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new monthly jupyter notebook with weight and training load graphs; notebook fixes
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lines changed

9 files changed

+295
-22
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‎Fit

Submodule Fit updated 1 file

‎Jupyter/activities_dashboard.ipynb

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@@ -362,7 +362,7 @@
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"name": "python",
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"nbconvert_exporter": "python",
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"pygments_lexer": "ipython3",
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"version": "3.11.4"
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"version": "3.11.7"
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}
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},
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"nbformat": 4,

‎Jupyter/course.ipynb

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@@ -83,7 +83,7 @@
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"name": "python",
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"nbconvert_exporter": "python",
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"pygments_lexer": "ipython3",
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"version": "3.11.4"
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"version": "3.11.7"
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},
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"orig_nbformat": 4
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},

‎Jupyter/daily.ipynb

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@@ -52,7 +52,7 @@
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"outputs": [],
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"source": [
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"\n",
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"__render_day(garmin_sum_db, graph, datetime.date.today() - datetime.timedelta(days = 1))\n"
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"__render_day(garmin_sum_db, graph, datetime.date.today() - datetime.timedelta(days = 1))"
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]
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},
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{
@@ -70,7 +70,7 @@
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"metadata": {},
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"outputs": [],
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"source": [
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"__render_day(garmin_sum_db, graph, datetime.date.today() - datetime.timedelta(days = 3))\n"
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"__render_day(garmin_sum_db, graph, datetime.date.today() - datetime.timedelta(days = 3))"
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]
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},
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{
@@ -79,7 +79,7 @@
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"metadata": {},
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"outputs": [],
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"source": [
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"__render_day(garmin_sum_db, graph, datetime.date.today() - datetime.timedelta(days = 4))\n"
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"__render_day(garmin_sum_db, graph, datetime.date.today() - datetime.timedelta(days = 4))"
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]
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},
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{
@@ -88,7 +88,7 @@
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"metadata": {},
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"outputs": [],
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"source": [
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"__render_day(garmin_sum_db, graph, datetime.date.today() - datetime.timedelta(days = 5))\n"
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"__render_day(garmin_sum_db, graph, datetime.date.today() - datetime.timedelta(days = 5))"
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]
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},
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{
@@ -97,7 +97,7 @@
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"metadata": {},
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"outputs": [],
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"source": [
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"__render_day(garmin_sum_db, graph, datetime.date.today() - datetime.timedelta(days = 6))\n"
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"__render_day(garmin_sum_db, graph, datetime.date.today() - datetime.timedelta(days = 6))"
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]
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},
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{
@@ -106,7 +106,7 @@
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"metadata": {},
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"outputs": [],
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"source": [
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"__render_day(garmin_sum_db, graph, datetime.date.today() - datetime.timedelta(days = 7))\n"
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"__render_day(garmin_sum_db, graph, datetime.date.today() - datetime.timedelta(days = 7))"
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]
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}
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],
@@ -128,7 +128,7 @@
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"name": "python",
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"nbconvert_exporter": "python",
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"pygments_lexer": "ipython3",
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"version": "3.11.4"
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"version": "3.11.7"
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},
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"orig_nbformat": 4
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},

