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428 lines
95 KiB
428 lines
95 KiB
{
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"cells": [
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{
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"cell_type": "code",
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"execution_count": 1,
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"metadata": {},
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"outputs": [],
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"source": [
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"import os\n",
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"import matplotlib.pyplot as plt\n",
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"import pandas as pd"
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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": 2,
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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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" logId dateOfSleep startTime endTime \\\n",
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"0 22919218280 2019-07-01 2019-06-30T21:42:30.000 2019-07-01T06:53:00.000 \n",
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"1 22907959315 2019-06-30 2019-06-29T22:50:30.000 2019-06-30T08:22:30.000 \n",
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"2 22896495948 2019-06-29 2019-06-28T23:00:30.000 2019-06-29T07:34:30.000 \n",
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"3 22885271917 2019-06-28 2019-06-27T23:25:30.000 2019-06-28T07:01:00.000 \n",
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"4 22873469544 2019-06-27 2019-06-27T00:22:30.000 2019-06-27T06:37:30.000 \n",
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"5 22859901781 2019-06-26 2019-06-25T23:10:30.000 2019-06-26T06:41:30.000 \n",
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"6 22835159082 2019-06-24 2019-06-23T22:23:30.000 2019-06-24T06:34:30.000 \n",
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"7 22835159081 2019-06-23 2019-06-22T23:07:00.000 2019-06-23T06:42:00.000 \n",
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"8 22835159080 2019-06-22 2019-06-22T01:42:00.000 2019-06-22T07:36:30.000 \n",
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"9 22799331499 2019-06-21 2019-06-20T22:55:00.000 2019-06-21T06:35:30.000 \n",
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"10 22786383973 2019-06-20 2019-06-19T22:24:00.000 2019-06-20T06:22:00.000 \n",
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"11 22773778389 2019-06-19 2019-06-18T22:36:00.000 2019-06-19T06:18:00.000 \n",
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"12 22762586407 2019-06-18 2019-06-17T22:31:00.000 2019-06-18T06:32:00.000 \n",
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"13 22747505160 2019-06-17 2019-06-16T21:56:30.000 2019-06-17T06:30:30.000 \n",
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"14 22738149556 2019-06-16 2019-06-15T23:13:00.000 2019-06-16T07:12:30.000 \n",
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"15 22723339639 2019-06-15 2019-06-14T23:09:00.000 2019-06-15T07:47:00.000 \n",
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"16 22710872408 2019-06-14 2019-06-13T22:16:00.000 2019-06-14T06:12:30.000 \n",
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"17 22698921476 2019-06-13 2019-06-12T22:12:30.000 2019-06-13T06:01:30.000 \n",
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"18 22681265384 2019-06-12 2019-06-11T22:05:30.000 2019-06-12T06:30:30.000 \n",
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"19 22674775396 2019-06-11 2019-06-10T22:07:30.000 2019-06-11T06:32:30.000 \n",
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"20 22661124288 2019-06-10 2019-06-09T21:56:00.000 2019-06-10T06:22:00.000 \n",
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"21 22648970133 2019-06-09 2019-06-08T22:46:00.000 2019-06-09T07:30:30.000 \n",
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"22 22638820465 2019-06-08 2019-06-07T22:14:30.000 2019-06-08T06:50:00.000 \n",
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"23 22626446172 2019-06-07 2019-06-06T22:33:30.000 2019-06-07T07:04:30.000 \n",
