diff --git a/ipynb/Bike-Stats.ipynb b/ipynb/Bike-Stats.ipynb index d1ae0c9..ea3d982 100644 --- a/ipynb/Bike-Stats.ipynb +++ b/ipynb/Bike-Stats.ipynb @@ -4,11 +4,11 @@ "cell_type": "markdown", "metadata": {}, "source": [ - "
Peter Norvig, Oct 2017
Last update: Jan 2024
\n", + "
Peter Norvig, Oct 2017
Last update: May 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", + "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", @@ -19,18 +19,27 @@ "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. 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" + "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": 1, + "execution_count": 2, "metadata": {}, "outputs": [ { @@ -215,14 +224,12 @@ " 2014 191.03 2469 118481 12.92 189.0 48.0 0.91 3972.62 36113.0" ] }, - "execution_count": 1, + "execution_count": 2, "metadata": {}, "output_type": "execute_result" } ], "source": [ - "%run BikeCode.ipynb\n", - "\n", "yearly" ] }, @@ -235,7 +242,7 @@ }, { "cell_type": "code", - "execution_count": 2, + "execution_count": 3, "metadata": {}, "outputs": [ { @@ -420,7 +427,7 @@ " 2014 0.6 7.9 379.7 12.92 189.0 48.0 0.91 12.7 115.7" ] }, - "execution_count": 2, + "execution_count": 3, "metadata": {}, "output_type": "execute_result" } @@ -458,7 +465,7 @@ }, { "cell_type": "code", - "execution_count": 3, + "execution_count": 4, "metadata": {}, "outputs": [ { @@ -466,114 +473,114 @@ "text/html": [ "\n", - "\n", + "
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 datesquareclustertotalcommentdatesquareclustertotalcomment
04/28/20241412753382Livermore04/28/20241412753382Livermore
02/25/20241411963279Expanding through Santa Cruz and to the South02/25/20241411963279Expanding through Santa Cruz and to the South
01/01/20241410563105Start of this year01/01/20241410563105Start of this year
12/08/20231410423084Benicia ride connects East Bay and Napa clusters12/08/20231410423084Benicia ride connects East Bay and Napa clusters
11/05/2023149322914Alum Rock ride gets 14x14 max square11/05/2023149322914Alum Rock ride gets 14x14 max square
06/30/2023136892640Rides in east Bay fill in holes06/30/2023136892640Rides in east Bay fill in holes
04/14/2023136302595Black Sands Beach low-tide hike connects Marin to max cluster04/14/2023136302595Black Sands Beach low-tide hike connects Marin to max cluster
03/04/2023135832574Almaden rides connects Gilroy to max cluster03/04/2023135832574Almaden rides connects Gilroy to max cluster
10/22/2022133962495Alviso levees to get to 13x13 max square10/22/2022133962495Alviso levees to get to 13x13 max square
10/16/2022123932492Milpitas ride connects East Bay to max cluster10/16/2022123932492Milpitas ride connects East Bay to max cluster
09/08/2022113002487First started tracking tiles09/08/2022113002487First started tracking tiles
\n" ], "text/plain": [ - "" + "" ] }, - "execution_count": 3, + "execution_count": 4, "metadata": {}, "output_type": "execute_result" } @@ -590,12 +597,14 @@ "\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**. " + "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": 4, + "execution_count": 5, "metadata": {}, "outputs": [ { @@ -619,1660 +628,1861 @@ " \n", " \n", " \n", - " pct\n", - " county\n", " name\n", " total\n", " done\n", + " pct\n", + " badge\n", " to next badge\n", " \n", " \n", " \n", " \n", " \n", - " 100.0%\n", - " SMC\n", - " Los Trancos Woods\n", - " 5.3\n", - " 5.3\n", - " \n", - " \n", - " \n", - " \n", - " 100.0%\n", - " SMC\n", - " Los Trancos OSP\n", - " 0.3\n", - " 0.3\n", - " \n", - " \n", - " \n", - " \n", - " 100.0%\n", - " SMC\n", - " Ladera\n", - " 8.1\n", - " 8.1\n", - " \n", - " \n", - " \n", - " \n", - " 100.0%\n", - " SMC\n", - " Kensington Square\n", - " 0.6\n", - " 0.6\n", - " \n", - " \n", - " \n", - " \n", - " 100.0%\n", - " SMC\n", - " Menlo Oaks\n", - " 3.5\n", - " 3.5\n", - " \n", - " \n", - " \n", - " \n", - " 100.0%\n", - " SMC\n", - " North Fair Oaks\n", - " 26.7\n", - " 27\n", - " \n", - " \n", - " \n", - " \n", - " 100.0%\n", - " SMC\n", - " West Menlo Park\n", - " 11.2\n", - " 11\n", - " \n", - " \n", - " \n", - " \n", - " 100.0%\n", - " SMC\n", - " Sequoia Tract\n", - " 11.0\n", - " 11\n", - " \n", - " \n", - " \n", - " \n", - " 99.9%\n", - " SCC\n", - " Loyola\n", - " 18.3\n", - " 18\n", - " \n", - " \n", - " \n", - " \n", - " 99.9%\n", - " SMC\n", - " Palomar Park\n", - " 4.0\n", - " 4.0\n", - " \n", - " \n", - " \n", - " \n", - " 99.9%\n", - " SMC\n", - " Emerald Lake Hills\n", - " 24.6\n", - " 25\n", - " \n", - " \n", - " \n", - " \n", - " 99.8%\n", - " SMC\n", - " Atherton\n", - " 56.3\n", - " 56\n", - " \n", - " \n", - " \n", - " \n", - " 99.8%\n", - " SMC\n", - " Windy Hill Preserve\n", - " 4.1\n", - " 4.1\n", - " \n", - " \n", - " \n", - " \n", - " 99.7%\n", - " SMC\n", - " East Palo Alto\n", - " 48.3\n", - " 48\n", - " \n", - " \n", - " \n", - " \n", - " 99.7%\n", - " SMC\n", - " Menlo Park\n", - " 139.5\n", - " 139\n", - " \n", - " \n", - " \n", - " \n", - " 99.6%\n", - " SMC\n", - " Sky Londa\n", - " 11.8\n", - " 12\n", - " \n", - " \n", - " \n", - " \n", - " 99.6%\n", - " SCC\n", - " Los Altos\n", - " 138.2\n", - " 138\n", - " \n", - " \n", - " \n", - " \n", - " 99.5%\n", - " SMC\n", - " Portola Valley\n", - " 48.2\n", - " 48\n", - " \n", - " \n", - " \n", - " \n", - " 99.4%\n", - " SMC\n", - " Woodside\n", - " 75.2\n", - " 75\n", - " \n", - " \n", - " \n", - " \n", - " 99.3%\n", - " SCC\n", - " Mountain View\n", - " 208.1\n", - " 207\n", - " \n", - " \n", - " \n", - " \n", - " 99.3%\n", - " SMC\n", - " Redwood City\n", - " 240.5\n", - " 239\n", - " \n", - " \n", - " \n", - " \n", - " 99.2%\n", - " SCC\n", - " Los Altos Hills\n", - " 91.3\n", - " 91\n", - " \n", - " \n", - " \n", - " \n", - " 99.2%\n", - " SMC\n", - " San Carlos\n", - " 99.0\n", - " 98\n", - " \n", - " \n", - " \n", - " \n", - " 99.0%\n", - " SCC\n", - " Palo Alto\n", - " 297.2\n", - " 294\n", - " \n", - " \n", - " \n", - " \n", - " 93.5%\n", - " SMC\n", - " San Mateo Highlands\n", - " 18.0\n", - " 17\n", - " 1.0 mi to 99%\n", - " \n", - " \n", - " \n", - " 90.9%\n", - " SMC\n", - " Burleigh Murray Park\n", - " 2.1\n", - " 1.9\n", - " 0.2 mi to 99%\n", - " \n", - " \n", - " \n", - " 90.4%\n", - " SMC\n", - " Foster City\n", - " 150.0\n", - " 136\n", - " 13 mi to 99%\n", - " \n", - " \n", - " \n", - " 86.8%\n", - " SCC\n", - " Foothills Preserve\n", - " 1.1\n", - " 1.0\n", - " 0.0 mi to 90%\n", - " \n", - " \n", - " \n", - " 76.4%\n", - " SMC\n", - " Skyline Ridge OSP\n", - " 0.8\n", - " 0.6\n", - " 0.1 mi to 90%\n", - " \n", - " \n", - " \n", - " 74.1%\n", - " SCC\n", - " San Francisco Bay Trail\n", - " 260.8\n", - " 193\n", - " 41 mi to 90%\n", - " \n", - " \n", - " \n", - " 73.2%\n", - " CCC\n", - " Rosie Riveter Park\n", - " 5.5\n", - " 4.0\n", - " 0.9 mi to 90%\n", - " \n", - " \n", - " \n", - " 71.5%\n", - " SMC\n", - " Burlingame Hills\n", - " 6.0\n", - " 4.3\n", - " 1.1 mi to 90%\n", - " \n", - " \n", - " \n", - " 66.7%\n", - " SMC\n", - " Coal Creek Preserve\n", - " 3.9\n", - " 2.6\n", - " 0.9 mi to 90%\n", - " \n", - " \n", - " \n", - " 63.5%\n", - " ---\n", " San Mateo County\n", " 2814.0\n", - " 1,787\n", - " 746 mi to 90%\n", + " 1,875\n", + " 66.64%\n", + " 50%\n", + " 657 mi to 90%\n", " \n", " \n", " \n", - " 59.5%\n", - " SMC\n", - " Russian Ridge Preserve\n", - " 12.2\n", - " 7.3\n", - " 3.7 mi to 90%\n", - " \n", - " \n", - " \n", - " 59.3%\n", - " SMC\n", - " Montara\n", - " 27.8\n", - " 16\n", - " 8.5 mi to 90%\n", - " \n", - " \n", - " \n", - " 