n", " Sat, 5/7/2022 2022 Wine Country Century \n", " Thu, 6/14/2012 2012 Coyote Creek Century with Juliet \n", " Sat, 5/13/2017 2017 Morgan Hill iCare Classic \n", " Sat, 3/9/2024 2024 Millbrae / San Bruno / Sawyer Camp Trail / Bay... \n", " Sat, 5/12/2018 2018 ICare Classic, Morgan Hill \n", " Sat, 5/6/2017 2017 Wine Country Century \n", " Fri, 8/10/2018 2018 Bike Ride Northwest Day 6 \n", " Fri, 2/28/2020 2020 Sawyer Camp Trail \n", " Wed, 6/7/2023 2023 Los Altos \n", " Sun, 8/30/2020 2020 Los Gatos \n", " Sat, 9/17/2022 2022 San Gregorio / Tunitas \n", " Sat, 10/1/2016 2016 Half Moon Bay overnight campout \n", " Mon, 10/5/2020 2020 Half way around the bay on bay trail \n", " Sun, 6/21/2020 2020 Sawyer Camp Trail \n", " Thu, 1/5/2012 2012 Tekapo Lake to Omarama New Zealand \n", " Tue, 8/7/2018 2018 Bike Ride Northwest Day 3 \n", " Sun, 6/15/2014 2014 Sierra to the Sea Day 1 \n", " Sun, 2/7/2021 2021 Saratoga / Campbell \n", " Sat, 7/2/2022 2022 Bear Gulch, West Side \n", "\n", " hours miles feet mph vam fpmi pct kms meters \n", " 7.87 102.41 2286 13.01 89.0 22.0 0.42 164.78 697.0 \n", " 6.65 100.26 5253 15.08 241.0 52.0 0.99 161.32 1601.0 \n", " 8.14 100.07 1513 12.29 57.0 15.0 0.29 161.01 461.0 \n", " 7.46 100.05 4596 13.41 188.0 46.0 0.87 160.98 1401.0 \n", " 8.12 98.52 4896 12.13 184.0 50.0 0.94 158.52 1492.0 \n", " 6.80 91.29 4160 13.42 186.0 46.0 0.86 146.89 1268.0 \n", " 7.26 89.49 5246 12.33 220.0 59.0 1.11 143.99 1599.0 \n", " 6.24 84.70 4380 13.57 214.0 52.0 0.98 136.28 1335.0 \n", " 6.41 84.43 3448 13.17 164.0 41.0 0.77 135.85 1051.0 \n", " 7.05 81.54 2110 11.57 91.0 26.0 0.49 131.20 643.0 \n", " 6.36 80.92 2100 12.72 101.0 26.0 0.49 130.20 640.0 \n", " 6.56 80.53 6015 12.28 279.0 75.0 1.41 129.57 1833.0 \n", " 7.51 80.07 6039 10.66 245.0 75.0 1.43 128.83 1841.0 \n", " 6.44 80.05 541 12.43 26.0 7.0 0.13 128.80 165.0 \n", " 6.59 79.78 1738 12.11 80.0 22.0 0.41 128.37 530.0 \n", " 5.46 79.42 2145 14.55 120.0 27.0 0.51 127.79 654.0 \n", " 6.18 78.96 5092 12.78 251.0 64.0 1.22 127.05 1552.0 \n", " 5.57 78.53 4777 14.10 261.0 61.0 1.15 126.35 1456.0 \n", " 5.89 78.38 2270 13.31 117.0 29.0 0.55 126.11 692.0 \n", " 6.49 77.73 6991 11.98 328.0 90.0 1.70 125.07 2131.0 " ] }, "execution_count": 21, "metadata": {}, "output_type": "execute_result" } ], "source": [ "top(rides, 'miles') # Longest rides" ] } ], "metadata": { "kernelspec": { "display_name": "Python 3 (ipykernel)", "language": "python", "name": "python3" }, "language_info": { "codemirror_mode": { "name": "ipython", "version": 3 }, "file_extension": ".py", "mimetype": "text/x-python", "name": "python", "nbconvert_exporter": "python", "pygments_lexer": "ipython3", "version": "3.9.12" }, "toc-autonumbering": true, "toc-showmarkdowntxt": false }, "nbformat": 4, "nbformat_minor": 4 }