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"24 22615666021 2019-06-06 2019-06-05T22:31:00.000 2019-06-06T06:39:00.000 \n",
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"25 22602351745 2019-06-05 2019-06-04T23:03:00.000 2019-06-05T06:39:00.000 \n",
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"26 22590503668 2019-06-04 2019-06-03T22:19:00.000 2019-06-04T06:20:00.000 \n",
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"27 22576235910 2019-06-03 2019-06-02T22:33:30.000 2019-06-03T06:16:30.000 \n",
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"28 22562754522 2019-06-02 2019-06-01T22:49:00.000 2019-06-02T07:00:30.000 \n",
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"29 22553516585 2019-06-01 2019-06-01T08:50:30.000 2019-06-01T10:09:30.000 \n",
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"30 22550042569 2019-06-01 2019-05-31T23:06:00.000 2019-06-01T04:57:30.000 \n",
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"\n",
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" duration minutesToFallAsleep minutesAsleep minutesAwake \\\n",
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"0 33000000 0 481 69 \n",
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"1 34320000 0 492 80 \n",
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"2 30840000 0 432 82 \n",
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"3 27300000 0 387 68 \n",
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"4 22500000 0 319 56 \n",
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"5 27060000 0 387 64 \n",
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"6 29460000 0 415 76 \n",
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"7 27300000 0 400 55 \n",
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"8 21240000 0 304 50 \n",
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"9 27600000 0 380 80 \n",
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"10 28680000 0 422 56 \n",
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"11 27720000 0 395 67 \n",
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"12 28860000 0 408 73 \n",
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"13 30840000 0 452 62 \n",
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"14 28740000 0 406 73 \n",
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"15 31080000 0 451 67 \n",
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"16 28560000 0 413 63 \n",
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"17 28140000 0 386 83 \n",
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"18 30300000 0 441 64 \n",
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"19 30300000 0 446 59 \n",
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"20 30360000 0 454 52 \n",
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"21 31440000 0 445 79 \n",
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"22 30900000 0 449 66 \n",
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"23 30660000 0 432 79 \n",
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"24 29280000 0 416 72 \n",
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"25 27360000 0 377 79 \n",
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"26 28860000 0 435 46 \n",
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"27 27780000 0 400 63 \n",
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"28 29460000 0 434 57 \n",
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"29 4740000 0 76 3 \n",
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"30 21060000 0 299 52 \n",
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"\n",
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" minutesAfterWakeup timeInBed efficiency type infoCode \\\n",
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"0 8 550 89 stages 0 \n",
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"1 0 572 90 stages 0 \n",
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"2 0 514 94 stages 0 \n",
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"3 1 455 84 stages 0 \n",
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"4 0 375 92 stages 0 \n",
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"5 0 451 86 stages 0 \n",
