openrun/examples/notebooks/01_overview.ipynb

{
 "cells": [
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# 01 — Overview\n",
    "\n",
    "Sanity-check the synced data: what's there, how complete it is, and what you've been up to recently.\n",
    "\n",
    "**Kernel:** pick the `.venv` from `garmin/` (top-right of this notebook)."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 1,
   "metadata": {},
   "outputs": [],
   "source": [
    "import sys\n",
    "sys.path.insert(0, '..')  # so we can import analysis.py from the project root\n",
    "\n",
    "import pandas as pd\n",
    "import matplotlib.pyplot as plt\n",
    "from openrun import open_conn, load_activities, load_wellness\n",
    "\n",
    "pd.options.display.float_format = '{:.2f}'.format\n",
    "conn = open_conn()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Data coverage"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 2,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
       "        vertical-align: middle;\n",
       "    }\n",
       "\n",
       "    .dataframe tbody tr th {\n",
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       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: right;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>table</th>\n",
       "      <th>rows</th>\n",
       "      <th>from</th>\n",
       "      <th>to</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>activities</td>\n",
       "      <td>378</td>\n",
       "      <td>1658945478000.0</td>\n",
       "      <td>2026-05-10 10:43:58</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>activity_fit_files</td>\n",
       "      <td>349</td>\n",
       "      <td></td>\n",
       "      <td></td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>activity_splits</td>\n",
       "      <td>2285</td>\n",
       "      <td></td>\n",
       "      <td></td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>activity_time_in_zone</td>\n",
       "      <td>345</td>\n",
       "      <td></td>\n",
       "      <td></td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>daily_body_battery</td>\n",
       "      <td>365</td>\n",
       "      <td>2025-05-13</td>\n",
       "      <td>2026-05-12</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>5</th>\n",
       "      <td>daily_hrv</td>\n",
       "      <td>363</td>\n",
       "      <td>2025-05-13</td>\n",
       "      <td>2026-05-12</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>6</th>\n",
       "      <td>daily_intensity_minutes</td>\n",
       "      <td>365</td>\n",
       "      <td>2025-05-13</td>\n",
       "      <td>2026-05-12</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>7</th>\n",
       "      <td>daily_resting_hr</td>\n",
       "      <td>363</td>\n",
       "      <td>2025-05-13</td>\n",
       "      <td>2026-05-11</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>8</th>\n",
       "      <td>daily_sleep</td>\n",
       "      <td>1462</td>\n",
       "      <td>2022-04-08</td>\n",
       "      <td>2026-05-17</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>9</th>\n",
       "      <td>daily_steps</td>\n",
       "      <td>1497</td>\n",
       "      <td>2022-04-08</td>\n",
       "      <td>2026-05-17</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>10</th>\n",
       "      <td>daily_stress</td>\n",
       "      <td>365</td>\n",
       "      <td>2025-05-13</td>\n",
       "      <td>2026-05-12</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>11</th>\n",
       "      <td>manual_activities</td>\n",
       "      <td>0</td>\n",
       "      <td></td>\n",
       "      <td></td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>12</th>\n",
       "      <td>race_plan</td>\n",
       "      <td>0</td>\n",
       "      <td></td>\n",
       "      <td></td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>13</th>\n",
       "      <td>sqlite_sequence</td>\n",
       "      <td>0</td>\n",
       "      <td></td>\n",
       "      <td></td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>14</th>\n",
       "      <td>sync_state</td>\n",
       "      <td>3</td>\n",
       "      <td></td>\n",
       "      <td></td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "                      table  rows             from                   to\n",
       "0                activities   378  1658945478000.0  2026-05-10 10:43:58\n",
       "1        activity_fit_files   349                                      \n",
       "2           activity_splits  2285                                      \n",
       "3     activity_time_in_zone   345                                      \n",
       "4        daily_body_battery   365       2025-05-13           2026-05-12\n",
       "5                 daily_hrv   363       2025-05-13           2026-05-12\n",
       "6   daily_intensity_minutes   365       2025-05-13           2026-05-12\n",
       "7          daily_resting_hr   363       2025-05-13           2026-05-11\n",
       "8               daily_sleep  1462       2022-04-08           2026-05-17\n",
       "9               daily_steps  1497       2022-04-08           2026-05-17\n",
       "10             daily_stress   365       2025-05-13           2026-05-12\n",
       "11        manual_activities     0                                      \n",
       "12                race_plan     0                                      \n",
       "13          sqlite_sequence     0                                      \n",
       "14               sync_state     3                                      "
      ]
     },
     "execution_count": 2,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "summary = []\n",
