{ "cells": [ { "cell_type": "markdown", "metadata": {}, "source": [ "
Peter Norvig, Oct 2017
Last update: May 2024
\n", "\n", "# Bicycling Statistics\n", "\n", "Bicycling is a great way to get some exercise, enjoy the outside, and go places. This notebook tracks [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": "code", "execution_count": 1, "metadata": {}, "outputs": [], "source": [ "%run BikeCode.ipynb" ] }, { "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 (also, Covid). 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": 2, "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": 2, "metadata": {}, "output_type": "execute_result" } ], "source": [ "yearly" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "And here's the same data on a per day basis, assuming I ride 6 days a week, 50 weeks a year:" ] }, { "cell_type": "code", "execution_count": 3, "metadata": {}, "outputs": [ { "data": { "text/html": [ "
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yearhoursmilesfeetmphvamfpmipctkmsmeters
20231.821.1810.311.66137.038.00.7333.9247.0
20221.820.11207.711.31207.060.01.1432.3368.1
20211.620.2655.412.36122.032.00.6132.5199.8
20201.517.8315.912.1766.018.00.3428.696.3
20191.620.1499.312.6396.025.00.4732.3152.2
20181.620.3528.812.82102.026.00.4932.7161.2
20171.924.5673.712.97109.027.00.5239.5205.3
20161.621.1671.513.03126.032.00.6034.0204.7
20151.418.2699.512.98152.038.00.7329.2213.2
20140.68.2394.912.92189.048.00.9113.2120.4
\n", "
" ], "text/plain": [ " year hours miles feet mph vam fpmi pct kms meters\n", " 2023 1.8 21.1 810.3 11.66 137.0 38.0 0.73 33.9 247.0\n", " 2022 1.8 20.1 1207.7 11.31 207.0 60.0 1.14 32.3 368.1\n", " 2021 1.6 20.2 655.4 12.36 122.0 32.0 0.61 32.5 199.8\n", " 2020 1.5 17.8 315.9 12.17 66.0 18.0 0.34 28.6 96.3\n", " 2019 1.6 20.1 499.3 12.63 96.0 25.0 0.47 32.3 152.2\n", " 2018 1.6 20.3 528.8 12.82 102.0 26.0 0.49 32.7 161.2\n", " 2017 1.9 24.5 673.7 12.97 109.0 27.0 0.52 39.5 205.3\n", " 2016 1.6 21.1 671.5 13.03 126.0 32.0 0.60 34.0 204.7\n", " 2015 1.4 18.2 699.5 12.98 152.0 38.0 0.73 29.2 213.2\n", " 2014 0.6 8.2 394.9 12.92 189.0 48.0 0.91 13.2 120.4" ] }, "execution_count": 3, "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": 4, "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": 4, "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 **name** of a place (and maybe the **county** it is in), the **total** number of miles of roads and trails in the place, the number of miles I have **done**, the percentage (**pct**) done, the **badge** I have been awarded, and the number of miles to go **to next badge**.\n", "\n", "First the big places (counties and countries, etc.), then the small places (cities and state parks, etc.)" ] }, { "cell_type": "code", "execution_count": 5, "metadata": {}, "outputs": [ { "data": { "text/html": [ "
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nametotaldonepctbadgeto next badge
San Mateo County2814.01,87566.64%50%657 mi to 90%
Santa Clara County7569.02,69535.60%25%1,090 mi to 50%
Alameda County5818.01,03817.84%none417 mi to 25%
Marin County2333.025510.94%none328 mi to 25%
San Francisco County1217.01139.26%none192 mi to 25%
Napa County1609.01448.92%none259 mi to 25%
Santa Cruz County2718.01947.12%none486 mi to 25%
Sonoma County4895.03186.50%none906 mi to 25%
Contra Costa County5945.02263.80%none1,260 mi to 25%
California377037.07,3551.95%none186 mi to 2%
USA6406754.07,9320.1238%none4,881 mi to 0.2%
Earth41974536.07,6780.0183%none717 mi to 0.02%
\n", "