56.2%\n", - " SMC\n", - " Burlingame\n", - " 88.4\n", - " 50\n", - " 30 mi to 90%\n", - " \n", - " \n", - " \n", - " 54.7%\n", - " SMC\n", - " Belmont\n", - " 98.1\n", - " 54\n", - " 35 mi to 90%\n", - " \n", - " \n", - " \n", - " 53.3%\n", - " SCC\n", - " Sunnyvale\n", - " 357.0\n", - " 190\n", - " 131 mi to 90%\n", - " \n", - " \n", - " \n", - " 52.8%\n", - " SCC\n", - " Cupertino\n", - " 172.0\n", - " 91\n", - " 64 mi to 90%\n", - " \n", - " \n", - " \n", - " 52.4%\n", - " SCC\n", - " Monte Sereno\n", - " 20.4\n", - " 11\n", - " 7.7 mi to 90%\n", - " \n", - " \n", - " \n", - " 52.3%\n", - " SMC\n", - " Hillsborough\n", - " 85.3\n", - " 45\n", - " 32 mi to 90%\n", - " \n", - " \n", - " \n", - " 51.8%\n", - " SMC\n", - " San Mateo\n", - " 256.0\n", - " 133\n", - " 98 mi to 90%\n", - " \n", - " \n", - " \n", - " 51.5%\n", - " SMC\n", - " Half Moon Bay State Beach\n", - " 4.4\n", - " 2.3\n", - " 1.7 mi to 90%\n", - " \n", - " \n", - " \n", - " 51.2%\n", - " SMC\n", - " Long Ridge Preserve\n", - " 11.0\n", - " 5.6\n", - " 4.3 mi to 90%\n", - " \n", - " \n", - " \n", - " 51.2%\n", - " SCC\n", - " Castle Rock State Park\n", - " 11.2\n", - " 5.7\n", - " 4.3 mi to 90%\n", - " \n", - " \n", - " \n", - " 51.0%\n", - " ALA\n", - " Newark\n", - " 147.0\n", - " 75\n", - " 57 mi to 90%\n", - " \n", - " \n", - " \n", - " 50.4%\n", - " SCC\n", - " Saratoga\n", - " 180.0\n", - " 91\n", - " 71 mi to 90%\n", - " \n", - " \n", - " \n", - " 50.2%\n", - " SMC\n", - " Brisbane\n", - " 40.9\n", - " 21\n", - " 16 mi to 90%\n", - " \n", - " \n", - " \n", - " 47.7%\n", - " SCC\n", - " Edenvale\n", - " 30.0\n", - " 14\n", - " 0.7 mi to 50%\n", - " \n", - " \n", - " \n", - " 47.3%\n", - " NSW\n", - " Barangaroo\n", - " 1.7\n", - " 0.8\n", - " 0.0 mi to 50%\n", - " \n", - " \n", - " \n", - " 47.2%\n", - " SCC\n", - " Gardner\n", - " 23.4\n", - " 11\n", - " 0.7 mi to 50%\n", - " \n", - " \n", - " \n", - " 43.9%\n", - " SFC\n", - " Presidio Terrace\n", - " 2.8\n", - " 1.2\n", - " 0.2 mi to 50%\n", - " \n", - " \n", - " \n", - " 43.6%\n", - " SMC\n", - " El Granada\n", - " 49.2\n", - " 21\n", - " 3.1 mi to 50%\n", - " \n", - " \n", - " \n", - " 43.6%\n", - " SMC\n", - " Moss Beach\n", - " 19.7\n", - " 8.6\n", - " 1.3 mi to 50%\n", - " \n", - " \n", - " \n", - " 43.3%\n", - " ALA\n", - " Hayward Acres\n", - " 3.5\n", - " 1.5\n", - " 0.2 mi to 50%\n", - " \n", - " \n", - " \n", - " 42.6%\n", - " SMC\n", - " Millbrae\n", - " 65.0\n", - " 28\n", - " 4.8 mi to 50%\n", - " \n", - " \n", - " \n", - " 40.8%\n", - " ALA\n", - " San Lorenzo\n", - " 55.5\n", - " 23\n", - " 5.1 mi to 50%\n", - " \n", - " \n", - " \n", - " 39.6%\n", - " SFC\n", - " Lincoln Park\n", - " 4.5\n", - " 1.8\n", - " 0.5 mi to 50%\n", - " \n", - " \n", - " \n", - " 39.5%\n", - " SCC\n", - " Communications Hill\n", - " 27.8\n", - " 11\n", - " 2.9 mi to 50%\n", - " \n", - " \n", - " \n", - " 39.0%\n", - " SMC\n", - " Purisima Creek Preserve\n", - " 16.5\n", - " 6.4\n", - " 1.8 mi to 50%\n", - " \n", - " \n", - " \n", - " 38.9%\n", - " SMC\n", - " Colma\n", - " 13.7\n", - " 5.3\n", - " 1.5 mi to 50%\n", - " \n", - " \n", - " \n", - " 38.7%\n", - " MAR\n", - " Mt Tamalpais State Park\n", - " 31.7\n", - " 12\n", - " 3.6 mi to 50%\n", - " \n", - " \n", - " \n", - " 38.2%\n", - " SMC\n", - " Broadmoor\n", - " 8.8\n", - " 3.4\n", - " 1.0 mi to 50%\n", - " \n", - " \n", - " \n", - " 37.4%\n", - " SFC\n", - " South Beach\n", - " 4.8\n", - " 1.8\n", - " 0.6 mi to 50%\n", - " \n", - " \n", - " \n", - " 37.1%\n", - " MAR\n", - " Muir Beach\n", - " 4.6\n", - " 1.7\n", - " 0.6 mi to 50%\n", - " \n", - " \n", - " \n", - " 36.8%\n", - " SCC\n", - " Spartan Keyes\n", - " 64.3\n", - " 24\n", - " 8.5 mi to 50%\n", - " \n", - " \n", - " \n", - " 36.8%\n", - " SFC\n", - " Lake Street\n", - " 3.9\n", - " 1.4\n", - " 0.5 mi to 50%\n", - " \n", - " \n", - " \n", - " 36.7%\n", - " SCC\n", - " Milpitas\n", - " 224.0\n", - " 82\n", - " 30 mi to 50%\n", - " \n", - " \n", - " \n", - " 36.1%\n", - " ALA\n", - " Ashland\n", - " 35.1\n", - " 13\n", - " 4.9 mi to 50%\n", - " \n", - " \n", - " \n", - " 36.0%\n", - " SCC\n", - " Willow Glen\n", - " 81.6\n", - " 29\n", - " 11 mi to 50%\n", - " \n", - " \n", - " \n", - " 34.8%\n", - " SCC\n", - " Santa Clara\n", - " 348.0\n", - " 121\n", - " 53 mi to 50%\n", - " \n", - " \n", - " \n", - " 34.7%\n", - " MAS\n", - " MIT\n", - " 9.6\n", - " 3.3\n", - " 1.5 mi to 50%\n", - " \n", - " \n", - " \n", - " 34.3%\n", - " NSW\n", - " Millers Point\n", - " 3.2\n", - " 1.1\n", - " 0.5 mi to 50%\n", - " \n", - " \n", - " \n", - " 33.7%\n", - " SCC\n", - " Parkview\n", - " 42.5\n", - " 14\n", - " 6.9 mi to 50%\n", - " \n", - " \n", - " \n", - " 33.6%\n", - " SMC\n", - " Half Moon Bay\n", - " 68.0\n", - " 23\n", - " 11 mi to 50%\n", - " \n", - " \n", - " \n", - " 33.6%\n", - " SCC\n", - " Los Gatos\n", - " 148.0\n", - " 50\n", - " 24 mi to 50%\n", - " \n", - " \n", - " \n", - " 33.2%\n", - " SMC\n", - " Pacifica\n", - " 150.9\n", - " 50\n", - " 25 mi to 50%\n", - " \n", - " \n", - " \n", - " 33.0%\n", - " SCC\n", - " Seven Trees\n", - " 40.9\n", - " 13\n", - " 7.0 mi to 50%\n", - " \n", - " \n", - " \n", - " 33.0%\n", - " ---\n", " Santa Clara County\n", " 7569.0\n", - " 2,498\n", - " 1,287 mi to 50%\n", + " 2,695\n", + " 35.60%\n", + " 25%\n", + " 1,090 mi to 50%\n", " \n", " \n", " \n", - " 32.9%\n", - " ALA\n", - " Fremont\n", - " 780.2\n", - " 257\n", - " 133 mi to 50%\n", - " \n", - " \n", - " \n", - " 32.9%\n", - " ALA\n", - " Union City\n", - " 208.8\n", - " 69\n", - " 36 mi to 50%\n", - " \n", - " \n", - " \n", - " 32.9%\n", - " MAR\n", - " Stinson Beach\n", - " 11.2\n", - " 3.7\n", - " 1.9 mi to 50%\n", - " \n", - " \n", - " \n", - " 32.7%\n", - " ALA\n", - " Hayward\n", - " 444.5\n", - " 145\n", - " 77 mi to 50%\n", - " \n", - " \n", - " \n", - " 32.7%\n", - " SCC\n", - " Branham\n", - " 44.0\n", - " 14\n", - " 7.6 mi to 50%\n", - " \n", - " \n", - " \n", - " 31.9%\n", - " MAR\n", - " Marin Headlands GGNRA\n", - " 65.7\n", - " 21\n", - " 12 mi to 50%\n", - " \n", - " \n", - " \n", - " 31.5%\n", - " SCC\n", - " San Martin\n", - " 35.3\n", - " 11\n", - " 6.5 mi to 50%\n", - " \n", - " \n", - " \n", - " 31.0%\n", - " SMC\n", - " San Bruno\n", - " 114.0\n", - " 35\n", - " 22 mi to 50%\n", - " \n", - " \n", - " \n", - " 30.9%\n", - " SCC\n", - " Willow Glen South\n", - " 63.3\n", - " 20\n", - " 12 mi to 50%\n", - " \n", - " \n", - " \n", - " 30.7%\n", - " SCC\n", - " Forest of Nisene Marks SP\n", - " 44.0\n", - " 14\n", - " 8.5 mi to 50%\n", - " \n", - " \n", - " \n", - " 30.1%\n", - " SMC\n", - " Butano State Park\n", - " 15.2\n", - " 4.6\n", - " 3.0 mi to 50%\n", - " \n", - " \n", - " \n", - " 29.6%\n", - " SMC\n", - " South San Francisco\n", - " 185.3\n", - " 55\n", - " 38 mi to 50%\n", - " \n", - " \n", - " \n", - " 29.4%\n", - " SFC\n", - " Golden Gate Park\n", - " 40.8\n", - " 12\n", - " 8.4 mi to 50%\n", - " \n", - " \n", - " \n", - " 29.3%\n", - " SFC\n", - " Seacliff\n", - " 4.1\n", - " 1.2\n", - " 0.8 mi to 50%\n", - " \n", - " \n", - " \n", - " 29.3%\n", - " SCC\n", - " Campbell\n", - " 119.0\n", - " 35\n", - " 25 mi to 50%\n", - " \n", - " \n", - " \n", - " 29.2%\n", - " NSW\n", - " Dawes Point\n", - " 1.8\n", - " 0.5\n", - " 0.4 mi to 50%\n", - " \n", - " \n", - " \n", - " 28.2%\n", - " ALA\n", - " Fairview\n", - " 34.4\n", - " 9.7\n", - " 7.5 mi to 50%\n", - " \n", - " \n", - " \n", - " 28.0%\n", - " SCC\n", - " San Jose\n", - " 2618.7\n", - " 733\n", - " 576 mi to 50%\n", - " \n", - " \n", - " \n", - " 