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"6 5 491 92 stages 0 \n",
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"7 0 455 93 stages 0 \n",
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"8 0 354 93 stages 0 \n",
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"9 0 460 91 stages 0 \n",
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"10 0 478 95 stages 0 \n",
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"11 0 462 87 stages 0 \n",
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"12 14 481 87 stages 0 \n",
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"13 1 514 89 stages 0 \n",
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"14 1 479 86 stages 0 \n",
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"15 0 518 89 stages 0 \n",
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"16 0 476 88 stages 0 \n",
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"17 0 469 93 stages 0 \n",
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"18 1 505 88 stages 0 \n",
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"19 3 505 92 stages 0 \n",
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"20 0 506 93 stages 0 \n",
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"21 0 524 94 stages 0 \n",
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"22 0 515 92 stages 0 \n",
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"23 0 511 84 stages 0 \n",
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"24 0 488 89 stages 0 \n",
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"25 0 456 86 stages 0 \n",
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"26 1 481 84 stages 0 \n",
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"27 2 463 91 stages 0 \n",
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"28 1 491 89 stages 0 \n",
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"29 0 79 96 classic 2 \n",
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"30 0 351 85 stages 0 \n",
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"\n",
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" levels mainSleep \n",
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"0 {'summary': {'deep': {'count': 5, 'minutes': 9... True \n",
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"1 {'summary': {'deep': {'count': 4, 'minutes': 1... True \n",
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"2 {'summary': {'deep': {'count': 4, 'minutes': 1... True \n",
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"3 {'summary': {'deep': {'count': 3, 'minutes': 9... True \n",
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"4 {'summary': {'deep': {'count': 5, 'minutes': 7... True \n",
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"5 {'summary': {'deep': {'count': 3, 'minutes': 8... True \n",
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"6 {'summary': {'deep': {'count': 2, 'minutes': 6... True \n",
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"7 {'summary': {'deep': {'count': 3, 'minutes': 8... True \n",
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"8 {'summary': {'deep': {'count': 2, 'minutes': 6... True \n",
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"9 {'summary': {'deep': {'count': 2, 'minutes': 7... True \n",
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"10 {'summary': {'deep': {'count': 4, 'minutes': 9... True \n",
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"11 {'summary': {'deep': {'count': 2, 'minutes': 7... True \n",
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"12 {'summary': {'deep': {'count': 2, 'minutes': 6... True \n",
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"13 {'summary': {'deep': {'count': 4, 'minutes': 9... True \n",
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"14 {'summary': {'deep': {'count': 3, 'minutes': 8... True \n",
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"15 {'summary': {'deep': {'count': 4, 'minutes': 1... True \n",
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"16 {'summary': {'deep': {'count': 2, 'minutes': 6... True \n",
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"17 {'summary': {'deep': {'count': 4, 'minutes': 8... True \n",