‎Jupyter/daily_trends.ipynb

Lines changed: 174 additions & 6 deletions
Original file line numberDiff line numberDiff line change
@@ -2,7 +2,7 @@
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"cells": [
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{
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"cell_type": "code",
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"execution_count": null,
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"execution_count": 1,
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"id": "b8aada92",
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"metadata": {},
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"outputs": [],
@@ -27,7 +27,7 @@
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},
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{
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"cell_type": "code",
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"execution_count": null,
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"execution_count": 2,
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"id": "2d38e0f7-2ee5-40df-9373-b6485798d541",
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"metadata": {},
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"outputs": [],
@@ -38,7 +38,7 @@
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},
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{
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"cell_type": "code",
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"execution_count": null,
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"execution_count": 3,
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"id": "7353aa53-92a0-44d9-b476-e050295c4748",
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"metadata": {},
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"outputs": [],
@@ -59,10 +59,178 @@
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},
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{
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"cell_type": "code",
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"execution_count": null,
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"execution_count": 4,
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"id": "e41203c2-d435-4045-9c84-3559b4d3b367",
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"metadata": {},
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"outputs": [],
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"outputs": [
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{
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"data": {
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"text/html": [
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"<div>\n",
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"<style scoped>\n",
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" .dataframe tbody tr th:only-of-type {\n",
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" vertical-align: middle;\n",
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" }\n",
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"\n",
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" .dataframe tbody tr th {\n",
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" vertical-align: top;\n",
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" }\n",
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"\n",
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" .dataframe thead th {\n",
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" text-align: right;\n",
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" }\n",
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"</style>\n",
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"<table border=\"1\" class=\"dataframe\">\n",
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" <thead>\n",
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" <tr style=\"text-align: right;\">\n",
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" <th></th>\n",
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" <th>Date</th>\n",
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" <th>stress_avg</th>\n",
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" <th>bb_max</th>\n",
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" <th>bb_min</th>\n",
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" <th>rem_sleep_max</th>\n",
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" <th>deep_sleep</th>\n",
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" <th>sleep_avg</th>\n",
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" </tr>\n",
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" </thead>\n",
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" <tbody>\n",
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" <tr>\n",
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" <th>0</th>\n",
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" <td>2022-05-02</td>\n",
100+
" <td>18</td>\n",
101+
" <td>80</td>\n",
102+
" <td>23</td>\n",
103+
" <td>13.0</td>\n",
104+
" <td>106.0</td>\n",
105+
" <td>7.616667</td>\n",
106+
" </tr>\n",
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" <tr>\n",
108+
" <th>1</th>\n",
109+
" <td>2022-05-03</td>\n",
110+
" <td>36</td>\n",
111+
" <td>100</td>\n",
112+
" <td>18</td>\n",
113+
" <td>94.0</td>\n",
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" <td>24.0</td>\n",
115+
" <td>8.533333</td>\n",
116+
" </tr>\n",
117+
" <tr>\n",
118+
" <th>2</th>\n",
119+
" <td>2022-05-04</td>\n",
120+
" <td>31</td>\n",
121+
" <td>70</td>\n",
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" <td>21</td>\n",
123+
" <td>110.0</td>\n",
124+
" <td>0.0</td>\n",
125+
" <td>7.666667</td>\n",
126+
" </tr>\n",
127+
" <tr>\n",
128+
" <th>3</th>\n",
129+
" <td>2022-05-05</td>\n",
130+
" <td>32</td>\n",
131+
" <td>63</td>\n",
132+
" <td>18</td>\n",
133+
" <td>74.0</td>\n",
134+
" <td>31.0</td>\n",
135+
" <td>6.416667</td>\n",
136+
" </tr>\n",
137+
" <tr>\n",
138+
" <th>4</th>\n",
139+
" <td>2022-05-06</td>\n",
140+
" <td>36</td>\n",
141+
" <td>93</td>\n",
142+
" <td>14</td>\n",
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" <td>111.0</td>\n",
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" <td>14.0</td>\n",
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" <td>8.933333</td>\n",
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" </tr>\n",
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" <tr>\n",
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" <th>...</th>\n",
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" <td>...</td>\n",
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" <td>...</td>\n",
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" <td>...</td>\n",
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" <td>...</td>\n",
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" <td>...</td>\n",
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" <td>...</td>\n",
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" <td>...</td>\n",
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" </tr>\n",
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" <tr>\n",
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" <th>653</th>\n",
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" <td>2024-02-14</td>\n",
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" <td>47</td>\n",
161+
" <td>65</td>\n",
162+
" <td>5</td>\n",
163+
" <td>52.0</td>\n",
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" <td>None</td>\n",
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" <td>6.183333</td>\n",
166+
" </tr>\n",
167+
" <tr>\n",
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" <th>654</th>\n",
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" <td>2024-02-15</td>\n",
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" <td>41</td>\n",
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" <td>20</td>\n",
172+
" <td>5</td>\n",
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" <td>0.0</td>\n",
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" <td>None</td>\n",
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" <td>4.3</td>\n",
176+
" </tr>\n",
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" <tr>\n",
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" <th>655</th>\n",
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" <td>2024-02-16</td>\n",
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" <td>30</td>\n",
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" <td>52</td>\n",
182+
" <td>21</td>\n",
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" <td>10.0</td>\n",
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" <td>None</td>\n",
185+
" <td>7.266667</td>\n",
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" </tr>\n",
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" <tr>\n",
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" <th>656</th>\n",
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" <td>2024-02-17</td>\n",
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" <td>39</td>\n",
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" <td>71</td>\n",
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" <td>12</td>\n",
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" <td>15.0</td>\n",
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" <td>None</td>\n",
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" <td>6.333333</td>\n",
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" </tr>\n",
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" <tr>\n",
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" <th>657</th>\n",
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" <td>2024-02-18</td>\n",
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" <td>45</td>\n",
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" <td>34</td>\n",
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" <td>5</td>\n",
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" <td>0.0</td>\n",
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" <td>None</td>\n",
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" <td>7.15</td>\n",
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" </tr>\n",
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" </tbody>\n",
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"</table>\n",
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"<p>658 rows × 7 columns</p>\n",
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"</div>"
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],
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"text/plain": [
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" Date stress_avg bb_max bb_min rem_sleep_max deep_sleep sleep_avg\n",
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"0 2022-05-02 18 80 23 13.0 106.0 7.616667\n",
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"1 2022-05-03 36 100 18 94.0 24.0 8.533333\n",
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"2 2022-05-04 31 70 21 110.0 0.0 7.666667\n",
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"3 2022-05-05 32 63 18 74.0 31.0 6.416667\n",
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"4 2022-05-06 36 93 14 111.0 14.0 8.933333\n",
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".. ... ... ... ... ... ... ...\n",
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"653 2024-02-14 47 65 5 52.0 None 6.183333\n",
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"654 2024-02-15 41 20 5 0.0 None 4.3\n",
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"655 2024-02-16 30 52 21 10.0 None 7.266667\n",
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"656 2024-02-17 39 71 12 15.0 None 6.333333\n",
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"657 2024-02-18 45 34 5 0.0 None 7.15\n",
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"\n",
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"[658 rows x 7 columns]"
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]
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},
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"execution_count": 4,
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"metadata": {},
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"output_type": "execute_result"
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}
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],
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"source": [
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"stress_avg = [entry.stress_avg for entry in data]\n",
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"bb_max = [entry.bb_max for entry in data]\n",
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"name": "python",
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"nbconvert_exporter": "python",
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"pygments_lexer": "ipython3",
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"version": "3.11.4"
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"version": "3.11.7"
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}
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},
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"nbformat": 4,