27.8%\n", - " ALA\n", - " Cherryland\n", - " 20.9\n", - " 5.8\n", - " 4.6 mi to 50%\n", - " \n", - " \n", - " \n", - " 27.7%\n", - " ALA\n", - " San Leandro\n", - " 230.6\n", - " 64\n", - " 51 mi to 50%\n", - " \n", - " \n", - " \n", - " 27.4%\n", - " SMC\n", - " Daly City\n", - " 148.1\n", - " 41\n", - " 33 mi to 50%\n", - " \n", - " \n", - " \n", - " 26.8%\n", - " CAL\n", - " Mokelumne Hill\n", - " 14.7\n", - " 3.9\n", - " 3.4 mi to 50%\n", - " \n", - " \n", - " \n", - " 26.7%\n", - " SFC\n", - " Presidio National Park\n", - " 43.5\n", - " 12\n", - " 10 mi to 50%\n", - " \n", - " \n", - " \n", - " 26.4%\n", - " SCC\n", - " Gilroy\n", - " 188.9\n", - " 50\n", - " 45 mi to 50%\n", - " \n", - " \n", - " \n", - " 26.1%\n", - " ALA\n", - " Castro Valley\n", - " 192.5\n", - " 50\n", - " 46 mi to 50%\n", - " \n", - " \n", - " \n", - " 25.6%\n", - " SMC\n", - " Bay Area Ridge Trail\n", - " 395.6\n", - " 101\n", - " 97 mi to 50%\n", - " \n", - " \n", - " \n", - " 23.6%\n", - " SON\n", - " Guerneville\n", - " 22.7\n", - " 5.4\n", - " 0.3 mi to 25%\n", - " \n", - " \n", - " \n", - " 21.6%\n", - " SFC\n", - " Presidio Heights\n", - " 6.5\n", - " 1.4\n", - " 0.2 mi to 25%\n", - " \n", - " \n", - " \n", - " 20.6%\n", - " SFC\n", - " Panhandle\n", - " 7.3\n", - " 1.5\n", - " 0.3 mi to 25%\n", - " \n", - " \n", - " \n", - " 18.2%\n", - " SFC\n", - " Balboa Terrace\n", - " 3.4\n", - " 0.6\n", - " 0.2 mi to 25%\n", - " \n", - " \n", - " \n", - " 18.2%\n", - " SFC\n", - " Polk Gulch\n", - " 4.0\n", - " 0.7\n", - " 0.3 mi to 25%\n", - " \n", - " \n", - " \n", - " 18.0%\n", - " SFC\n", - " Cole Valley\n", - " 1.7\n", - " 0.3\n", - " 0.1 mi to 25%\n", - " \n", - " \n", - " \n", - " 17.8%\n", - " SON\n", - " Healdsburg\n", - " 53.7\n", - " 9.6\n", - " 3.9 mi to 25%\n", - " \n", - " \n", - " \n", - " 17.0%\n", - " SON\n", - " Bodega Bay\n", - " 28.9\n", - " 4.9\n", - " 2.3 mi to 25%\n", - " \n", - " \n", - " \n", - " 16.6%\n", - " ---\n", " Alameda County\n", " 5818.0\n", - " 965\n", - " 490 mi to 25%\n", + " 1,030\n", + " 17.71%\n", + " none\n", + " 424 mi to 25%\n", " \n", " \n", " \n", - " 15.9%\n", - " SFC\n", - " Forest Hill\n", - " 6.1\n", - " 1.0\n", - " 0.6 mi to 25%\n", - " \n", - " \n", - " \n", - " 15.5%\n", - " SFC\n", - " Northern Waterfront\n", - " 5.6\n", - " 0.9\n", - " 0.5 mi to 25%\n", - " \n", - " \n", - " \n", - " 15.4%\n", - " SFC\n", - " Aquatic Park Fort Mason\n", - " 6.4\n", - " 1.0\n", - " 0.6 mi to 25%\n", - " \n", - " \n", - " \n", - " 15.2%\n", - " SFC\n", - " Little Hollywood\n", - " 3.7\n", - " 0.6\n", - " 0.4 mi to 25%\n", - " \n", - " \n", - " \n", - " 14.2%\n", - " SFC\n", - " Clarendon Heights\n", - " 6.0\n", - " 0.9\n", - " 0.6 mi to 25%\n", - " \n", - " \n", - " \n", - " 13.8%\n", - " SFC\n", - " Fisherman's Wharf\n", - " 6.2\n", - " 0.9\n", - " 0.7 mi to 25%\n", - " \n", - " \n", - " \n", - " 13.2%\n", - " SFC\n", - " Sutro Heights\n", - " 7.1\n", - " 0.9\n", - " 0.8 mi to 25%\n", - " \n", - " \n", - " \n", - " 13.0%\n", - " SFC\n", - " Ashbury Heights\n", - " 3.7\n", - " 0.5\n", - " 0.4 mi to 25%\n", - " \n", - " \n", - " \n", - " 12.9%\n", - " MAR\n", - " Corte Madera\n", - " 51.0\n", - " 6.6\n", - " 6.2 mi to 25%\n", - " \n", - " \n", - " \n", - " 12.9%\n", - " MAR\n", - " Sausalito\n", - " 32.7\n", - " 4.2\n", - " 4.0 mi to 25%\n", - " \n", - " \n", - " \n", - " 12.3%\n", - " SFC\n", - " Dogpatch\n", - " 5.1\n", - " 0.6\n", - " 0.6 mi to 25%\n", - " \n", - " \n", - " \n", - " 12.2%\n", - " ALA\n", - " Alameda\n", - " 206.7\n", - " 25\n", - " 26 mi to 25%\n", - " \n", - " \n", - " \n", - " 11.9%\n", - " SFC\n", - " Cow Hollow\n", - " 12.0\n", - " 1.4\n", - " 1.6 mi to 25%\n", - " \n", - " \n", - " \n", - " 10.9%\n", - " ---\n", " Marin County\n", " 2333.0\n", " 255\n", + " 10.94%\n", + " none\n", " 328 mi to 25%\n", " \n", " \n", " \n", - " 10.7%\n", - " SFC\n", - " Pacific Heights\n", - " 18.0\n", - " 1.9\n", - " 2.6 mi to 25%\n", - " \n", - " \n", - " \n", - " 10.7%\n", - " SFC\n", - " Golden Gate Heights\n", - " 17.8\n", - " 1.9\n", - " 2.5 mi to 25%\n", - " \n", - " \n", - " \n", - " 10.2%\n", - " SFC\n", - " Financial District\n", - " 9.4\n", - " 1.0\n", - " 1.4 mi to 25%\n", - " \n", - " \n", - " \n", - " 9.3%\n", - " ---\n", " San Francisco County\n", " 1217.0\n", " 113\n", + " 9.26%\n", + " none\n", " 192 mi to 25%\n", " \n", " \n", " \n", - " 9.1%\n", - " MAR\n", - " Mill Valley\n", - " 92.2\n", - " 8.4\n", - " 15 mi to 25%\n", - " \n", - " \n", - " \n", - " 8.9%\n", - " ---\n", " Napa County\n", " 1609.0\n", " 143\n", + " 8.90%\n", + " none\n", " 259 mi to 25%\n", " \n", " \n", " \n", - " 8.6%\n", - " SFC\n", - " Mission Bay\n", - " 13.8\n", - " 1.2\n", - " 2.3 mi to 25%\n", - " \n", - " \n", - " \n", - " 7.7%\n", - " ALA\n", - " Emeryville\n", - " 28.1\n", - " 2.2\n", - " 4.9 mi to 25%\n", - " \n", - " \n", - " \n", - " 7.6%\n", - " ALA\n", - " Berkeley\n", - " 260.3\n", - " 20\n", - " 45 mi to 25%\n", - " \n", - " \n", - " \n", - " 7.1%\n", - " ---\n", " Santa Cruz County\n", " 2718.0\n", " 194\n", + " 7.12%\n", + " none\n", " 486 mi to 25%\n", " \n", " \n", " \n", - " 6.8%\n", - " ALA\n", - " Albany\n", - " 42.7\n", - " 2.9\n", - " 7.8 mi to 25%\n", - " \n", - " \n", - " \n", - " 6.2%\n", - " MAS\n", - " Cambridge\n", - " 180.8\n", - " 11\n", - " 34 mi to 25%\n", - " \n", - " \n", - " \n", - " 6.0%\n", - " SFC\n", - " Central Waterfront\n", - " 10.2\n", - " 0.6\n", - " 1.9 mi to 25%\n", - " \n", - " \n", - " \n", - " 5.1%\n", - " ---\n", " Sonoma County\n", " 4895.0\n", " 251\n", + " 5.12%\n", + " none\n", " 973 mi to 25%\n", " \n", " \n", " \n", - " 3.8%\n", - " ---\n", " Contra Costa County\n", " 5945.0\n", " 226\n", + " 3.80%\n", + " none\n", " 1,260 mi to 25%\n", " \n", " \n", " \n", - " 3.7%\n", - " MAR\n", - " San Rafael\n", - " 260.0\n", - " 9.6\n", - " 55 mi to 25%\n", - " \n", - " \n", - " \n", - " 1.8%\n", - " ---\n", " California\n", " 377037.0\n", - " 6,719\n", - " 822 mi to 2%\n", + " 7,239\n", + " 1.92%\n", + " none\n", + " 302 mi to 2%\n", " \n", " \n", " \n", - " 0.113%\n", - " ---\n", " USA\n", " 6406754.0\n", - " 7,267\n", - " 5,546 mi to 0.2%\n", + " 7,688\n", + " 0.1200%\n", + " none\n", + " 5,125 mi to 0.2%\n", " \n", " \n", " \n", - " 0.017%\n", - " ---\n", " Earth\n", " 41974536.0\n", - " 7,159\n", - " 1,236 mi to 0.02%\n", + " 7,555\n", + " 0.0180%\n", + " none\n", + " 839 mi to 0.02%\n", " \n", " \n", "\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", - 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" 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% " + " 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 1,030 17.71% none 424 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 1609.0 143 8.90% none 259 mi to 25%\n", + " Santa Cruz County 2718.0 194 7.12% none 486 mi to 25%\n", + " Sonoma County 4895.0 251 5.12% none 973 mi to 25%\n", + " Contra Costa County 5945.0 226 3.80% none 1,260 mi to 25%\n", + " California 377037.0 7,239 1.92% none 302 mi to 2%\n", + " USA 6406754.0 7,688 0.1200% none 5,125 mi to 0.2%\n", + " Earth 41974536.0 7,555 0.0180% none 839 mi to 0.02%" ] }, - "execution_count": 4, + "execution_count": 5, "metadata": {}, "output_type": "execute_result" } ], "source": [ - "wandering(by='pct')" + "big_places" + ] + }, + { + "cell_type": "code", + "execution_count": 6, + "metadata": {}, + "outputs": [ + { + "data": { + "text/html": [ + "
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namecountytotaldonepctbadgeto next badge