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"18 {'summary': {'deep': {'count': 6, 'minutes': 9... True \n",
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"19 {'summary': {'deep': {'count': 3, 'minutes': 1... True \n",
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"20 {'summary': {'deep': {'count': 4, 'minutes': 1... True \n",
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"21 {'summary': {'deep': {'count': 5, 'minutes': 9... True \n",
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"22 {'summary': {'deep': {'count': 5, 'minutes': 1... True \n",
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"23 {'summary': {'deep': {'count': 4, 'minutes': 7... True \n",
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"24 {'summary': {'deep': {'count': 4, 'minutes': 6... True \n",
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"25 {'summary': {'deep': {'count': 3, 'minutes': 8... True \n",
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"26 {'summary': {'deep': {'count': 6, 'minutes': 1... True \n",
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"27 {'summary': {'deep': {'count': 5, 'minutes': 9... True \n",
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"28 {'summary': {'deep': {'count': 6, 'minutes': 8... True \n",
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"29 {'summary': {'restless': {'count': 2, 'minutes... False \n",
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"30 {'summary': {'deep': {'count': 4, 'minutes': 8... True \n"
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]
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}
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],
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"source": [
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"sleep_df = pd.read_json(\"data/sleep-2019-06-01.json\", convert_dates=True)\n",
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"print(sleep_df)"
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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": 3,
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"metadata": {},
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"outputs": [
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{
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"data": {
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"image/png": 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\n",
|
|
"text/plain": [
|
|
"<Figure size 432x288 with 1 Axes>"
|
|
]
|
|
},
|
|
"metadata": {
|
|
"needs_background": "light"
|
|
},
|
|
"output_type": "display_data"
|
|
}
|
|
],
|
|
"source": [
|
|
"ax = plt.gca()\n",
|
|
"ax.set_title('Sleep Distribution for June')\n",
|
|
"ax.boxplot(sleep_df['minutesAsleep']/60, vert=False,manage_ticks=False, notch=True)\n",
|
|
"plt.xlabel(\"Hours Asleep\")\n",
|
|
"ax.set_yticks([])\n",
|
|
"plt.show()"
|
|
]
|
|
},
|
|
{
|
|
"cell_type": "code",
|
|
"execution_count": 4,
|
|
"metadata": {},
|
|
"outputs": [
|
|
{
|
|
"data": {
|
|
"text/plain": [
|
|
"<matplotlib.axes._subplots.AxesSubplot at 0x7f61966bb050>"
|
|
]
|
|
},
|
|
"execution_count": 4,
|
|
"metadata": {},
|
|
"output_type": "execute_result"
|
|
},
|
|
{
|
|
"data": {
|
|
"image/png": "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\n",
|
|
"text/plain": [
|
|
"<Figure size 432x288 with 1 Axes>"
|
|
]
|
|
},
|
|
"metadata": {
|
|
"needs_background": "light"
|
|
},
|
|
"output_type": "display_data"
|
|
}
|
|
],
|
|
"source": [
|
|
"startTimes = pd.to_datetime(sleep_df['startTime'])\n",
|
|
"sleep = pd.to_datetime(sleep_df['startTime']).dt.hour -12 + pd.to_datetime(sleep_df['startTime']).dt.minute/60\n",
|
|
"sleep.hist()"
|
|
]
|
|
},
|
|
{
|
|
"cell_type": "code",
|
|
"execution_count": 5,
|
|
"metadata": {},
|
|
"outputs": [
|
|
{
|
|
"data": {
|
|
"image/png": "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\n",
|
|
"text/plain": [
|
|
"<Figure size 432x288 with 1 Axes>"
|
|
]
|
|
},
|
|
"metadata": {
|
|
"needs_background": "light"
|
|
},
|
|
"output_type": "display_data"
|
|
}
|
|
],
|
|
"source": [
|
|
"ax = plt.gca()\n",
|
|
"ax.set_title('Fall asleep times')\n",
|
|
"ax.boxplot(sleep, vert=False,manage_ticks=False, notch=True)\n",
|
|
"plt.xlabel(\"Time went to Bed\")\n",
|
|
"plt.xlim(8, 12)\n",
|
|
"ax.set_yticks([])\n",
|
|