‎Jupyter/garmin.ipynb

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"name": "python",
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"nbconvert_exporter": "python",
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"pygments_lexer": "ipython3",
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"version": "3.11.4"
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"version": "3.11.7"
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},
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"orig_nbformat": 4
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},

‎Jupyter/graphs.py

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import matplotlib.dates as mdates
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1717
from garmindb import ConfigManager
18-
from garmindb.garmindb import MonitoringDb, Monitoring, MonitoringHeartRate
18+
from garmindb.garmindb import MonitoringDb, Monitoring, MonitoringHeartRate, ActivitiesDb
1919
from garmindb.summarydb import DaysSummary, WeeksSummary, MonthsSummary, SummaryDb
2020

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config = {
23-
'size' : [16.0, 12.0],
23+
'size' : [8.0, 6.0],
2424
'steps' : {'period' : 'weeks', 'days' : 730},
2525
'hr' : {'period' : 'weeks', 'days' : 730},
2626
'itime' : {'period' : 'weeks', 'days' : 730},
@@ -88,7 +88,21 @@ def __remove_discontinuities(cls, data):
8888
return data
8989

9090
@classmethod
91-
def __graph_multiple_single_axes(cls, time, data_list, stat_name, ylabel, save, geometry=111):
91+
def _graph_scatter(cls, time, data, stat_name, ylabel, save=False, geometry=111):
92+
title = f'{stat_name} Over Time'
93+
figure = plt.figure(figsize=config.get('size'))
94+
color = Colors.from_integer(0).name
95+
axes = figure.add_subplot(geometry, frame_on=True)
96+
axes.scatter(time, data, color=color)
97+
axes.grid()
98+
axes.set_title(title)
99+
axes.set_xlabel('Time')
100+
axes.set_ylabel(ylabel)
101+
if save:
102+
figure.savefig(stat_name + ".png")
103+
104+
@classmethod
105+
def _graph_multiple_single_axes(cls, time, data_list, stat_name, ylabel, save=False, geometry=111):
92106
title = f'{stat_name} Over Time'
93107
figure = plt.figure(figsize=config.get('size'))
94108
for index, data in enumerate(data_list):
@@ -182,8 +196,9 @@ def _graph_itime(self, time, data, period, geometry=111):
182196
yrange_list, self.save, geometry)
183197

184198
def _graph_weight(self, time, data, period, geometry=111):
199+
"""Generate a graph weight"""
185200
weight = [entry.weight_avg for entry in data]
186-
self.__graph_multiple_single_axes(time, [weight], 'Weight', 'weight', self.save, geometry)
201+
self._graph_multiple_single_axes(time, [weight], 'Weight', 'weight', self.save, geometry)
187202

188203
def graph_activity(self, activity, period=None, days=None, geometry=111):
189204
"""Generate a graph for the given activity with points every period spanning days."""

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