Sequoia TractSMC11.0011100%99%
Kensington SquareSMC0.600.6100%99%
Los Trancos OSPSMC0.300.3100%99%
Los Trancos WoodsSMC5.305.3100%99%
Menlo OaksSMC3.503.5100%99%
North Fair OaksSMC26.7027100%99%
Palomar ParkSMC4.004.0100%99%
LaderaSMC8.108.1100%99%
Windy Hill PreserveSMC4.104.1100%99%
Foothills OS PreserveSCC1.101.1100%99%
Emerald Lake HillsSMC24.602599.96%99%
East Palo AltoSMC48.304899.95%99%
LoyolaSCC18.301899.94%99%
Los AltosSCC138.2013899.80%99%
AthertonSMC56.305699.80%99%
West Menlo ParkSMC11.201199.75%99%
WoodsideSMC75.207599.74%99%
Redwood CitySMC240.5024099.73%99%
Sky LondaSMC11.801299.70%99%
Menlo ParkSMC139.5013999.70%99%
Mountain ViewSCC208.1020799.64%99%
Los Altos HillsSCC91.309199.56%99%
Palo AltoSCC297.2029699.45%99%
San CarlosSMC99.009899.43%99%
Foster CitySMC150.0014999.40%99%
Portola ValleySMC48.204899.12%99%
Burleigh Murray ParkSMC2.102.095.08%90%0.1 mi to 99%
San Mateo HighlandsSMC18.001793.50%90%1.0 mi to 99%
Skyline Ridge OSPSMC0.800.676.40%75%0.1 mi to 90%
BelmontSMC98.107475.43%75%14 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%
CupertinoSCC172.009554.99%50%60 mi to 90%
San MateoSMC256.0014054.60%50%91 mi to 90%
HillsboroughSMC85.304553.10%50%31 mi to 90%
Monte SerenoSCC20.401152.40%50%7.7 mi to 90%
Half Moon Bay State BeachSMC4.402.352.40%50%1.7 mi to 90%
NewarkALA147.007651.60%50%56 mi to 90%
Los GatosSCC148.007651.60%50%57 mi to 90%
SaratogaSCC180.009351.40%50%69 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 MartinSCC35.301131.50%25%6.5 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%
Daly CitySMC148.104228.27%25%32 mi to 50%
San LeandroALA230.606528.10%25%51 mi to 50%
San JoseSCC2618.7073328.00%25%576 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", + " Sequoia Tract SMC 11.00 11 100% 99% \n", + " Kensington Square SMC 0.60 0.6 100% 99% \n", + " Los Trancos OSP SMC 0.30 0.3 100% 99% \n", + " Los Trancos Woods SMC 5.30 5.3 100% 99% \n", + " Menlo Oaks SMC 3.50 3.5 100% 99% \n", + " North Fair Oaks SMC 26.70 27 100% 99% \n", + " Palomar Park SMC 4.00 4.0 100% 99% \n", + " Ladera SMC 8.10 8.1 100% 99% \n", + " Windy Hill Preserve SMC 4.10 4.1 100% 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", + " Los Altos SCC 138.20 138 99.80% 99% \n", + " Atherton SMC 56.30 56 99.80% 99% \n", + " West Menlo Park SMC 11.20 11 99.75% 99% \n", + " Woodside SMC 75.20 75 99.74% 99% \n", + " Redwood City SMC 240.50 240 99.73% 99% \n", + " Sky Londa SMC 11.80 12 99.70% 99% \n", + " Menlo Park SMC 139.50 139 99.70% 99% \n", + " Mountain View SCC 208.10 207 99.64% 99% \n", + " Los Altos Hills SCC 91.30 91 99.56% 99% \n", + " Palo Alto SCC 297.20 296 99.45% 99% \n", + " San Carlos SMC 99.00 98 99.43% 99% \n", + " Foster City SMC 150.00 149 99.40% 99% \n", + " Portola Valley SMC 48.20 48 99.12% 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", + " Skyline Ridge OSP SMC 0.80 0.6 76.40% 75% \n", + " Belmont SMC 98.10 74 75.43% 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", + " Cupertino SCC 172.00 95 54.99% 50% \n", + " San Mateo SMC 256.00 140 54.60% 50% \n", + " Hillsborough SMC 85.30 45 53.10% 50% \n", + " Monte Sereno SCC 20.40 11 52.40% 50% \n", + " Half Moon Bay State Beach SMC 4.40 2.3 52.40% 50% \n", + " Newark ALA 147.00 76 51.60% 50% \n", + " Los Gatos SCC 148.00 76 51.60% 50% \n", + " Saratoga SCC 180.00 93 51.40% 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 31.50% 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", + " Daly City SMC 148.10 42 28.27% 25% \n", + " San Leandro ALA 230.60 65 28.10% 25% \n", + " San Jose SCC 2618.70 733 28.00% 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", + " 0.1 mi to 99% \n", + " 1.0 mi to 99% \n", + " 0.1 mi to 90% \n", + " 14 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", + " 60 mi to 90% \n", + " 91 mi to 90% \n", + " 31 mi to 90% \n", + " 7.7 mi to 90% \n", + " 1.7 mi to 90% \n", + " 56 mi to 90% \n", + " 57 mi to 90% \n", + " 69 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", + " 6.5 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", + " 32 mi to 50% \n", + " 51 mi to 50% \n", + " 576 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" ] }, { @@ -2286,7 +2496,7 @@ }, { "cell_type": "code", - "execution_count": 5, + "execution_count": 7, "metadata": {}, "outputs": [ { @@ -2396,7 +2606,7 @@ " 31.88 " ] }, - "execution_count": 5, + "execution_count": 7, "metadata": {}, "output_type": "execute_result" }, @@ -2430,7 +2640,7 @@ }, { "cell_type": "code", - "execution_count": 6, + "execution_count": 8, "metadata": {}, "outputs": [ { @@ -2545,7 +2755,7 @@ " 2014 46 35" ] }, - "execution_count": 6, + "execution_count": 8, "metadata": {}, "output_type": "execute_result" } @@ -2570,7 +2780,7 @@ }, { "cell_type": "code", - "execution_count": 7, + "execution_count": 9, "metadata": {}, "outputs": [ { @@ -2604,65 +2814,65 @@ " \n", " \n", " 104\n", - " 7\n", + " 4\n", " 69\n", - " 9\n", + " 6\n", " \n", " \n", " \n", " 105\n", - " 13\n", + " 10\n", " 70\n", - " 21\n", + " 18\n", " \n", " \n", " \n", " 106\n", - " 17\n", + " 14\n", " 71\n", - " 31\n", + " 28\n", " \n", " \n", " \n", " 107\n", - " 25\n", + " 22\n", " 72\n", - " 34\n", + " 31\n", " \n", " \n", " \n", " 108\n", - " 29\n", + " 26\n", " 73\n", - " 38\n", + " 36\n", " \n", " \n", " \n", " 109\n", - " 35\n", + " 32\n", " 74\n", - " 40\n", + " 39\n", " \n", " \n", " \n", " 110\n", - " 43\n", + " 40\n", " 75\n", - " 48\n", + " 47\n", " \n", " \n", " \n", " 111\n", - " 51\n", + " 48\n", " 76\n", - " 51\n", + " 50\n", " \n", " \n", " \n", " 112\n", - " 62\n", + " 59\n", " 77\n", - " 54\n", + " 53\n", " \n", " \n", "\n", @@ -2670,18 +2880,18 @@ ], "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" + " 104 4 69 6\n", + " 105 10 70 18\n", + " 106 14 71 28\n", + " 107 22 72 31\n", + " 108 26 73 36\n", + " 109 32 74 39\n", + " 110 40 75 47\n", + " 111 48 76 50\n", + " 112 59 77 53" ] }, - "execution_count": 7, + "execution_count": 9, "metadata": {}, "output_type": "execute_result" } @@ -2694,8 +2904,35 @@ "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", + "I need 4 rides of 104 kms or 6 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", + "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. 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": [ + "119" + ] + }, + "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", @@ -2730,7 +2967,7 @@ }, { "cell_type": "code", - "execution_count": 8, + "execution_count": 11, "metadata": {}, "outputs": [ { @@ -2770,12 +3007,12 @@ }, { "cell_type": "code", - "execution_count": 9, + "execution_count": 12, "metadata": {}, "outputs": [ { "data": { - "image/png": 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\n", + "image/png": 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\n", "text/plain": [ "