"plt.show()"
|
|
]
|
|
},
|
|
{
|
|
"cell_type": "code",
|
|
"execution_count": 6,
|
|
"metadata": {},
|
|
"outputs": [],
|
|
"source": [
|
|
"def getAllSleepData():\n",
|
|
" files = os.listdir(\"data\")\n",
|
|
" dfs = []\n",
|
|
" for file in files: # this can take 15 seconds\n",
|
|
" if \"sleep-\" in file: # finds the steps files\n",
|
|
" dfs.append(pd.read_json(\"data/\" + file, convert_dates=['startTime', 'endTime']))\n",
|
|
" return pd.concat(dfs)"
|
|
]
|
|
},
|
|
{
|
|
"cell_type": "code",
|
|
"execution_count": 7,
|
|
"metadata": {},
|
|
"outputs": [],
|
|
"source": [
|
|
"sleep_df = getAllSleepData()"
|
|
]
|
|
},
|
|
{
|
|
"cell_type": "code",
|
|
"execution_count": 8,
|
|
"metadata": {},
|
|
"outputs": [],
|
|
"source": [
|
|
"sleep_df['start'] = sleep_df['startTime'].dt.hour - 12 + sleep_df['startTime'].dt.minute/60\n",
|
|
"sleep_df['end'] = sleep_df['endTime'].dt.hour + sleep_df['endTime'].dt.minute/60"
|
|
]
|
|
},
|
|
{
|
|
"cell_type": "code",
|
|
"execution_count": 9,
|
|
"metadata": {},
|
|
"outputs": [
|
|
{
|
|
"data": {
|
|
"image/png": "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\n",
|
|
"text/plain": [
|
|
"<Figure size 432x288 with 1 Axes>"
|
|
]
|
|
},
|
|
"metadata": {
|
|
"needs_background": "light"
|
|
},
|
|
"output_type": "display_data"
|
|
}
|
|
],
|
|
"source": [
|
|
"ax = plt.gca()\n",
|
|
"ax.set_title('Wakeup Time')\n",
|
|
"ax.boxplot(sleep_df['end'], vert=False,manage_ticks=False, notch=True)\n",
|
|
"plt.xlabel(\"Wakeup Time\")\n",
|
|
"ax.set_yticks([])\n",
|
|
"plt.xlim(4, 10)\n",
|
|
"plt.show()"
|
|
]
|
|
},
|
|
{
|
|
"cell_type": "code",
|
|
"execution_count": 10,
|
|
"metadata": {},
|
|
"outputs": [
|
|
{
|
|
"data": {
|
|
"image/png": "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\n",
|
|
"text/plain": [
|
|
"<Figure size 432x288 with 1 Axes>"
|
|
]
|
|
},
|
|
"metadata": {
|
|
"needs_background": "light"
|
|
},
|
|
"output_type": "display_data"
|
|
}
|
|
],
|
|
"source": [
|
|
"ax = plt.gca()\n",
|
|
"ax.set_title('Time Went to Sleep')\n",
|
|
"ax.boxplot(sleep_df['start'], vert=False,manage_ticks=False, notch=True)\n",
|
|
"plt.xlabel(\"Time went to sleep\")\n",
|
|
"ax.set_yticks([])\n",
|
|
"plt.xlim(8, 12)\n",
|
|
"plt.show()"
|
|
]
|
|
},
|
|
{
|
|
"cell_type": "code",
|
|
"execution_count": 11,
|
|
"metadata": {},
|
|
"outputs": [],
|
|
"source": [
|
|
"sleep_df['weekday'] = sleep_df['startTime'].dt.weekday"
|
|
]
|
|
},
|
|
{
|
|
"cell_type": "code",
|
|
"execution_count": 12,
|
|
"metadata": {},
|
|
"outputs": [
|
|
{
|
|
"data": {
|
|
"image/png": 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\n",
|
|
"text/plain": [
|
|
"<Figure size 432x288 with 1 Axes>"
|
|
]
|
|
},
|
|
"metadata": {
|
|
"needs_background": "light"
|
|
},
|
|
"output_type": "display_data"
|
|
}
|
|
],
|
|
"source": [
|
|
"ax = plt.gca()\n",
|
|
"ax.set_title('Steps Distribution for July\\n')\n",
|
|
"sleep_df.boxplot(column=['start'], by='weekday',ax=ax, notch=True)\n",
|
|
"plt.xlabel(\"Week Day\")\n",
|
|
"plt.ylabel(\"Sleep Start\")\n",
|
|
"plt.ylim(8, 12)\n",
|
|
"plt.show()"
|
|
]
|
|
},
|
|
{
|
|
"cell_type": "code",
|
|
"execution_count": 13,
|
|
"metadata": {},
|
|
"outputs": [
|
|
{
|
|
"data": {
|
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"image/png": 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\n",
|
|
"text/plain": [
|
|
"<Figure size 432x288 with 1 Axes>"
|
|
]
|
|
},
|
|
"metadata": {
|
|
"needs_background": "light"
|
|
},
|
|
"output_type": "display_data"
|
|
}
|
|
],
|
|
"source": [
|
|
"ax = plt.gca()\n",
|
|
"ax.set_title('Wake Up Time')\n",
|
|
"sleep_df.boxplot(column=['end'], by='weekday',ax=ax, notch=True)\n",
|
|
"plt.xlabel(\"Week Day\")\n",
|
|
"plt.ylabel(\"Sleep Start\")\n",
|
|
"plt.ylim(5, 10)\n",
|
|
"plt.show()"
|
|
]
|
|
}
|
|
],
|
|
"metadata": {
|
|
"kernelspec": {
|
|
"display_name": "Python 3",
|
|
"language": "python",
|
|
"name": "python3"
|
|
},
|
|
"language_info": {
|
|
"codemirror_mode": {
|
|
"name": "ipython",
|
|
"version": 3
|
|
},
|
|
"file_extension": ".py",
|
|
"mimetype": "text/x-python",
|
|
"name": "python",
|
|
"nbconvert_exporter": "python",
|
|
"pygments_lexer": "ipython3",
|
|
"version": "3.7.6"
|
|
}
|
|
},
|
|
"nbformat": 4,
|
|
"nbformat_minor": 4
|
|
}
|