    "for (table,) in conn.execute(\"SELECT name FROM sqlite_master WHERE type='table' ORDER BY name\"):\n",
    "    n = conn.execute(f'SELECT COUNT(*) FROM \"{table}\"').fetchone()[0]\n",
    "    date_col = 'start_time_local' if table == 'activities' else ('calendar_date' if table.startswith('daily_') else None)\n",
    "    if date_col and n:\n",
    "        mn, mx = conn.execute(f'SELECT MIN({date_col}), MAX({date_col}) FROM {table}').fetchone()\n",
    "    else:\n",
    "        mn = mx = ''\n",
    "    summary.append({'table': table, 'rows': n, 'from': mn, 'to': mx})\n",
    "pd.DataFrame(summary)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Activity types"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 3,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
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       "\n",
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       "    }\n",
       "\n",
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       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>count</th>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>activity_type</th>\n",
       "      <th></th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>running</th>\n",
       "      <td>335</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>trail_running</th>\n",
       "      <td>15</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>cycling</th>\n",
       "      <td>9</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>transition_v2</th>\n",
       "      <td>7</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>open_water_swimming</th>\n",
       "      <td>6</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>multi_sport</th>\n",
       "      <td>4</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>assistance</th>\n",
       "      <td>1</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>mountain_biking</th>\n",
       "      <td>1</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "                     count\n",
       "activity_type             \n",
       "running                335\n",
       "trail_running           15\n",
       "cycling                  9\n",
       "transition_v2            7\n",
       "open_water_swimming      6\n",
       "multi_sport              4\n",
       "assistance               1\n",
       "mountain_biking          1"
      ]
     },
     "execution_count": 3,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "activities = load_activities(conn)\n",
    "activities['activity_type'].value_counts().to_frame('count')"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Last 10 activities"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 4,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
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       "\n",
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       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>start_time_local</th>\n",
       "      <th>activity_type</th>\n",
       "      <th>activity_name</th>\n",
       "      <th>distance_km</th>\n",
       "      <th>duration_min</th>\n",
       "      <th>pace_min_per_km</th>\n",
       "      <th>avg_hr</th>\n",
       "      <th>training_load</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>NaT</td>\n",
       "      <td>running</td>\n",
       "      <td>Milford Running</td>\n",
       "      <td>12.94</td>\n",
       "      <td>105.89</td>\n",
       "      <td>8.09</td>\n",
       "      <td>163.00</td>\n",
       "      <td>101.28</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>NaT</td>\n",
       "      <td>transition_v2</td>\n",
       "      <td>Transition</td>\n",
       "      <td>24.03</td>\n",
       "      <td>75.39</td>\n",
       "      <td>3.01</td>\n",
       "      <td>116.00</td>\n",
       "      <td>90.98</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>NaT</td>\n",
       "      <td>open_water_swimming</td>\n",
       "      <td>Open Water Swimming</td>\n",
       "      <td>0.52</td>\n",
       "      <td>23.45</td>\n",
       "      <td>NaN</td>\n",
       "      <td>137.00</td>\n",
       "      <td>55.14</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>NaT</td>\n",
       "      <td>running</td>\n",
       "      <td>Running</td>\n",
       "      <td>4.88</td>\n",
       "      <td>25.64</td>\n",
       "      <td>5.17</td>\n",
       "      <td>169.00</td>\n",
       "      <td>134.45</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>NaT</td>\n",
       "      <td>transition_v2</td>\n",
       "      <td>Transition 2</td>\n",
       "      <td>3.89</td>\n",
       "      <td>715.77</td>\n",
       "      <td>NaN</td>\n",
       "      <td>107.00</td>\n",
       "      <td>10.10</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>5</th>\n",
       "      <td>NaT</td>\n",
       "      <td>cycling</td>\n",
       "      <td>Cycling</td>\n",
       "      <td>18.98</td>\n",
       "      <td>56.46</td>\n",
       "      <td>NaN</td>\n",
       "      <td>100.00</td>\n",
       "      <td>10.10</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>6</th>\n",
       "      <td>NaT</td>\n",
       "      <td>transition_v2</td>\n",
       "      <td>Transition 1</td>\n",
       "      <td>4.44</td>\n",
       "      <td>2117.33</td>\n",
       "      <td>NaN</td>\n",
       "      <td>87.00</td>\n",
       "      <td>8.48</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>7</th>\n",
       "      <td>NaT</td>\n",
       "      <td>open_water_swimming</td>\n",
       "      <td>Open Water Swimming</td>\n",
       "      <td>0.80</td>\n",
       "      <td>32.80</td>\n",
       "      <td>NaN</td>\n",