" ], "text/plain": [ " name total done pct badge to next badge\n", " San Mateo County 2814.0 1,875 66.64% 50% 657 mi to 90%\n", " Santa Clara County 7569.0 2,695 35.60% 25% 1,090 mi to 50%\n", " Alameda County 5818.0 1,038 17.84% none 417 mi to 25%\n", " Marin County 2333.0 255 10.94% none 328 mi to 25%\n", " San Francisco County 1217.0 113 9.26% none 192 mi to 25%\n", " Napa County 1609.0 144 8.92% none 259 mi to 25%\n", " Santa Cruz County 2718.0 194 7.12% none 486 mi to 25%\n", " Sonoma County 4895.0 318 6.50% none 906 mi to 25%\n", " Contra Costa County 5945.0 226 3.80% none 1,260 mi to 25%\n", " California 377037.0 7,355 1.95% none 186 mi to 2%\n", " USA 6406754.0 7,932 0.1238% none 4,881 mi to 0.2%\n", " Earth 41974536.0 7,678 0.0183% none 717 mi to 0.02%" ] }, "execution_count": 5, "metadata": {}, "output_type": "execute_result" } ], "source": [ "big_places" ] }, { "cell_type": "code", "execution_count": 6, "metadata": {}, "outputs": [ { "data": { "text/html": [ "
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namecountytotaldonepctbadgeto next badge
AthertonSMC56.3056100%99%
Menlo OaksSMC3.503.5100%99%
Kensington SquareSMC0.600.6100%99%
LaderaSMC8.108.1100%99%
Windy Hill PreserveSMC4.104.1100%99%
Los Trancos OSPSMC0.300.3100%99%
Los Trancos WoodsSMC5.305.3100%99%
North Fair OaksSMC26.7027100%99%
Palomar ParkSMC4.004.0100%99%
Sequoia TractSMC11.0011100%99%
Foothills OS PreserveSCC1.101.1100%99%
Emerald Lake HillsSMC24.602599.96%99%
East Palo AltoSMC48.304899.95%99%
LoyolaSCC18.301899.94%99%
Portola ValleySMC48.204899.93%99%
Menlo ParkSMC139.5013999.90%99%
Los AltosSCC138.2013899.89%99%
WoodsideSMC75.207599.83%99%
Mountain ViewSCC208.1020899.81%99%
Los Altos HillsSCC91.309199.78%99%
West Menlo ParkSMC11.201199.75%99%
Redwood CitySMC240.5024099.73%99%
Sky LondaSMC11.801299.70%99%
Palo AltoSCC297.2029699.51%99%
San CarlosSMC99.009999.50%99%
Foster CitySMC150.0014999.40%99%
StanfordSCC82.538299.13%99%
Burleigh Murray ParkSMC2.102.095.08%90%0.1 mi to 99%
San Mateo HighlandsSMC18.001793.50%90%1.0 mi to 99%
BelmontSMC98.108788.39%75%1.6 mi to 90%
Skyline Ridge OSPSMC0.800.676.40%75%0.1 mi to 90%
Portola Redwoods SPSMC2.902.274.30%50%0.5 mi to 90%
Rosie Riveter ParkCCC5.504.073.20%50%0.9 mi to 90%
Burlingame HillsSMC6.004.371.50%50%1.1 mi to 90%
San Francisco Bay TrailSCC260.8017968.47%50%56 mi to 90%
Coal Creek PreserveSMC3.902.666.70%50%0.9 mi to 90%
ColmaSMC13.709.166.24%50%3.3 mi to 90%
MontaraSMC27.801760.20%50%8.3 mi to 90%
Russian Ridge PreserveSMC12.207.359.50%50%3.7 mi to 90%
BurlingameSMC88.405056.88%50%29 mi to 90%
SunnyvaleSCC357.0019755.30%50%124 mi to 90%
San MateoSMC256.0014054.60%50%91 mi to 90%
CupertinoSCC172.009454.42%50%61 mi to 90%
SaratogaSCC180.009753.70%50%65 mi to 90%
HillsboroughSMC85.304553.10%50%31 mi to 90%
Half Moon Bay State BeachSMC4.402.352.40%50%1.7 mi to 90%
Monte SerenoSCC20.401152.40%50%7.7 mi to 90%
Los GatosSCC148.007752.04%50%56 mi to 90%
NewarkALA147.007651.60%50%56 mi to 90%
MillbraeSMC65.003351.30%50%25 mi to 90%
Castle Rock State ParkSCC11.205.751.20%50%4.3 mi to 90%
BrisbaneSMC40.902150.40%50%16 mi to 90%
EdenvaleSCC30.001447.70%25%0.7 mi to 50%
BarangarooNSW1.700.847.30%25%0.0 mi to 50%
GardnerSCC23.401147.20%25%0.7 mi to 50%
Long Ridge PreserveSMC11.005.045.10%25%0.5 mi to 50%
Presidio TerraceSFC2.801.243.90%25%0.2 mi to 50%
Moss BeachSMC19.708.643.69%25%1.2 mi to 50%
El GranadaSMC49.202143.60%25%3.1 mi to 50%
Hayward AcresALA3.501.543.30%25%0.2 mi to 50%
San LorenzoALA55.502340.95%25%5.0 mi to 50%
Lincoln ParkSFC4.501.839.60%25%0.5 mi to 50%
