{
"cells": [
{
"cell_type": "markdown",
"metadata": {},
"source": [
"# I Just Felt Like Running\n",
"\n",
"### Running on 365 consecutive days for no other reason"
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"March 2017 was a bad month for my running -- I only ran [four times](http://smashrun.com/ixjlyons/overview/2017/3). By early April, I decided it would be cool to try to go on a little run streak to get things going again. At first, I think the goal was 10 days straight. And after that, 20 days. And then, I decided to make my longest streak longer than my longest break (34 days). You get the point. Now here we are, 365 days later."
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"![I just felt like running](http://i.imgur.com/lz6mc3v.gif)"
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"I use Runkeeper on my phone to track GPS coordinates of every run I go on, so in commemoration of an aribtrary set of 365 consecutive days, I thought it'd be cool to take a look at the data.\n",
"\n",
"On Runkeeper, you can go to Settings, then Export Data, and select the appropriate date range. This gives you a zip file containing a CSV file (`cardioActivities.csv`) summarizing every tracked activity, and a [GPX](https://en.wikipedia.org/wiki/GPS_Exchange_Format) file for each activity containing the GPS coordinates sampled every few seconds."
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"## Summary\n",
"\n",
"I'll start with `cardioActivities.csv` to just get a summary of how the year went."
]
},
{
"cell_type": "code",
"execution_count": 1,
"metadata": {},
"outputs": [
{
"data": {
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Date
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Route Name
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Distance (km)
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Duration
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Average Pace
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Average Speed (km/h)
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Calories Burned
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Average Heart Rate (bpm)
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2018-04-05-1812.gpx
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3
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2018-04-04-0753.gpx
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Running
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NaN
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5.61
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28:27
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5:04
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11.83
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483.0
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1
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NaN
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NaN
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2018-04-03-0902.gpx
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"text/plain": [
" Date Type Route Name Distance (km) Duration \\\n",
"0 2018-04-07 09:21:31 Running NaN 3.65 18:14 \n",
"1 2018-04-06 07:30:17 Running NaN 2.66 13:57 \n",
"2 2018-04-05 18:12:03 Running NaN 5.68 30:00 \n",
"3 2018-04-04 07:53:16 Running NaN 5.37 27:36 \n",
"4 2018-04-03 09:02:23 Running NaN 5.61 28:27 \n",
"\n",
" Average Pace Average Speed (km/h) Calories Burned Climb (m) \\\n",
"0 5:00 12.00 315.0 2 \n",
"1 5:15 11.43 229.0 2 \n",
"2 5:17 11.35 491.0 5 \n",
"3 5:09 11.66 464.0 4 \n",
"4 5:04 11.83 483.0 1 \n",
"\n",
" Average Heart Rate (bpm) Notes GPX File \n",
"0 NaN NaN 2018-04-07-0921.gpx \n",
"1 NaN NaN 2018-04-06-0730.gpx \n",
"2 NaN NaN 2018-04-05-1812.gpx \n",
"3 NaN NaN 2018-04-04-0753.gpx \n",
"4 NaN NaN 2018-04-03-0902.gpx "
]
},
"execution_count": 1,
"metadata": {},
"output_type": "execute_result"
}
],
"source": [
"import os\n",
"import numpy as np\n",
"import pandas as pd\n",
"import matplotlib.pyplot as plt\n",
"%matplotlib inline\n",
"\n",
"datadir = 'activities'\n",
"summary_csv = os.path.join(datadir, 'cardioActivities.csv')\n",
"\n",
"activities = pd.read_csv(summary_csv)\n",
"activities.head()"
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"The data needs a little cleaning up by removing cycling activities (tracked during [May is Bike Month](https://mayisbikemonth.com/)) and converting the `Date` column to a proper datetime type. I also want to aggregate data for days on which I ran multiple times (usually to and from a location), so I can add a separate column for the full date+time and remove the time from the date column."
