{ "cells": [ { "cell_type": "markdown", "metadata": {}, "source": [ "# Analysis of the incidence of chickenpox" ] }, { "cell_type": "code", "execution_count": 1, "metadata": {}, "outputs": [], "source": [ "%matplotlib inline\n", "import matplotlib.pyplot as plt\n", "import pandas as pd\n", "import isoweek" ] }, { "cell_type": "code", "execution_count": 2, "metadata": {}, "outputs": [], "source": [ "data_url = \"https://www.sentiweb.fr/datasets/all/inc-7-PAY-ds2.csv\"" ] }, { "cell_type": "code", "execution_count": 3, "metadata": {}, "outputs": [], "source": [ "data_file = \"chicken-pox.csv\"\n", "\n", "import os\n", "import urllib.request\n", "if not os.path.exists(data_file):\n", " urllib.request.urlretrieve(data_url, data_file)" ] }, { "cell_type": "code", "execution_count": 4, "metadata": {}, "outputs": [ { "data": { "text/html": [ "
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weekgeo_inseeindicatorincinc100inc_upinc_lowinc100_upinc100_low
0201601FR7145572216108130062520
1201602FR7116401813031102492016
2201603FR7162872517937146372822
3201604FR7147852316341132292520
4201605FR7190072920783172313226
5201606FR7189242920716171323226
6201607FR7215453323470196203630
7201608FR7193383021170175063227
8201609FR7142892215867127112420
9201610FR7181402819881163993125
10201611FR7152452316841136492621
11201612FR7183072820062165523125
12201613FR7168122618509151152823
13201614FR7208373222746189283529
14201615FR7198703021766179743328
15201616FR7184892820334166443126
16201617FR7163072518060145542822
17201618FR7145012216117128852520
18201619FR7198113021683179393328
19201620FR7144792216085128732520
20201621FR7189552920809171013226
21201622FR7180372819823162513025
22201623FR7186792920486168723126
23201624FR7185402820365167153126
24201625FR7162452517946145442822
25201626FR7210403223009190713529
26201627FR7143622216031126932519
27201628FR7155592417369137492721
28201629FR7144192216203126352519
29201630FR710675161221691341914
..............................
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492202524FR74234666121856103
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493 rows × 9 columns

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" ], "text/plain": [ " week geo_insee indicator inc inc100 inc_up inc_low inc100_up \\\n", "0 201601 FR 7 14557 22 16108 13006 25 \n", "1 201602 FR 7 11640 18 13031 10249 20 \n", "2 201603 FR 7 16287 25 17937 14637 28 \n", "3 201604 FR 7 14785 23 16341 13229 25 \n", "4 201605 FR 7 19007 29 20783 17231 32 \n", "5 201606 FR 7 18924 29 20716 17132 32 \n", "6 201607 FR 7 21545 33 23470 19620 36 \n", "7 201608 FR 7 19338 30 21170 17506 32 \n", "8 201609 FR 7 14289 22 15867 12711 24 \n", "9 201610 FR 7 18140 28 19881 16399 31 \n", "10 201611 FR 7 15245 23 16841 13649 26 \n", "11 201612 FR 7 18307 28 20062 16552 31 \n", "12 201613 FR 7 16812 26 18509 15115 28 \n", "13 201614 FR 7 20837 32 22746 18928 35 \n", "14 201615 FR 7 19870 30 21766 17974 33 \n", "15 201616 FR 7 18489 28 20334 16644 31 \n", "16 201617 FR 7 16307 25 18060 14554 28 \n", "17 201618 FR 7 14501 22 16117 12885 25 \n", "18 201619 FR 7 19811 30 21683 