Communications HillSCC27.801139.50%25%2.9 mi to 50%
Purisima Creek PreserveSMC16.506.439.00%25%1.8 mi to 50%
Mt Tamalpais State ParkMAR31.701238.70%25%3.6 mi to 50%
BroadmoorSMC8.803.438.26%25%1.0 mi to 50%
South BeachSFC4.801.837.40%25%0.6 mi to 50%
Muir BeachMAR4.601.737.10%25%0.6 mi to 50%
Lake StreetSFC3.901.436.80%25%0.5 mi to 50%
Spartan KeyesSCC64.302436.80%25%8.5 mi to 50%
MilpitasSCC224.008236.70%25%30 mi to 50%
AshlandALA35.101336.10%25%4.9 mi to 50%
Willow GlenSCC81.602936.00%25%11 mi to 50%
San BrunoSMC114.004034.90%25%17 mi to 50%
Santa ClaraSCC348.0012134.80%25%53 mi to 50%
MITMAS9.603.334.70%25%1.5 mi to 50%
FremontALA780.2026834.30%25%122 mi to 50%
Millers PointNSW3.201.134.30%25%0.5 mi to 50%
Seven TreesSCC40.901434.00%25%6.5 mi to 50%
Half Moon BaySMC68.002334.00%25%11 mi to 50%
ParkviewSCC42.501433.70%25%6.9 mi to 50%
Union CityALA208.807033.37%25%35 mi to 50%
PacificaSMC150.905033.20%25%25 mi to 50%
BranhamSCC44.001533.20%25%7.4 mi to 50%
HaywardALA444.5014833.20%25%75 mi to 50%
Stinson BeachMAR11.203.732.90%25%1.9 mi to 50%
Marin Headlands GGNRAMAR65.702131.90%25%12 mi to 50%
San MartinSCC35.301131.85%25%6.4 mi to 50%
South San FranciscoSMC185.305730.98%25%35 mi to 50%
Willow Glen SouthSCC63.302030.90%25%12 mi to 50%
Forest of Nisene Marks SPSCC44.001430.70%25%8.5 mi to 50%
CampbellSCC119.003630.30%25%23 mi to 50%
Butano State ParkSMC15.204.630.10%25%3.0 mi to 50%
Golden Gate ParkSFC40.801229.40%25%8.4 mi to 50%
SeacliffSFC4.101.229.30%25%0.8 mi to 50%
FairviewALA34.401029.20%25%7.2 mi to 50%
Dawes PointNSW1.800.529.20%25%0.4 mi to 50%
Bay Area Ridge TrailSMC395.6011328.68%25%84 mi to 50%
San JoseSCC2618.7074928.62%25%560 mi to 50%
Daly CitySMC148.104228.27%25%32 mi to 50%
San LeandroALA230.606528.10%25%51 mi to 50%
CherrylandALA20.905.827.80%25%4.6 mi to 50%
El Corte de Madera OSPSMC34.549.326.88%25%8.0 mi to 50%
Mokelumne HillCAL14.703.926.80%25%3.4 mi to 50%
Presidio National ParkSFC43.501226.70%25%10 mi to 50%
GilroySCC188.905026.40%25%45 mi to 50%
Castro ValleyALA192.505026.10%25%46 mi to 50%
GuernevilleSON22.705.423.60%none0.3 mi to 25%
Presidio HeightsSFC6.501.421.60%none0.2 mi to 25%
PanhandleSFC7.301.520.60%none0.3 mi to 25%
Polk GulchSFC4.000.718.20%none0.3 mi to 25%
Balboa TerraceSFC3.400.618.20%none0.2 mi to 25%
Cole ValleySFC1.700.318.00%none0.1 mi to 25%
HealdsburgSON53.709.617.80%none3.9 mi to 25%
Bodega BaySON28.904.917.00%none2.3 mi to 25%
Forest HillSFC6.101.015.90%none0.6 mi to 25%
Northern WaterfrontSFC5.600.915.50%none0.5 mi to 25%
Aquatic Park Fort MasonSFC6.401.015.40%none0.6 mi to 25%
Little HollywoodSFC3.700.615.20%none0.4 mi to 25%
Clarendon HeightsSFC6.000.914.20%none0.6 mi to 25%
Fisherman's WharfSFC6.200.913.80%none0.7 mi to 25%
Sutro HeightsSFC7.100.913.20%none0.8 mi to 25%
Ashbury HeightsSFC3.700.513.00%none0.4 mi to 25%
SausalitoMAR32.704.212.90%none4.0 mi to 25%
Corte MaderaMAR51.006.612.90%none6.2 mi to 25%
DogpatchSFC5.100.612.30%none0.6 mi to 25%
AlamedaALA206.702512.20%none26 mi to 25%
Cow HollowSFC12.001.411.90%none1.6 mi to 25%
Pacific HeightsSFC18.001.910.70%none2.6 mi to 25%
Golden Gate HeightsSFC17.801.910.70%none2.5 mi to 25%
Financial DistrictSFC9.401.010.20%none1.4 mi to 25%
Mill ValleyMAR92.208.49.10%none15 mi to 25%
Mission BaySFC13.801.28.60%none2.3 mi to 25%
BerkeleyALA260.30207.80%none45 mi to 25%
EmeryvilleALA28.102.27.70%none4.9 mi to 25%
AlbanyALA42.702.96.80%none7.8 mi to 25%
CambridgeMAS180.80116.20%none34 mi to 25%
Central WaterfrontSFC10.200.66.00%none1.9 mi to 25%
San RafaelMAR260.009.63.70%none55 mi to 25%
