95 lines
78 KiB
Text
95 lines
78 KiB
Text
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{
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"cells": [
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{
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"cell_type": "code",
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"execution_count": 34,
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"id": "067b9e86-c8f2-41c6-9f3c-3df26976962a",
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"metadata": {},
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"outputs": [
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{
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"name": "stdout",
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"output_type": "stream",
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"text": [
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"15:03:00 1:47:00\n"
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]
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},
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{
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"data": {
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"text/plain": [
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"<Axes: xlabel='date', ylabel='sleep_time'>"
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]
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},
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"execution_count": 34,
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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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"data": {
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"image/png": "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"text/plain": [
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"<Figure size 640x480 with 1 Axes>"
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]
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},
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"metadata": {},
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"output_type": "display_data"
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}
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],
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"source": [
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"PATH = \"watch-data/SLEEP/SLEEP_1679159561556.csv\"\n",
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"import pandas as pd\n",
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"import seaborn as sns\n",
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"import datetime\n",
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"fmtdelta = lambda td: str(datetime.timedelta(minutes = int(td)))\n",
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"\n",
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"df = pd.read_csv(PATH, escapechar='\\\\', parse_dates=['start', 'stop', 'date'])\n",
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"df['sleep_time'] = df['deepSleepTime'] + df['shallowSleepTime'] + df['REMTime']\n",
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"df = df[df.sleep_time > 0]\n",
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"print(fmtdelta(df.sleep_time.max()), fmtdelta(df.sleep_time.min()))\n",
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"sns.lineplot(df, x = 'date', y = 'sleep_time')"
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]
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},
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{
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"cell_type": "code",
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"execution_count": 31,
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"id": "918c73b9-1036-41a6-89cb-21a741ba7bea",
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"metadata": {},
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"outputs": [
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{
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"data": {
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"text/plain": [
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"('2:24:30.397921', '6:15:56.393443')"
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]
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},
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"execution_count": 31,
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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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"fmtdelta(df.sleep_time.std()), fmtdelta(df.sleep_time.mean())"
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]
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}
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],
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"metadata": {
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"kernelspec": {
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"display_name": "Python 3 (ipykernel)",
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"language": "python",
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"name": "python3"
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},
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"language_info": {
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"codemirror_mode": {
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"name": "ipython",
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"version": 3
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},
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"file_extension": ".py",
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"mimetype": "text/x-python",
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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": "3.10.10"
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}
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},
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"nbformat": 4,
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"nbformat_minor": 5
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}
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