" ] @@ -2801,7 +3038,7 @@ }, { "cell_type": "code", - "execution_count": 10, + "execution_count": 13, "metadata": {}, "outputs": [ { @@ -2810,7 +3047,7 @@ "'Coast: 70 min, Creek: 64 min.'" ] }, - "execution_count": 10, + "execution_count": 13, "metadata": {}, "output_type": "execute_result" } @@ -2839,7 +3076,7 @@ }, { "cell_type": "code", - "execution_count": 11, + "execution_count": 14, "metadata": {}, "outputs": [ { @@ -2868,7 +3105,7 @@ }, { "cell_type": "code", - "execution_count": 12, + "execution_count": 15, "metadata": {}, "outputs": [ { @@ -3215,7 +3452,7 @@ " 14.58 0.53 77.0 " ] }, - "execution_count": 12, + "execution_count": 15, "metadata": {}, "output_type": "execute_result" } @@ -3233,7 +3470,7 @@ }, { "cell_type": "code", - "execution_count": 13, + "execution_count": 16, "metadata": {}, "outputs": [ { @@ -3730,7 +3967,7 @@ " 7.10 2.43 173.0 " ] }, - "execution_count": 13, + "execution_count": 16, "metadata": {}, "output_type": "execute_result" } @@ -3748,7 +3985,7 @@ }, { "cell_type": "code", - "execution_count": 14, + "execution_count": 17, "metadata": {}, "outputs": [ { @@ -3819,21 +4056,6 @@ " \n", " \n", " \n", - " Mon, 3/29/2021\n", - " 2021\n", - " Everesting 1: Mt Diablo\n", - " 2.60\n", - " 22.22\n", - " 3406\n", - " 8.55\n", - " 399.0\n", - " 153.0\n", - " 2.90\n", - " 35.75\n", - " 1038.0\n", - " \n", - " \n", - " \n", " Tue, 3/30/2021\n", " 2021\n", " Everesting 2: Kings + WOLH + OLH\n", @@ -3849,6 +4071,21 @@ " \n", " \n", " \n", + " Mon, 3/29/2021\n", + " 2021\n", + " Everesting 1: Mt Diablo\n", + " 2.60\n", + " 22.22\n", + " 3406\n", + " 8.55\n", + " 399.0\n", + " 153.0\n", + " 2.90\n", + " 35.75\n", + " 1038.0\n", + " \n", + " \n", + " \n", " Sun, 12/1/2013\n", " 2013\n", " Mt. Hamilton\n", @@ -4095,8 +4332,8 @@ " 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", + " Mon, 3/29/2021 2021 Everesting 1: Mt Diablo 2.60 \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", @@ -4117,8 +4354,8 @@ " 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", + " 22.22 3406 8.55 399.0 153.0 2.90 35.75 1038.0 \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", @@ -4137,7 +4374,7 @@ " 32.33 2788 12.93 340.0 86.0 1.63 52.02 850.0 " ] }, - "execution_count": 14, + "execution_count": 17, "metadata": {}, "output_type": "execute_result" } @@ -4158,7 +4395,7 @@ }, { "cell_type": "code", - "execution_count": 15, + "execution_count": 18, "metadata": {}, "outputs": [ { @@ -4197,42 +4434,42 @@ " \n", " \n", " count\n", - " 541.000000\n", - " 541.000000\n", - " 541.000000\n", - " 541.000000\n", - " 541.000000\n", - " 541.000000\n", - " 541.000000\n", - " 541.000000\n", - " 541.000000\n", - " 541.000000\n", + " 545.000000\n", + " 545.000000\n", + " 545.000000\n", + " 545.000000\n", + " 545.000000\n", + " 545.000000\n", + " 545.000000\n", + " 545.000000\n", + " 545.000000\n", + " 545.000000\n", " \n", " \n", " mean\n", - " 2016.985213\n", - " 3.363882\n", - " 43.002107\n", - " 1822.046211\n", - " 12.985176\n", - " 157.634011\n", - " 41.500924\n", - " 0.785767\n", - " 69.190296\n", - " 555.364140\n", + " 2017.036697\n", + " 3.381119\n", + " 43.222330\n", + " 1835.176147\n", + " 12.992881\n", + " 157.930275\n", + " 41.550459\n", + " 0.786679\n", + " 69.544661\n", + " 559.366972\n", " \n", " \n", " std\n", - " 2.551645\n", - " 1.459116\n", - " 17.528475\n", - " 1495.022452\n", - " 1.317832\n", - " 89.937978\n", - " 27.231764\n", - " 0.515627\n", - " 28.203336\n", - " 455.678902\n", + " 2.611930\n", + " 1.474291\n", + " 17.659635\n", + " 1510.896504\n", + " 1.376471\n", + " 90.220516\n", + " 27.241663\n", + " 0.515809\n", + " 28.414416\n", + " 460.515601\n", " \n", " \n", " min\n", @@ -4251,40 +4488,40 @@ " 25%\n", " 2015.000000\n", " 2.210000\n", - " 29.060000\n", - " 732.000000\n", + " 29.180000\n", + " 739.000000\n", " 12.160000\n", " 81.000000\n", " 20.000000\n", " 0.370000\n", - " 46.760000\n", - " 223.000000\n", + " 46.950000\n", + " 225.000000\n", " \n", " \n", " 50%\n", " 2017.000000\n", - " 2.870000\n", - " 36.820000\n", + " 2.880000\n", + " 36.880000\n", " 1375.000000\n", " 13.140000\n", " 152.000000\n", " 36.000000\n", " 0.690000\n", - " 59.240000\n", + " 59.340000\n", " 419.000000\n", " \n", " \n", " 75%\n", " 2018.000000\n", - " 4.380000\n", - " 57.050000\n", - " 2323.000000\n", + " 4.430000\n", + " 57.640000\n", + " 2362.000000\n", " 13.780000\n", - " 218.000000\n", + " 219.000000\n", " 56.000000\n", " 1.070000\n", - " 91.790000\n", - " 708.000000\n", + " 92.740000\n", + " 720.000000\n", " \n", " \n", " max\n", @@ -4292,7 +4529,7 @@ " 8.140000\n", " 102.410000\n", " 7644.000000\n", - " 16.750000\n", + " 21.650000\n", " 406.000000\n", " 153.000000\n", " 2.900000\n", @@ -4305,27 +4542,27 @@ ], "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", + "count 545.000000 545.000000 545.000000 545.000000 545.000000 \n", + "mean 2017.036697 3.381119 43.222330 1835.176147 12.992881 \n", + "std 2.611930 1.474291 17.659635 1510.896504 1.376471 \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", + "25% 2015.000000 2.210000 29.180000 739.000000 12.160000 \n", + "50% 2017.000000 2.880000 36.880000 1375.000000 13.140000 \n", + "75% 2018.000000 4.430000 57.640000 2362.000000 13.780000 \n", + "max 2024.000000 8.140000 102.410000 7644.000000 21.650000 \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", + "count 545.000000 545.000000 545.000000 545.000000 545.000000 \n", + "mean 157.930275 41.550459 0.786679 69.544661 559.366972 \n", + "std 90.220516 27.241663 0.515809 28.414416 460.515601 \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", + "25% 81.000000 20.000000 0.370000 46.950000 225.000000 \n", + "50% 152.000000 36.000000 0.690000 59.340000 419.000000 \n", + "75% 219.000000 56.000000 1.070000 92.740000 720.000000 \n", "max 406.000000 153.000000 2.900000 164.780000 2330.000000 " ] }, - "execution_count": 15, + "execution_count": 18, "metadata": {}, "output_type": "execute_result" } @@ -4336,7 +4573,7 @@ }, { "cell_type": "code", - "execution_count": 16, + "execution_count": 19, "metadata": {}, "outputs": [ { @@ -4494,7 +4731,7 @@ "max 839.000000 15.890000 11.870000 575.000000 " ] }, - "execution_count": 16, + "execution_count": 19, "metadata": {}, "output_type": "execute_result" } @@ -4505,7 +4742,7 @@ }, { "cell_type": "code", - "execution_count": 17, + "execution_count": 20, "metadata": {}, "outputs": [ { @@ -4546,6 +4783,21 @@ " \n", " \n", " \n", + " Fri, 7/19/2024\n", + " 2024\n", + " Belmont\n", + " 3.37\n", + " 72.97\n", + " 3716\n", + " 21.65\n", + " 336.0\n", + " 51.0\n", + " 0.96\n", + " 117.41\n", + " 1133.0\n", + " \n", + " \n", + " \n", " Sun, 5/22/2016\n", " 2016\n", " Canada\n", @@ -4829,27 +5081,13 @@ " 50.65\n", " 247.0\n", " \n", - " \n", - " \n", - " Fri, 9/23/2016\n", - " 2016\n", - " Los Gatos\n", - " 2.89\n", - " 43.93\n", - " 1339\n", - " 15.20\n", - " 141.0\n", - " 30.0\n", - " 0.58\n", - " 70.68\n", - " 408.0\n", - " \n", " \n", "\n", "" ], "text/plain": [ " date year title hours miles feet \\\n", + " Fri, 7/19/2024 2024 Belmont 3.37 72.97 3716 \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", @@ -4869,9 +5107,9 @@ " 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", + " 21.65 336.0 51.0 0.96 117.41 1133.0 \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", @@ -4890,11 +5128,10 @@ " 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 " + " 15.28 120.0 26.0 0.49 50.65 247.0 " ] }, - "execution_count": 17, + "execution_count": 20, "metadata": {}, "output_type": "execute_result" } @@ -4905,7 +5142,7 @@ }, { "cell_type": "code", - "execution_count": 18, + "execution_count": 21, "metadata": {}, "outputs": [ { @@ -5252,7 +5489,7 @@ " 1.74 1.96 34.0 " ] }, - "execution_count": 18, + "execution_count": 21, "metadata": {}, "output_type": "execute_result" } @@ -5263,7 +5500,7 @@ }, { "cell_type": "code", - "execution_count": 19, + "execution_count": 22, "metadata": {}, "outputs": [ { @@ -5610,7 +5847,7 @@ " 2.09 128.0 " ] }, - "execution_count": 19, + "execution_count": 22, "metadata": {}, "output_type": "execute_result" } @@ -5621,7 +5858,7 @@ }, { "cell_type": "code", - "execution_count": 20, + "execution_count": 23, "metadata": {}, "outputs": [ { @@ -5968,7 +6205,7 @@ " 0.51 53.0 " ] }, - "execution_count": 20, + "execution_count": 23, "metadata": {}, "output_type": "execute_result" } @@ -5979,7 +6216,7 @@ }, { "cell_type": "code", - "execution_count": 21, + "execution_count": 24, "metadata": {}, "outputs": [ { @@ -6155,6 +6392,21 @@ " \n", " \n", " \n", + " Sat, 6/1/2024\n", + " 2024\n", + " OLH / Old Haul / Loma Mar / Pescadero / Tunita...