\n", "
" ], "text/plain": [ " name county total done pct badge \\\n", " Atherton SMC 56.30 56 100% 99% \n", " Menlo Oaks SMC 3.50 3.5 100% 99% \n", " Kensington Square SMC 0.60 0.6 100% 99% \n", " Ladera SMC 8.10 8.1 100% 99% \n", " Windy Hill Preserve SMC 4.10 4.1 100% 99% \n", " Los Trancos OSP SMC 0.30 0.3 100% 99% \n", " Los Trancos Woods SMC 5.30 5.3 100% 99% \n", " North Fair Oaks SMC 26.70 27 100% 99% \n", " Palomar Park SMC 4.00 4.0 100% 99% \n", " Sequoia Tract SMC 11.00 11 100% 99% \n", " Foothills OS Preserve SCC 1.10 1.1 100% 99% \n", " Emerald Lake Hills SMC 24.60 25 99.96% 99% \n", " East Palo Alto SMC 48.30 48 99.95% 99% \n", " Loyola SCC 18.30 18 99.94% 99% \n", " Portola Valley SMC 48.20 48 99.93% 99% \n", " Menlo Park SMC 139.50 139 99.90% 99% \n", " Los Altos SCC 138.20 138 99.89% 99% \n", " Woodside SMC 75.20 75 99.83% 99% \n", " Mountain View SCC 208.10 208 99.81% 99% \n", " Los Altos Hills SCC 91.30 91 99.78% 99% \n", " West Menlo Park SMC 11.20 11 99.75% 99% \n", " Redwood City SMC 240.50 240 99.73% 99% \n", " Sky Londa SMC 11.80 12 99.70% 99% \n", " Palo Alto SCC 297.20 296 99.51% 99% \n", " San Carlos SMC 99.00 99 99.50% 99% \n", " Foster City SMC 150.00 149 99.40% 99% \n", " Stanford SCC 82.53 82 99.13% 99% \n", " Burleigh Murray Park SMC 2.10 2.0 95.08% 90% \n", " San Mateo Highlands SMC 18.00 17 93.50% 90% \n", " Belmont SMC 98.10 87 88.39% 75% \n", " Skyline Ridge OSP SMC 0.80 0.6 76.40% 75% \n", " Portola Redwoods SP SMC 2.90 2.2 74.30% 50% \n", " Rosie Riveter Park CCC 5.50 4.0 73.20% 50% \n", " Burlingame Hills SMC 6.00 4.3 71.50% 50% \n", " San Francisco Bay Trail SCC 260.80 179 68.47% 50% \n", " Coal Creek Preserve SMC 3.90 2.6 66.70% 50% \n", " Colma SMC 13.70 9.1 66.24% 50% \n", " Montara SMC 27.80 17 60.20% 50% \n", " Russian Ridge Preserve SMC 12.20 7.3 59.50% 50% \n", " Burlingame SMC 88.40 50 56.88% 50% \n", " Sunnyvale SCC 357.00 197 55.30% 50% \n", " San Mateo SMC 256.00 140 54.60% 50% \n", " Cupertino SCC 172.00 94 54.42% 50% \n", " Saratoga SCC 180.00 97 53.70% 50% \n", " Hillsborough SMC 85.30 45 53.10% 50% \n", " Half Moon Bay State Beach SMC 4.40 2.3 52.40% 50% \n", " Monte Sereno SCC 20.40 11 52.40% 50% \n", " Los Gatos SCC 148.00 77 52.04% 50% \n", " Newark ALA 147.00 76 51.60% 50% \n", " Millbrae SMC 65.00 33 51.30% 50% \n", " Castle Rock State Park SCC 11.20 5.7 51.20% 50% \n", " Brisbane SMC 40.90 21 50.40% 50% \n", " Edenvale SCC 30.00 14 47.70% 25% \n", " Barangaroo NSW 1.70 0.8 47.30% 25% \n", " Gardner SCC 23.40 11 47.20% 25% \n", " Long Ridge Preserve SMC 11.00 5.0 45.10% 25% \n", " Presidio Terrace SFC 2.80 1.2 43.90% 25% \n", " Moss Beach SMC 19.70 8.6 43.69% 25% \n", " El Granada SMC 49.20 21 43.60% 25% \n", " Hayward Acres ALA 3.50 1.5 43.30% 25% \n", " San Lorenzo ALA 55.50 23 40.95% 25% \n", " Lincoln Park SFC 4.50 1.8 39.60% 25% \n", " Communications Hill SCC 27.80 11 39.50% 25% \n", " Purisima Creek Preserve SMC 16.50 6.4 39.00% 25% \n", " Mt Tamalpais State Park MAR 31.70 12 38.70% 25% \n", " Broadmoor SMC 8.80 3.4 38.26% 25% \n", " South Beach SFC 4.80 1.8 37.40% 25% \n", " Muir Beach MAR 4.60 1.7 37.10% 25% \n", " Lake Street SFC 3.90 1.4 36.80% 25% \n", " Spartan Keyes SCC 64.30 24 36.80% 25% \n", " Milpitas SCC 224.00 82 36.70% 25% \n", " Ashland ALA 35.10 13 36.10% 25% \n", " Willow Glen SCC 81.60 29 36.00% 25% \n", " San Bruno SMC 114.00 40 34.90% 25% \n", " Santa Clara SCC 348.00 121 34.80% 25% \n", " MIT MAS 9.60 3.3 34.70% 25% \n", " Fremont ALA 780.20 268 34.30% 25% \n", " Millers Point