]
},
{
"cell_type": "code",
"execution_count": 2,
"metadata": {},
"outputs": [
{
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Average Heart Rate (bpm)
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11.83
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"text/plain": [
" Date Type Route Name Distance (km) Duration Average Pace \\\n",
"0 2018-04-07 Running NaN 3.65 18:14 5:00 \n",
"1 2018-04-06 Running NaN 2.66 13:57 5:15 \n",
"2 2018-04-05 Running NaN 5.68 30:00 5:17 \n",
"3 2018-04-04 Running NaN 5.37 27:36 5:09 \n",
"4 2018-04-03 Running NaN 5.61 28:27 5:04 \n",
"\n",
" Average Speed (km/h) Calories Burned Climb (m) Average Heart Rate (bpm) \\\n",
"0 12.00 315.0 2 NaN \n",
"1 11.43 229.0 2 NaN \n",
"2 11.35 491.0 5 NaN \n",
"3 11.66 464.0 4 NaN \n",
"4 11.83 483.0 1 NaN \n",
"\n",
" Notes GPX File Datetime \n",
"0 NaN 2018-04-07-0921.gpx 2018-04-07 09:21:31 \n",
"1 NaN 2018-04-06-0730.gpx 2018-04-06 07:30:17 \n",
"2 NaN 2018-04-05-1812.gpx 2018-04-05 18:12:03 \n",
"3 NaN 2018-04-04-0753.gpx 2018-04-04 07:53:16 \n",
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},
"execution_count": 2,
"metadata": {},
"output_type": "execute_result"
}
],
"source": [
"activities = activities[activities.Type == 'Running']\n",
"activities['Datetime'] = pd.to_datetime(activities['Date'])\n",
"activities['Date'] = activities['Datetime'].dt.normalize()\n",
"activities.head()"
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"Now for the aggregation. Distance should be accumulated by adding up all runs for a day, whereas it makes a bit more sense to just average the speed for different runs on a day."
]
},
{
"cell_type": "code",
"execution_count": 3,
"metadata": {
"scrolled": true
},
"outputs": [
{
"data": {
"text/html": [
"
\n",
"\n",
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\n",
" \n",
"
\n",
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\n",
"
Distance (km)
\n",
"
Average Speed (km/h)
\n",
"
Calories Burned
\n",
"
Climb (m)
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"
\n",
" \n",
" \n",
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\n",
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count
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365.000000
\n",
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365.000000
\n",
"
365.000000
\n",
"
365.000000
\n",
"
\n",
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\n",
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mean
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7.269151
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11.612251
\n",
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628.715068
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11.394521
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std
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4.485533
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0.927397
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390.872166
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33.269181
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1.870000
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4.520000
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64.000000
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0.000000
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25%
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11.230000
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393.000000
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2.000000
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50%
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11.650000
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523.000000
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4.000000
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816.000000
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9.000000
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14.950000
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3654.000000
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383.000000
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\n",
" \n",
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\n",
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"
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"text/plain": [
" Distance (km) Average Speed (km/h) Calories Burned Climb (m)\n",
"count 365.000000 365.000000 365.000000 365.000000\n",
"mean 7.269151 11.612251 628.715068 11.394521\n",
"std 4.485533 0.927397 390.872166 33.269181\n",
"min 1.870000 4.520000 64.000000 0.000000\n",
"25% 4.540000 11.230000 393.000000 2.000000\n",
"50% 6.060000 11.650000 523.000000 4.000000\n",
"75% 9.290000 12.100000 816.000000 9.000000\n",
"max 42.220000 14.950000 3654.000000 383.000000"
]
},
"execution_count": 3,
"metadata": {},
"output_type": "execute_result"
}
],
"source": [
"activities = activities.groupby('Date').agg({\n",
" 'Distance (km)': np.sum,\n",
" 'Average Speed (km/h)': np.mean,\n",
" 'Calories Burned': np.sum,\n",
" 'Climb (m)': np.sum,\n",
"}).reset_index()\n",
"\n",
"activities.describe()"
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"There, now we have exactly 365 rows. One measurement of interest is the total distance run for the year."
]
},
{
"cell_type": "code",
"execution_count": 4,
"metadata": {},
"outputs": [
{
"data": {
"text/plain": [
"2653.24"
]
},
"execution_count": 4,
"metadata": {},
"output_type": "execute_result"
}
],
"source": [
"activities['Distance (km)'].sum()"
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"In terms of distance between state capitols, that's pretty close to Google's estimate of the [walking distance from Sacramento, CA to Topeka, KS](https://www.google.com/maps/dir/sacramento/topeka/@39.2229955,-117.5752175,5z/data=!3m1!4b1!4m14!4m13!1m5!1m1!1s0x809ac672b28397f9:0x921f6aaa74197fdb!2m2!1d-121.4943996!2d38.5815719!1m5!1m1!1s0x87bf02e4daec7a29:0xbe2be7d06ae3a7f0!2m2!1d-95.6890185!2d39.0558235!3e2).\n",
"\n",
"Aside from total distance, I've been interested in seeing my run distance per day for the year."
]
},
{
"cell_type": "code",
"execution_count": 5,
"metadata": {},
"outputs": [
{
"data": {
"text/plain": [
"Text(0,0.5,'distance per day (km)')"
]
},
"execution_count": 5,
"metadata": {},
"output_type": "execute_result"
},
{
"data": {
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\n",
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