\n", + " 7.84\n", + " 81.70\n", + " 7314\n", + " 10.42\n", + " 284.0\n", + " 90.0\n", + " 1.70\n", + " 131.46\n", + " 2229.0\n", + " \n", + " \n", + " \n", " Wed, 6/7/2023\n", " 2023\n", " Los Altos\n", @@ -6303,21 +6555,6 @@ " 126.11\n", " 692.0\n", " \n", - " \n", - " \n", - " Sat, 7/2/2022\n", - " 2022\n", - " Bear Gulch, West Side\n", - " 6.49\n", - " 77.73\n", - " 6991\n", - " 11.98\n", - " 328.0\n", - " 90.0\n", - " 1.70\n", - " 125.07\n", - " 2131.0\n", - " \n", " \n", "\n", "" @@ -6333,6 +6570,7 @@ " 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", + " 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", @@ -6343,7 +6581,6 @@ " 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", @@ -6355,6 +6592,7 @@ " 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", + " 7.84 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", @@ -6364,11 +6602,10 @@ " 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 " + " 5.89 78.38 2270 13.31 117.0 29.0 0.55 126.11 692.0 " ] }, - "execution_count": 21, + "execution_count": 24, "metadata": {}, "output_type": "execute_result" } diff --git a/ipynb/BikeCode.ipynb b/ipynb/BikeCode.ipynb index 82fc510..edb2eb2 100644 --- a/ipynb/BikeCode.ipynb +++ b/ipynb/BikeCode.ipynb @@ -13,7 +13,7 @@ }, { "cell_type": "code", - "execution_count": 1, + "execution_count": 2, "metadata": {}, "outputs": [], "source": [ @@ -42,7 +42,7 @@ }, { "cell_type": "code", - "execution_count": 2, + "execution_count": 3, "metadata": {}, "outputs": [], "source": [ @@ -80,7 +80,7 @@ }, { "cell_type": "code", - "execution_count": 3, + "execution_count": 4, "metadata": {}, "outputs": [], "source": [ @@ -110,7 +110,7 @@ }, { "cell_type": "code", - "execution_count": 4, + "execution_count": 5, "metadata": {}, "outputs": [], "source": [ @@ -127,7 +127,7 @@ }, { "cell_type": "code", - "execution_count": 5, + "execution_count": 6, "metadata": {}, "outputs": [], "source": [ @@ -146,13 +146,13 @@ }, { "cell_type": "code", - "execution_count": 6, + "execution_count": 7, "metadata": {}, "outputs": [], "source": [ "segments = parse_segments(open('bikesegments.csv'))\n", "\n", - "places = drop_index(pd.read_table(open('bikeplaceshort.csv'), sep=',', comment='#'))\n", + "places = drop_index(pd.read_table(open('bikeplaceshort.csv'), sep=',', comment='#'))\n", "\n", "tiles = drop_index(pd.DataFrame(columns='date square cluster total comment'.split(), data=[\n", " ('04/28/2024', 14, 1275, 3382, 'Livermore!11287081291'),\n", @@ -178,7 +178,7 @@ }, { "cell_type": "code", - "execution_count": 7, + "execution_count": 8, "metadata": {}, "outputs": [], "source": [ @@ -223,25 +223,35 @@ }, { "cell_type": "code", - "execution_count": 8, + "execution_count": 9, "metadata": {}, "outputs": [], "source": [ "def mapl(f, *values): return list(map(f, *values))\n", "\n", - "def wandering(places=places, by=['pct']):\n", + "def wandering(places=places, by='pct'):\n", " \"All those who wander are not lost.\" # Also try by=['cat', 'pct']\n", - " M = 1_000_000\n", - " F = drop_index(places.sort_values(by=by, ascending=('pct' not in by)))\n", + " F = drop_index(places.sort_values(by=by, ascending=False))\n", " pd.set_option('display.max_rows', None)\n", " return pd.DataFrame(\n", - " {'pct': [f'{p:.1f}%' if (p > 1) else f'{p:.3f}%' for p in F['pct']],\n", + " {'name': F['name'],\n", " 'county': F['county'],\n", - " 'name': F['name'],\n", - " 'total': F['miles'],\n", - " 'done': mapl(rounded, F['miles'] * F['pct'] / 100),\n", - " 'to next badge': mapl(to_go, F['pct'], F['miles'])})\n", + " 'total': F['miles'],\n", + " 'done': [rounded(m * p / 100) for m, p in zip(F['miles'], F['pct'])],\n", + " 'pct': [pretty_pct(p) for p in F['pct']], \n", + " 'badge': [badge(float(p)) for p in F['pct']],\n", + " 'to next badge': [to_go(p, m) for p, m in zip(F['pct'], F['miles'])]\n", + " })\n", "\n", + "def pretty_pct(pct) -> str:\n", + " return '100%' if pct == 100 else f'{pct:.2f}%' if pct > 1 else f'{pct:.4f}%'\n", + "\n", + "def badge(pct) -> str:\n", + " \"\"\"What badge has this got us?\"\"\"\n", + " for badge in (99, 90, 75, 50, 25):\n", + " if pct >= badge:\n", + " return f'{badge}%'\n", + " return 'none'\n", "\n", "def to_go(pct, miles, targets=(0.02, 0.1, 0.2, 1, 2, 25, 50, 90, 99)):\n", " \"\"\"Describe next target to hit to get a badge.\"\"\"\n", @@ -256,7 +266,10 @@ " return (rounded(x/1e6) + 'M' if x > 1e6\n", " else f'{x/1e6:4.2f}M' if x > 1e5\n", " else f'{round(x):,d}' if x > 10 \n", - " else f'{x:.1f}')" + " else f'{x:.1f}')\n", + "\n", + "small_places = wandering(places[places['county'] != '---'])\n", + "big_places = wandering(places[places['county'] == '---']).drop(columns='county')" ] }, { @@ -268,7 +281,7 @@ }, { "cell_type": "code", - "execution_count": 9, + "execution_count": 10, "metadata": {}, "outputs": [], "source": [ @@ -309,7 +322,7 @@ }, { "cell_type": "code", - "execution_count": 11, + "execution_count": 17, "metadata": {}, "outputs": [], "source": [ @@ -321,7 +334,7 @@ "\n", "def Ed_gap(distances, target) -> int:\n", " \"\"\"The number of rides needed to reach an Eddington number target.\"\"\"\n", - " return target - sum(distances >= target)\n", + " return target - count(distances >= target)\n", "\n", "def Ed_gaps(rides, N=9) -> dict:\n", " \"\"\"A table of gaps to Eddington numbers by year.\"\"\"\n", @@ -336,15 +349,1263 @@ " def Ed(year, unit): return Ed_number(rides[rides['year'] <= year], unit)\n", " data = [(y, Ed(y, 'kms'), Ed(y, 'miles')) for y in years]\n", " df = pd.DataFrame(data, columns=['year', 'Ed_km', 'Ed_mi'])\n", - " return drop_index(df)" + " return drop_index(df)\n", + "\n", + "def count_rides(rides, unit='kms', distance=100) -> int:\n", + " return count(rides[unit] > distance)\n", + "\n", + "count = sum" ] }, { "cell_type": "code", - "execution_count": null, + "execution_count": 12, "metadata": {}, - "outputs": [], - "source": [] + "outputs": [ + { + "data": { + "text/html": [ + "
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namemilescountypct
Atherton56.30SMC99.800
Bay Area Ridge Trail395.60SMC28.680
Belmont98.10SMC75.430
Brisbane40.90SMC50.400
Broadmoor8.80SMC38.260
Burleigh Murray Park2.10SMC95.080
Burlingame88.40SMC56.880
Burlingame Hills6.00SMC71.500
Butano State Park15.20SMC30.100
Coal Creek Preserve3.90SMC66.700
Colma13.70SMC66.240
Daly City148.10SMC28.270
East Palo Alto48.30SMC99.950
El Corte de Madera OSP34.54SMC26.880
El Granada49.20SMC43.600
Emerald Lake Hills24.60SMC99.960
Foster City150.00SMC99.400
Half Moon Bay68.00SMC34.000
Half Moon Bay State Beach4.40SMC52.400
Hillsborough85.30SMC53.100
Kensington Square0.60SMC100.000
Ladera8.10SMC100.000
Long Ridge Preserve11.00SMC45.100
Los Trancos OSP0.30SMC100.000
Los Trancos Woods5.30SMC100.000
Menlo Oaks3.50SMC100.000
Menlo Park139.50SMC99.700
Millbrae65.00SMC51.300
Montara27.80SMC60.200
Moss Beach19.70SMC43.690
North Fair Oaks26.70SMC100.000
Pacifica150.90SMC33.200
Palomar Park4.00SMC100.000
Portola Redwoods SP2.90SMC74.300
Portola Valley48.20SMC99.120
Purisima Creek Preserve16.50SMC39.000
Redwood City240.50SMC99.730
Russian Ridge Preserve12.20SMC59.500