NSW 3.20 1.1 34.30% 25% \n", " Seven Trees SCC 40.90 14 34.00% 25% \n", " Half Moon Bay SMC 68.00 23 34.00% 25% \n", " Parkview SCC 42.50 14 33.70% 25% \n", " Union City ALA 208.80 70 33.37% 25% \n", " Pacifica SMC 150.90 50 33.20% 25% \n", " Branham SCC 44.00 15 33.20% 25% \n", " Hayward ALA 444.50 148 33.20% 25% \n", " Stinson Beach MAR 11.20 3.7 32.90% 25% \n", " Marin Headlands GGNRA MAR 65.70 21 31.90% 25% \n", " San Martin SCC 35.30 11 31.85% 25% \n", " South San Francisco SMC 185.30 57 30.98% 25% \n", " Willow Glen South SCC 63.30 20 30.90% 25% \n", " Forest of Nisene Marks SP SCC 44.00 14 30.70% 25% \n", " Campbell SCC 119.00 36 30.30% 25% \n", " Butano State Park SMC 15.20 4.6 30.10% 25% \n", " Golden Gate Park SFC 40.80 12 29.40% 25% \n", " Seacliff SFC 4.10 1.2 29.30% 25% \n", " Fairview ALA 34.40 10 29.20% 25% \n", " Dawes Point NSW 1.80 0.5 29.20% 25% \n", " Bay Area Ridge Trail SMC 395.60 113 28.68% 25% \n", " San Jose SCC 2618.70 749 28.62% 25% \n", " Daly City SMC 148.10 42 28.27% 25% \n", " San Leandro ALA 230.60 65 28.10% 25% \n", " Cherryland ALA 20.90 5.8 27.80% 25% \n", " El Corte de Madera OSP SMC 34.54 9.3 26.88% 25% \n", " Mokelumne Hill CAL 14.70 3.9 26.80% 25% \n", " Presidio National Park SFC 43.50 12 26.70% 25% \n", " Gilroy SCC 188.90 50 26.40% 25% \n", " Castro Valley ALA 192.50 50 26.10% 25% \n", " Guerneville SON 22.70 5.4 23.60% none \n", " Presidio Heights SFC 6.50 1.4 21.60% none \n", " Panhandle SFC 7.30 1.5 20.60% none \n", " Polk Gulch SFC 4.00 0.7 18.20% none \n", " Balboa Terrace SFC 3.40 0.6 18.20% none \n", " Cole Valley SFC 1.70 0.3 18.00% none \n", " Healdsburg SON 53.70 9.6 17.80% none \n", " Bodega Bay SON 28.90 4.9 17.00% none \n", " Forest Hill SFC 6.10 1.0 15.90% none \n", " Northern Waterfront SFC 5.60 0.9 15.50% none \n", " Aquatic Park Fort Mason SFC 6.40 1.0 15.40% none \n", " Little Hollywood SFC 3.70 0.6 15.20% none \n", " Clarendon Heights SFC 6.00 0.9 14.20% none \n", " Fisherman's Wharf SFC 6.20 0.9 13.80% none \n", " Sutro Heights SFC 7.10 0.9 13.20% none \n", " Ashbury Heights SFC 3.70 0.5 13.00% none \n", " Sausalito MAR 32.70 4.2 12.90% none \n", " Corte Madera MAR 51.00 6.6 12.90% none \n", " Dogpatch SFC 5.10 0.6 12.30% none \n", " Alameda ALA 206.70 25 12.20% none \n", " Cow Hollow SFC 12.00 1.4 11.90% none \n", " Pacific Heights SFC 18.00 1.9 10.70% none \n", " Golden Gate Heights SFC 17.80 1.9 10.70% none \n", " Financial District SFC 9.40 1.0 10.20% none \n", " Mill Valley MAR 92.20 8.4 9.10% none \n", " Mission Bay SFC 13.80 1.2 8.60% none \n", " Berkeley ALA 260.30 20 7.80% none \n", " Emeryville ALA 28.10 2.2 7.70% none \n", " Albany ALA 42.70 2.9 6.80% none \n", " Cambridge MAS 180.80 11 6.20% none \n", " Central Waterfront SFC 10.20 0.6 6.00% none \n", " San Rafael MAR 260.00 9.6 3.70% none \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", " \n", " \n", " \n", " 0.1 mi to 99% \n", " 1.0 mi to 99% \n", " 1.6 mi to 90% \n", " 0.1 mi to 90% \n", " 0.5 mi to 90% \n", " 0.9 mi to 90% \n", " 1.1 mi to 90% \n", " 56 mi to 90% \n", " 0.9 mi to 90% \n", " 3.3 mi to 90% \n", " 8.3 mi to 90% \n", " 3.7 mi to 90% \n", " 29 mi to 90% \n", " 124 mi to 90% \n", " 91 mi to 90% \n", " 61 mi to 90% \n", " 65 mi to 90% \n", " 31 mi to 90% \n", " 1.7 mi to 90% \n", " 7.7 mi to 90% \n", " 56 mi to 90% \n", " 56 mi to 90% \n", " 25 mi to 90% \n", " 4.3 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", " 0.5 mi to 50% \n", " 0.2 mi to 50% \n", " 1.2 mi to 50% \n", " 3.1 mi to 50% \n", " 0.2 mi to 50% \n", " 