       "      <td>106.00</td>\n",
       "      <td>8.48</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>8</th>\n",
       "      <td>NaT</td>\n",
       "      <td>running</td>\n",
       "      <td>Running</td>\n",
       "      <td>5.09</td>\n",
       "      <td>25.35</td>\n",
       "      <td>4.97</td>\n",
       "      <td>162.00</td>\n",
       "      <td>173.71</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>9</th>\n",
       "      <td>NaT</td>\n",
       "      <td>transition_v2</td>\n",
       "      <td>Transition 2</td>\n",
       "      <td>0.77</td>\n",
       "      <td>137.95</td>\n",
       "      <td>NaN</td>\n",
       "      <td>118.00</td>\n",
       "      <td>5.90</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "  start_time_local        activity_type        activity_name  distance_km  \\\n",
       "0              NaT              running      Milford Running        12.94   \n",
       "1              NaT        transition_v2           Transition        24.03   \n",
       "2              NaT  open_water_swimming  Open Water Swimming         0.52   \n",
       "3              NaT              running              Running         4.88   \n",
       "4              NaT        transition_v2         Transition 2         3.89   \n",
       "5              NaT              cycling              Cycling        18.98   \n",
       "6              NaT        transition_v2         Transition 1         4.44   \n",
       "7              NaT  open_water_swimming  Open Water Swimming         0.80   \n",
       "8              NaT              running              Running         5.09   \n",
       "9              NaT        transition_v2         Transition 2         0.77   \n",
       "\n",
       "   duration_min  pace_min_per_km  avg_hr  training_load  \n",
       "0        105.89             8.09  163.00         101.28  \n",
       "1         75.39             3.01  116.00          90.98  \n",
       "2         23.45              NaN  137.00          55.14  \n",
       "3         25.64             5.17  169.00         134.45  \n",
       "4        715.77              NaN  107.00          10.10  \n",
       "5         56.46              NaN  100.00          10.10  \n",
       "6       2117.33              NaN   87.00           8.48  \n",
       "7         32.80              NaN  106.00           8.48  \n",
       "8         25.35             4.97  162.00         173.71  \n",
       "9        137.95              NaN  118.00           5.90  "
      ]
     },
     "execution_count": 4,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "cols = ['start_time_local', 'activity_type', 'activity_name', 'distance_km', 'duration_min', 'pace_min_per_km', 'avg_hr', 'training_load']\n",
    "activities[cols].tail(10).iloc[::-1].reset_index(drop=True)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "20e72ec0",
   "metadata": {},
   "outputs": [],
   "source": []
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Monthly running mileage, year-over-year"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 5,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 1100x400 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "runs = activities[activities['activity_type'].str.contains('running', case=False, na=False)].copy()\n",
    "monthly = (runs.assign(month_no=runs['start_time_local'].dt.month)\n",
    "                .groupby(['year', 'month_no'])['distance_km'].sum()\n",
    "                .unstack('year'))\n",
    "\n",
    "fig, ax = plt.subplots(figsize=(11, 4))\n",
    "monthly.plot(ax=ax, marker='o')\n",
    "ax.set_xticks(range(1, 13))\n",
    "ax.set_xticklabels(['Jan','Feb','Mar','Apr','May','Jun','Jul','Aug','Sep','Oct','Nov','Dec'])\n",
    "ax.set_ylabel('km')\n",
    "ax.set_xlabel('')\n",
    "ax.set_title('Monthly running km — year over year')\n",
    "ax.legend(title='Year')\n",
    "ax.grid(alpha=0.3)\n",
    "plt.tight_layout()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Wellness completeness (last 90 days)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 6,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
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       "\n",
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       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
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       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>% missing</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>total_steps</th>\n",
       "      <td>0.00</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>sleep_score</th>\n",
       "      <td>100.00</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>avg_stress</th>\n",
       "      <td>6.67</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>hrv_last_night</th>\n",
       "      <td>13.33</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>resting_hr</th>\n",
       "      <td>7.78</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>bb_charged</th>\n",
       "      <td>7.78</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "                % missing\n",
       "total_steps          0.00\n",
       "sleep_score        100.00\n",
       "avg_stress           6.67\n",
       "hrv_last_night      13.33\n",
       "resting_hr           7.78\n",
       "bb_charged           7.78"
      ]
     },
     "execution_count": 6,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "w = load_wellness(conn).tail(90)\n",
    "missing = w[['total_steps','sleep_score','avg_stress','hrv_last_night','resting_hr','bb_charged']].isna().mean().to_frame('% missing') * 100\n",
    "missing"
   ]
  }
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