San Bruno114.00SMC34.900
San Carlos99.00SMC99.430
San Mateo256.00SMC54.600
San Mateo Highlands18.00SMC93.500
Sequoia Tract11.00SMC100.000
Sky Londa11.80SMC99.700
Skyline Ridge OSP0.80SMC76.400
South San Francisco185.30SMC30.980
West Menlo Park11.20SMC99.750
Windy Hill Preserve4.10SMC100.000
Woodside75.20SMC99.740
Branham44.00SCC33.200
Campbell119.00SCC30.300
Communications Hill27.80SCC39.500
Cupertino172.00SCC54.990
Edenvale30.00SCC47.700
Foothills OS Preserve1.10SCC100.000
Gardner23.40SCC47.200
Gilroy188.90SCC26.400
Los Altos138.20SCC99.800
Los Altos Hills91.30SCC99.560
Los Gatos148.00SCC51.600
Loyola18.30SCC99.940
Milpitas224.00SCC36.700
Monte Sereno20.40SCC52.400
Mountain View208.10SCC99.640
Palo Alto297.20SCC99.450
Parkview42.50SCC33.700
San Francisco Bay Trail260.80SCC68.470
San Jose2618.70SCC28.000
San Martin35.30SCC31.500
Santa Clara348.00SCC34.800
Saratoga180.00SCC51.400
Seven Trees40.90SCC34.000
Spartan Keyes64.30SCC36.800
Sunnyvale357.00SCC55.300
Willow Glen81.60SCC36.000
Willow Glen South63.30SCC30.900
Alameda206.70ALA12.200
Albany42.70ALA6.800
Ashland35.10ALA36.100
Berkeley260.30ALA7.800
Castro Valley192.50ALA26.100
Cherryland20.90ALA27.800
Emeryville28.10ALA7.700
Fairview34.40ALA29.200
Fremont780.20ALA34.300
Hayward444.50ALA33.200
Hayward Acres3.50ALA43.300
Newark147.00ALA51.600
San Leandro230.60ALA28.100
San Lorenzo55.50ALA40.950
Union City208.80ALA33.370
Aquatic Park Fort Mason6.40SFC15.400
Ashbury Heights3.70SFC13.000
Balboa Terrace3.40SFC18.200
Central Waterfront10.20SFC6.000
Clarendon Heights6.00SFC14.200
Cole Valley1.70SFC18.000
Cow Hollow12.00SFC11.900
Dogpatch5.10SFC12.300
Financial District9.40SFC10.200
Fisherman's Wharf6.20SFC13.800
Forest Hill6.10SFC15.900
Golden Gate Heights17.80SFC10.700
Golden Gate Park40.80SFC29.400
Lake Street3.90SFC36.800
Lincoln Park4.50SFC39.600
Little Hollywood3.70SFC15.200
Mission Bay13.80SFC8.600
Northern Waterfront5.60SFC15.500
Pacific Heights18.00SFC10.700
Panhandle7.30SFC20.600
Polk Gulch4.00SFC18.200
Presidio Heights6.50SFC21.600
Presidio National Park43.50SFC26.700
Presidio Terrace2.80SFC43.900
Seacliff4.10SFC29.300
South Beach4.80SFC37.400
Sutro Heights7.10SFC13.200
Barangaroo1.70NSW47.300
Bodega Bay28.90SON17.000
Cambridge180.80MAS6.200
Castle Rock State Park11.20SCC51.200
Corte Madera51.00MAR12.900
Dawes Point1.80NSW29.200
Forest of Nisene Marks SP44.00SCC30.700
Guerneville22.70SON23.600
Healdsburg53.70SON17.800
Marin Headlands GGNRA65.70MAR31.900
Mill Valley92.20MAR9.100
Millers Point3.20NSW34.300
MIT9.60MAS34.700
Mokelumne Hill14.70CAL26.800
Mt Tamalpais State Park31.70MAR38.700
Muir Beach4.60MAR37.100
Rosie Riveter Park5.50CCC73.200
San Rafael260.00MAR3.700
Sausalito32.70MAR12.900
Stinson Beach11.20MAR32.900
San Mateo County2814.00---66.640
Santa Clara County7569.00---35.600
Alameda County5818.00---17.710
Marin County2333.00---10.940
San Francisco County1217.00---9.260
Napa County1609.00---8.900
Sonoma County4895.00---5.120
Santa Cruz County2718.00---7.120
Contra Costa County5945.00---3.800
California377037.00---1.920
USA6406754.00---0.120
Earth41974536.00---0.018
\n", + "
" + ], + "text/plain": [ + " name miles county pct\n", + " Atherton 56.30 SMC 99.800\n", + " Bay Area Ridge Trail 395.60 SMC 28.680\n", + " Belmont 98.10 SMC 75.430\n", + " Brisbane 40.90 SMC 50.400\n", + " Broadmoor 8.80 SMC 38.260\n", + " Burleigh Murray Park 2.10 SMC 95.080\n", + " Burlingame 88.40 SMC 56.880\n", + " Burlingame Hills 6.00 SMC 71.500\n", + " Butano State Park 15.20 SMC 30.100\n", + " Coal Creek Preserve 3.90 SMC 66.700\n", + " Colma 13.70 SMC 66.240\n", + " Daly City 148.10 SMC 28.270\n", + " East Palo Alto 48.30 SMC 99.950\n", + " El Corte de Madera OSP 34.54 SMC 26.880\n", + " El Granada 49.20 SMC 43.600\n", + " Emerald Lake Hills 24.60 SMC 99.960\n", + " Foster City 150.00 SMC 99.400\n", + " Half Moon Bay 68.00 SMC 34.000\n", + " Half Moon Bay State Beach 4.40 SMC 52.400\n", + " Hillsborough 85.30 SMC 53.100\n", + " Kensington Square 0.60 SMC 100.000\n", + " Ladera 8.10 SMC 100.000\n", + " Long Ridge Preserve 11.00 SMC 45.100\n", + " Los Trancos OSP 0.30 SMC 100.000\n", + " Los Trancos Woods 5.30 SMC 100.000\n", + " Menlo Oaks 3.50 SMC 100.000\n", + " Menlo Park 139.50 SMC 99.700\n", + " Millbrae 65.00 SMC 51.300\n", + " Montara 27.80 SMC 60.200\n", + " Moss Beach 19.70 SMC 43.690\n", + " North Fair Oaks 26.70 SMC 100.000\n", + " Pacifica 150.90 SMC 33.200\n", + " Palomar Park 4.00 SMC 100.000\n", + " Portola Redwoods SP 2.90 SMC 74.300\n", + " Portola Valley 48.20 SMC 99.120\n", + " Purisima Creek Preserve 16.50 SMC 39.000\n", + " Redwood City 240.50 SMC 99.730\n", + " Russian Ridge Preserve 12.20 SMC 59.500\n", + " San Bruno 114.00 SMC 34.900\n", + " San Carlos 99.00 SMC 99.430\n", + " San Mateo 256.00 SMC 54.600\n", + " San Mateo Highlands 18.00 SMC 93.500\n", + " Sequoia Tract 11.00 SMC 100.000\n", + " Sky Londa 11.80 SMC 99.700\n", + " Skyline Ridge OSP 0.80 SMC 76.400\n", + " South San Francisco 185.30 SMC 30.980\n", + " West Menlo Park 11.20 SMC 99.750\n", + " Windy Hill Preserve 4.10 SMC 100.000\n", + " Woodside 75.20 SMC 99.740\n", + " Branham 44.00 SCC 33.200\n", + " Campbell 119.00 SCC 30.300\n", + " Communications Hill 27.80 SCC 39.500\n", + " Cupertino 172.00 SCC 54.990\n", + " Edenvale 30.00 SCC 47.700\n", + " Foothills OS Preserve 1.10 SCC 100.000\n", + " Gardner 23.40 SCC 47.200\n", + " Gilroy 188.90 SCC 26.400\n", + " Los Altos 138.20 SCC 99.800\n", + " Los Altos Hills 91.30 SCC 99.560\n", + " Los Gatos 148.00 SCC 51.600\n", + " Loyola 18.30 SCC 99.940\n", + " Milpitas 224.00 SCC 36.700\n", + " Monte Sereno 20.40 SCC 52.400\n", + " Mountain View 208.10 SCC 99.640\n", + " Palo Alto 297.20 SCC 99.450\n", + " Parkview 42.50 SCC 33.700\n", + " San Francisco Bay Trail 260.80 SCC 68.470\n", + " San Jose 2618.70 SCC 28.000\n", + " San Martin 35.30 SCC 31.500\n", + " Santa Clara 348.00 SCC 34.800\n", + " Saratoga 180.00 SCC 51.400\n", + " Seven Trees 40.90 SCC 34.000\n", + " Spartan Keyes 64.30 SCC 36.800\n", + " Sunnyvale 357.00 SCC 55.300\n", + " Willow Glen 81.60 SCC 36.000\n", + " Willow Glen South 63.30 SCC 30.900\n", + " Alameda 206.70 ALA 12.200\n", + " Albany 42.70 ALA 6.800\n", + " Ashland 35.10 ALA 36.100\n", + " Berkeley 260.30 ALA 7.800\n", + " Castro Valley 192.50 ALA 26.100\n", + " Cherryland 20.90 ALA 27.800\n", + " Emeryville 28.10 ALA 7.700\n", + " Fairview 34.40 ALA 29.200\n", + " Fremont 780.20 ALA 34.300\n", + " Hayward 444.50 ALA 33.200\n", + " Hayward Acres 3.50 ALA 43.300\n", + " Newark 147.00 ALA 51.600\n", + " San Leandro 230.60 ALA 28.100\n", + " San Lorenzo 55.50 ALA 40.950\n", + " Union City 208.80 ALA 33.370\n", + " Aquatic Park Fort Mason 6.40 SFC 15.400\n", + " Ashbury Heights 3.70 SFC 13.000\n", + " Balboa Terrace 3.40 SFC 18.200\n", + " Central Waterfront 10.20 SFC 6.000\n", + " Clarendon Heights 6.00 SFC 14.200\n", + " Cole Valley 1.70 SFC 18.000\n", + " Cow Hollow 12.00 SFC 11.900\n", + " Dogpatch 5.10 SFC 12.300\n", + " Financial District 9.40 SFC 10.200\n", + " Fisherman's Wharf 6.20 SFC 13.800\n", + " Forest Hill 6.10 SFC 15.900\n", + " Golden Gate Heights 17.80 SFC 10.700\n", + " Golden Gate Park 40.80 SFC 29.400\n", + " Lake Street 3.90 SFC 36.800\n", + " Lincoln Park 4.50 SFC 39.600\n", + " Little Hollywood 3.70 SFC 15.200\n", + " Mission Bay 13.80 SFC 8.600\n", + " Northern Waterfront 5.60 SFC 15.500\n", + " Pacific Heights 18.00 SFC 10.700\n", + " Panhandle 7.30 SFC 20.600\n", + " Polk Gulch 4.00 SFC 18.200\n", + " Presidio Heights 