5.0 mi to 50% \n", " 0.5 mi to 50% \n", " 2.9 mi to 50% \n", " 1.8 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", " 0.5 mi to 50% \n", " 8.5 mi to 50% \n", " 30 mi to 50% \n", " 4.9 mi to 50% \n", " 11 mi to 50% \n", " 17 mi to 50% \n", " 53 mi to 50% \n", " 1.5 mi to 50% \n", " 122 mi to 50% \n", " 0.5 mi to 50% \n", " 6.5 mi to 50% \n", " 11 mi to 50% \n", " 6.9 mi to 50% \n", " 35 mi to 50% \n", " 25 mi to 50% \n", " 7.4 mi to 50% \n", " 75 mi to 50% \n", " 1.9 mi to 50% \n", " 12 mi to 50% \n", " 6.4 mi to 50% \n", " 35 mi to 50% \n", " 12 mi to 50% \n", " 8.5 mi to 50% \n", " 23 mi to 50% \n", " 3.0 mi to 50% \n", " 8.4 mi to 50% \n", " 0.8 mi to 50% \n", " 7.2 mi to 50% \n", " 0.4 mi to 50% \n", " 84 mi to 50% \n", " 560 mi to 50% \n", " 32 mi to 50% \n", " 51 mi to 50% \n", " 4.6 mi to 50% \n", " 8.0 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", " 0.3 mi to 25% \n", " 0.2 mi to 25% \n", " 0.3 mi to 25% \n", " 0.3 mi to 25% \n", " 0.2 mi to 25% \n", " 0.1 mi to 25% \n", " 3.9 mi to 25% \n", " 2.3 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", " 4.0 mi to 25% \n", " 6.2 mi to 25% \n", " 0.6 mi to 25% \n", " 26 mi to 25% \n", " 1.6 mi to 25% \n", " 2.6 mi to 25% \n", " 2.5 mi to 25% \n", " 1.4 mi to 25% \n", " 15 mi to 25% \n", " 2.3 mi to 25% \n", " 45 mi to 25% \n", " 4.9 mi to 25% \n", " 7.8 mi to 25% \n", " 34 mi to 25% \n", " 1.9 mi to 25% \n", " 55 mi to 25% " ] }, "execution_count": 6, "metadata": {}, "output_type": "execute_result" } ], "source": [ "small_places" ] }, { "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": 7, "metadata": {}, "outputs": [ { "data": { "text/html": [ "
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NameInitialsSMC %SCC %SMC milesSCC milesTotal milesAvg %
Megan GardnerMG99.3119.3627951465426059.335
Barry MannBM77.9130.7021922324451654.305
Peter NorvigPN67.1435.4518892683457251.295
Brian FeinbergBF36.7645.3010343429446341.030
Jason MolendaJM7.6056.092144245445931.845
\n", "
" ], "text/plain": [ " Name Initials SMC % SCC % SMC miles SCC miles Total miles \\\n", " Megan Gardner MG 99.31 19.36 2795 1465 4260 \n", " Barry Mann BM 77.91 30.70 2192 2324 4516 \n", " Peter Norvig PN 67.14 35.45 1889 2683 4572 \n", " Brian Feinberg BF 36.76 45.30 1034 3429 4463 \n", " Jason Molenda JM 7.60 56.09 214 4245 4459 \n", "\n", " Avg % \n", " 59.335 \n", " 54.305 \n", " 51.295 \n", " 41.030 \n", " 31.845 " ] }, "execution_count": 7, "metadata": {}, "output_type": "execute_result" }, { "data": { "image/png": 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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": 8, "metadata": {}, "outputs": [ { "data": { "text/html": [ "
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yearEd_kmEd_mi
202410468
202310167
20229666
20219365
20208762
20198056
20187754
20177351
20166747
20156142
20144635
\n", "
" ], "text/plain": [ " year Ed_km Ed_mi\n", " 2024 104 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": 8, "metadata": {}, "output_type": "execute_result" } ], "source": [ "Ed_progress(rides)" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "My current Eddington Number is **104** 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": 9, "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", "
kmskms gapmilesmiles gap
1056692
106107014
107187124
108227228
109287333
110367437
111447546
112557649
113607752
\n", "
" ], "text/plain": [ " kms kms gap miles miles gap\n", " 105 6 69 2\n", " 106 10 70 14\n", " 107 18 71 24\n", " 108 22 72 28\n", " 109 28 73 33\n", " 110 36 74 37\n", " 111 44 75 46\n", " 112 55 76 49\n", " 113 60 77 52" ] }, "execution_count": 9, "metadata": {}, "output_type": "execute_result" } ], "source": [ "Ed_gaps(rides)" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "I need just one ride of 105 km to increase my number to 105 kms, but I need two rides of 69 miles to reach that level. (It takes more than one because of rides that are between 68 and 69 miles.)\n", "\n", "I'm glad that my Eddington number (in miles) is greater than my age (in years), but I'm not sure how long I can keep that up. At some point I might switch from tracking Eddington numbers to tracking my number of metric centuries:" ] }, { "cell_type": "code", "execution_count": 10, "metadata": {}, "outputs": [ { "data": { "text/plain": [ "123" ] }, "execution_count": 10, "metadata": {}, "output_type": "execute_result" } ], "source": [ "count(rides.kms >= 100)" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "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 1.61 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": 11, "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": 12, "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": 13, "metadata": {}, "outputs": [ { "data": { "text/plain": [ "'Coast: 70 min, Creek: 64 min.'" ] }, "execution_count": 13, "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": 14, "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": 15, "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": 15, "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": 16, "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": 16, "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": 17, "metadata": { "scrolled": true }, "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
Sat, 7/25/20152015Palo Alto, California4.0443.62481910.80364.0110.02.0970.181469.0
Sun, 6/4/20172017Sequoia Challenge6.2966.52752010.58364.0113.02.14107.032292.0
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", " Sat, 7/25/2015 2015 Palo Alto, California 4.04 \n", " Sun, 6/4/2017 2017 Sequoia Challenge 6.29 \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", " 43.62 4819 10.80 364.0 110.0 2.09 70.18 1469.0 \n", " 66.52 7520 10.58 364.0 113.0 2.14 107.03 2292.0 \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": 17, "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": 18, "metadata": {}, "outputs": [ { "data": { "text/html": [ "
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yearhoursmilesfeetmphvamfpmipctkmsmeters
count549.000000549.000000549.000000549.000000549.000000549.000000549.000000549.000000549.000000549.000000
mean2017.0874323.40165843.4591991837.23679412.981494157.36065641.4499090.78477269.925792559.996357
std2.6690311.48523617.8166441506.5139481.33078889.68660627.1737410.51452828.667056459.179588
min2012.0000001.54000020.96000068.0000008.55000010.0000003.0000000.05000033.72000021.000000
25%2015.0000002.22000029.210000741.00000012.16000081.00000020.0000000.37000047.000000226.000000
50%2017.0000002.89000037.0500001378.00000013.140000152.00000036.0000000.69000059.610000420.000000
75%2018.0000004.46000058.4200002362.00000013.780000217.00000055.0000001.05000094.000000720.000000
max2024.0000008.140000102.4100007644.00000016.750000406.000000153.0000002.900000164.7800002330.000000
\n", "