6.50 SFC 21.600\n", + " Presidio National Park 43.50 SFC 26.700\n", + " Presidio Terrace 2.80 SFC 43.900\n", + " Seacliff 4.10 SFC 29.300\n", + " South Beach 4.80 SFC 37.400\n", + " Sutro Heights 7.10 SFC 13.200\n", + " Barangaroo 1.70 NSW 47.300\n", + " Bodega Bay 28.90 SON 17.000\n", + " Cambridge 180.80 MAS 6.200\n", + " Castle Rock State Park 11.20 SCC 51.200\n", + " Corte Madera 51.00 MAR 12.900\n", + " Dawes Point 1.80 NSW 29.200\n", + " Forest of Nisene Marks SP 44.00 SCC 30.700\n", + " Guerneville 22.70 SON 23.600\n", + " Healdsburg 53.70 SON 17.800\n", + " Marin Headlands GGNRA 65.70 MAR 31.900\n", + " Mill Valley 92.20 MAR 9.100\n", + " Millers Point 3.20 NSW 34.300\n", + " MIT 9.60 MAS 34.700\n", + " Mokelumne Hill 14.70 CAL 26.800\n", + " Mt Tamalpais State Park 31.70 MAR 38.700\n", + " Muir Beach 4.60 MAR 37.100\n", + " Rosie Riveter Park 5.50 CCC 73.200\n", + " San Rafael 260.00 MAR 3.700\n", + " Sausalito 32.70 MAR 12.900\n", + " Stinson Beach 11.20 MAR 32.900\n", + " San Mateo County 2814.00 --- 66.640\n", + " Santa Clara County 7569.00 --- 35.600\n", + " Alameda County 5818.00 --- 17.710\n", + " Marin County 2333.00 --- 10.940\n", + " San Francisco County 1217.00 --- 9.260\n", + " Napa County 1609.00 --- 8.900\n", + " Sonoma County 4895.00 --- 5.120\n", + " Santa Cruz County 2718.00 --- 7.120\n", + " Contra Costa County 5945.00 --- 3.800\n", + " California 377037.00 --- 1.920\n", + " USA 6406754.00 --- 0.120\n", + " Earth 41974536.00 --- 0.018" + ] + }, + "execution_count": 12, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "places" + ] } ], "metadata": { diff --git a/ipynb/bikeplaceshort.csv b/ipynb/bikeplaceshort.csv index 5f96b0e..2724b35 100644 --- a/ipynb/bikeplaceshort.csv +++ b/ipynb/bikeplaceshort.csv @@ -3,80 +3,82 @@ name,miles,county,pct # San Mateo County = SMC # Atherton,56.3,SMC,99.8 -Bay Area Ridge Trail,395.6,SMC,25.6 -Belmont,98.1,SMC,54.7 -Brisbane,40.9,SMC,50.2 -Broadmoor,8.8,SMC,38.2 -Burleigh Murray Park,2.1,SMC,90.9 +Bay Area Ridge Trail,395.6,SMC,28.68 +Belmont,98.1,SMC,75.43 +Brisbane,40.9,SMC,50.4 +Broadmoor,8.8,SMC,38.26 +Burleigh Murray Park,2.1,SMC,95.08 +Burlingame,88.4,SMC,56.88 Burlingame Hills,6,SMC,71.5 -Burlingame,88.4,SMC,56.2 Butano State Park,15.2,SMC,30.1 Coal Creek Preserve,3.9,SMC,66.7 -Colma,13.7,SMC,38.9 -Daly City,148.1,SMC,27.4 -East Palo Alto,48.3,SMC,99.7 +Colma,13.7,SMC,66.24 +Daly City,148.1,SMC,28.27 +East Palo Alto,48.3,SMC,99.95 +El Corte de Madera OSP,34.54,SMC,26.88 El Granada,49.2,SMC,43.6 -Emerald Lake Hills,24.6,SMC,99.9 -Foster City,150,SMC,90.4 -Half Moon Bay,68,SMC,33.6 -Half Moon Bay State Beach,4.4,SMC,51.5 -Hillsborough,85.3,SMC,52.3 +Emerald Lake Hills,24.6,SMC,99.96 +Foster City,150,SMC,99.4 +Half Moon Bay,68,SMC,34.0 +Half Moon Bay State Beach,4.4,SMC,52.4 +Hillsborough,85.3,SMC,53.1 Kensington Square,0.6,SMC,100 Ladera,8.1,SMC,100 -Long Ridge Preserve,11.0,SMC,51.2 +Long Ridge Preserve,11.0,SMC,45.1 Los Trancos OSP,0.3,SMC,100 Los Trancos Woods,5.3,SMC,100 Menlo Oaks,3.5,SMC,100 Menlo Park,139.5,SMC,99.7 -Millbrae,65,SMC,42.6 -Montara,27.8,SMC,59.3 -Moss Beach,19.7,SMC,43.6 +Millbrae,65,SMC,51.3 +Montara,27.8,SMC,60.2 +Moss Beach,19.7,SMC,43.69 North Fair Oaks,26.7,SMC,100 Pacifica,150.9,SMC,33.2 -Palomar Park,4,SMC,99.9 -Portola Valley,48.2,SMC,99.5 +Palomar Park,4,SMC,100 +Portola Redwoods SP,2.9,SMC,74.3 +Portola Valley,48.2,SMC,99.12 Purisima Creek Preserve,16.5,SMC,39.0 -Redwood City,240.5,SMC,99.3 +Redwood City,240.5,SMC,99.73 Russian Ridge Preserve,12.2,SMC,59.5 -San Bruno,114,SMC,31.0 -San Carlos,99,SMC,99.2 -San Mateo,256,SMC,51.8 +San Bruno,114,SMC,34.9 +San Carlos,99,SMC,99.43 +San Mateo,256,SMC,54.6 San Mateo Highlands,18,SMC,93.5 Sequoia Tract,11,SMC,100 -Sky Londa,11.8,SMC,99.6 +Sky Londa,11.8,SMC,99.7 Skyline Ridge OSP,0.8,SMC,76.4 -South San Francisco,185.3,SMC,29.6 -West Menlo Park,11.2,SMC,100 -Windy Hill Preserve,4.1,SMC,99.8 -Woodside,75.2,SMC,99.4 +South San Francisco,185.3,SMC,30.98 +West Menlo Park,11.2,SMC,99.75 +Windy Hill Preserve,4.1,SMC,100 +Woodside,75.2,SMC,99.74 # # Santa Clara County = SCC # -Branham,44,SCC,32.7 -Campbell,119,SCC,29.3 +Branham,44,SCC,33.2 +Campbell,119,SCC,30.3 Communications Hill,27.8,SCC,39.5 -Cupertino,172,SCC,52.8 +Cupertino,172,SCC,54.99 Edenvale,30,SCC,47.7 -Foothills Preserve,1.1,SCC,86.8 +Foothills OS Preserve,1.1,SCC,100 Gardner,23.4,SCC,47.2 Gilroy,188.9,SCC,26.4 -Los Altos,138.2,SCC,99.6 -Los Altos Hills,91.3,SCC,99.2 -Los Gatos,148,SCC,33.6 -Loyola,18.3,SCC,99.9 +Los Altos,138.2,SCC,99.8 +Los Altos Hills,91.3,SCC,99.56 +Los Gatos,148,SCC,51.6 +Loyola,18.3,SCC,99.94 Milpitas,224,SCC,36.7 Monte Sereno,20.4,SCC,52.4 -Mountain View,208.1,SCC,99.3 -Palo Alto,297.2,SCC,99.0 +Mountain View,208.1,SCC,99.64 +Palo Alto,297.2,SCC,99.45 Parkview,42.5,SCC,33.7 -San Francisco Bay Trail,260.8,SCC,74.1 +San Francisco Bay Trail,260.8,SCC,68.47 San Jose,2618.7,SCC,28 San Martin,35.3,SCC,31.5 Santa Clara,348,SCC,34.8 -Saratoga,180,SCC,50.4 -Seven Trees,40.9,SCC,33 +Saratoga,180,SCC,51.4 +Seven Trees,40.9,SCC,34 Spartan Keyes,64.3,SCC,36.8 -Sunnyvale,357,SCC,53.3 +Sunnyvale,357,SCC,55.3 Willow Glen,81.6,SCC,36 Willow Glen South,63.3,SCC,30.9 # @@ -85,18 +87,18 @@ Willow Glen South,63.3,SCC,30.9 Alameda,206.7,ALA,12.2 Albany,42.7,ALA,6.8 Ashland,35.1,ALA,36.1 -Berkeley,260.3,ALA,7.6 +Berkeley,260.3,ALA,7.8 Castro Valley,192.5,ALA,26.1 Cherryland,20.9,ALA,27.8 Emeryville,28.1,ALA,7.7 -Fairview,34.4,ALA,28.2 -Fremont,780.2,ALA,32.9 -Hayward,444.5,ALA,32.7 +Fairview,34.4,ALA,29.2 +Fremont,780.2,ALA,34.3 +Hayward,444.5,ALA,33.2 Hayward Acres,3.5,ALA,43.3 -Newark,147,ALA,51 -San Leandro,230.6,ALA,27.7 -San Lorenzo,55.5,ALA,40.8 -Union City,208.8,ALA,32.9 +Newark,147,ALA,51.6 +San Leandro,230.6,ALA,28.1 +San Lorenzo,55.5,ALA,40.95 +Union City,208.8,ALA,33.37 # # SF County = SFC # @@ -153,9 +155,9 @@ Stinson Beach,11.2,MAR,32.9 # # Counties and Bigger # -San Mateo County,2814,---,63.5 -Santa Clara County,7569,---,33.0 -Alameda County,5818,---,16.58 +San Mateo County,2814,---,66.64 +Santa Clara County,7569,---,35.6 +Alameda County,5818,---,17.71 Marin County,2333,---,10.94 San Francisco County,1217,---,9.26 Napa County,1609,---,8.9 @@ -163,6 +165,6 @@ Sonoma County,4895,---,5.12 Santa Cruz County,2718,---,7.12 Contra Costa County,5945,---,3.8 # -California,377037,---,1.782 -USA,6406754,---,0.11343 -Earth,41974536,---,0.017055 \ No newline at end of file +California,377037,---,1.92 +USA,6406754,---,0.12 +Earth,41974536,---,0.018 \ No newline at end of file diff --git a/ipynb/bikerides.tsv b/ipynb/bikerides.tsv index 09f76d1..5b35da0 100644 --- a/ipynb/bikerides.tsv +++ b/ipynb/bikerides.tsv @@ -1,7 +1,11 @@ date title hours miles feet # -##### 2019-2024: Mostly Eddington rides; most recent first +# 2024 # +Fri, 7/19/2024 Belmont 3:22:04 72.97 3,716 +Sat, 7/13/2024 100K Km + Morning Ride 6:27:14 63.59 2,487 +Wed, 7/10/2024 Completed Foster City 5:11:12 73.77 927 +Sat, 6/1/2024 OLH / Old Haul / Loma Mar / Pescadero / Tunitas / Kings 7:50:15 81.70 7,314 Mon, 5/27/2024 Saratoga 4:49:50 77.25 1,749 Sat, 5/25/2024 Niles 5:36:13 75.71 1,396 Sat, 3/9/2024 Millbrae / San Bruno / Sawyer Camp Trail / Bay Trail 8:07:10 98.52 4,896 @@ -47,7 +51,7 @@ Sat, 4/9/2022 Kings / Skyline / 92 6:07:05 69.29 5,029 Sat, 1/29/2022 Woodside plus Montebello 6:49:14 67.73 5,553 Sat, 1/15/2022 Crestview 5:43:00 64.49 4,446 # -# 2021 +# 2021 and earlier # Sun, 11/14/2021 Hayward 5:08:23 72.23 1,132 Sat, 10/16/2021 San Jose 5:47:00 70.18 2,562