" ], "text/plain": [ " year hours miles feet mph \\\n", "count 549.000000 549.000000 549.000000 549.000000 549.000000 \n", "mean 2017.087432 3.401658 43.459199 1837.236794 12.981494 \n", "std 2.669031 1.485236 17.816644 1506.513948 1.330788 \n", "min 2012.000000 1.540000 20.960000 68.000000 8.550000 \n", "25% 2015.000000 2.220000 29.210000 741.000000 12.160000 \n", "50% 2017.000000 2.890000 37.050000 1378.000000 13.140000 \n", "75% 2018.000000 4.460000 58.420000 2362.000000 13.780000 \n", "max 2024.000000 8.140000 102.410000 7644.000000 16.750000 \n", "\n", " vam fpmi pct kms meters \n", "count 549.000000 549.000000 549.000000 549.000000 549.000000 \n", "mean 157.360656 41.449909 0.784772 69.925792 559.996357 \n", "std 89.686606 27.173741 0.514528 28.667056 459.179588 \n", "min 10.000000 3.000000 0.050000 33.720000 21.000000 \n", "25% 81.000000 20.000000 0.370000 47.000000 226.000000 \n", "50% 152.000000 36.000000 0.690000 59.610000 420.000000 \n", "75% 217.000000 55.000000 1.050000 94.000000 720.000000 \n", "max 406.000000 153.000000 2.900000 164.780000 2330.000000 " ] }, "execution_count": 18, "metadata": {}, "output_type": "execute_result" } ], "source": [ "rides.describe() # Summary statistics for the rides" ] }, { "cell_type": "code", "execution_count": 19, "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": 19, "metadata": {}, "output_type": "execute_result" } ], "source": [ "segments.describe() # Summary statistics for the segments" ] }, { "cell_type": "code", "execution_count": 20, "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
Sun, 8/25/20242024Petaluma–Santa Rosa + Napa5.2284.26296616.14173.035.00.67135.57904.0
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
\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", " Sun, 8/25/2024 2024 Petaluma–Santa Rosa + Napa 5.22 84.26 2966 \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", "\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", " 16.14 173.0 35.0 0.67 135.57 904.0 \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 " ] }, "execution_count": 20, "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": 21, "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": 21, "metadata": {}, "output_type": "execute_result" } ], "source": [ "top(segments, 'mph') # Fastest segments (there are no descent segments in the database)" ] }, { "cell_type": "code", "execution_count": 22, "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": 22, "metadata": {}, "output_type": "execute_result" } ], "source": [ "top(segments, 'feet') # Biggest climbing segments" ] }, { "cell_type": "code", "execution_count": 23, "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": 23, "metadata": {}, "output_type": "execute_result" } ], "source": [ "top(segments, 'pct') # Steepest climbs" ] }, { "cell_type": "code", "execution_count": 24, "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
Sun, 8/25/20242024Petaluma–Santa Rosa + Napa5.2284.26296616.14173.035.00.67135.57904.0
Sat, 6/1/20242024OLH / Old Haul / Loma Mar / Pescadero / Tunita...7.8481.70731410.42284.090.01.70131.462229.0
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
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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", " Sun, 8/25/2024 2024 Petaluma–Santa Rosa + Napa \n", " Sat, 6/1/2024 2024 OLH / Old Haul / Loma Mar / Pescadero / Tunita... \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", "\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", " 5.22 84.26 2966 16.14 173.0 35.0 0.67 135.57 904.0 \n", " 7.84 81.70 7314 10.42 284.0 90.0 1.70 131.46 2229.0 \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 " ] }, "execution_count": 24, "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 }