17939 33 \n", "19 201620 FR 7 14479 22 16085 12873 25 \n", "20 201621 FR 7 18955 29 20809 17101 32 \n", "21 201622 FR 7 18037 28 19823 16251 30 \n", "22 201623 FR 7 18679 29 20486 16872 31 \n", "23 201624 FR 7 18540 28 20365 16715 31 \n", "24 201625 FR 7 16245 25 17946 14544 28 \n", "25 201626 FR 7 21040 32 23009 19071 35 \n", "26 201627 FR 7 14362 22 16031 12693 25 \n", "27 201628 FR 7 15559 24 17369 13749 27 \n", "28 201629 FR 7 14419 22 16203 12635 25 \n", "29 201630 FR 7 10675 16 12216 9134 19 \n", ".. ... ... ... ... ... ... ... ... \n", "463 202447 FR 7 4296 6 5090 3502 8 \n", "464 202448 FR 7 3736 6 4469 3003 7 \n", "465 202449 FR 7 4853 7 5704 4002 9 \n", "466 202450 FR 7 5496 8 6407 4585 10 \n", "467 202451 FR 7 5005 8 5885 4125 9 \n", "468 202452 FR 7 3929 6 4817 3041 7 \n", "469 202501 FR 7 6059 9 9667 2451 14 \n", "470 202502 FR 7 5966 9 9175 2757 14 \n", "471 202503 FR 7 2462 4 3763 1161 6 \n", "472 202504 FR 7 6895 10 9324 4466 14 \n", "473 202505 FR 7 2087 3 3118 1056 5 \n", "474 202506 FR 7 3455 5 4952 1958 7 \n", "475 202507 FR 7 4502 7 6622 2382 10 \n", "476 202508 FR 7 2835 4 4384 1286 7 \n", "477 202509 FR 7 3381 5 5294 1468 8 \n", "478 202510 FR 7 2921 4 4421 1421 7 \n", "479 202511 FR 7 5878 9 9009 2747 13 \n", "480 202512 FR 7 3855 6 5715 1995 9 \n", "481 202513 FR 7 5964 9 8320 3608 12 \n", "482 202514 FR 7 4984 7 7110 2858 11 \n", "483 202515 FR 7 5557 8 7852 3262 12 \n", "484 202516 FR 7 6151 9 9109 3193 14 \n", "485 202517 FR 7 6246 9 9068 3424 14 \n", "486 202518 FR 7 5003 7 7288 2718 11 \n", "487 202519 FR 7 5084 8 8171 1997 12 \n", "488 202520 FR 7 3083 5 4631 1535 7 \n", "489 202521 FR 7 4693 7 6733 2653 10 \n", "490 202522 FR 7 6837 10 9734 3940 15 \n", "491 202523 FR 7 4858 7 7093 2623 11 \n", "492 202524 FR 7 4234 6 6612 1856 10 \n", "\n", " inc100_low \n", "0 20 \n", "1 16 \n", "2 22 \n", "3 20 \n", "4 26 \n", "5 26 \n", "6 30 \n", "7 27 \n", "8 20 \n", "9 25 \n", "10 21 \n", "11 25 \n", "12 23 \n", "13 29 \n", "14 28 \n", "15 26 \n", "16 22 \n", "17 20 \n", "18 28 \n", "19 20 \n", "20 26 \n", "21 25 \n", "22 26 \n", "23 26 \n", "24 22 \n", "25 29 \n", "26 19 \n", "27 21 \n", "28 19 \n", "29 14 \n", ".. ... \n", "463 5 \n", "464 5 \n", "465 6 \n", "466 7 \n", "467 6 \n", "468 5 \n", "469 4 \n", "470 4 \n", "471 2 \n", "472 7 \n", "473 2 \n", "474 3 \n", "475 4 \n", "476 2 \n", "477 2 \n", "478 2 \n", "479 4 \n", "480 3 \n", "481 5 \n", "482 4 \n", "483 5 \n", "484 5 \n", "485 5 \n", "486 4 \n", "487 3 \n", "488 2 \n", "489 4 \n", "490 6 \n", "491 4 \n", "492 3 \n", "\n", "[493 rows x 9 columns]" ] }, "execution_count": 4, "metadata": {}, "output_type": "execute_result" } ], "source": [ "raw_data = pd.read_csv(data_file, skiprows=1)\n", "raw_data" ] }, { "cell_type": "code", "execution_count": 5, "metadata": {}, "outputs": [ { "data": { "text/html": [ "
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weekgeo_inseeindicatorincinc100inc_upinc_lowinc100_upinc100_low
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" ], "text/plain": [ "Empty DataFrame\n", "Columns: [week, geo_insee, indicator, inc, inc100, inc_up, inc_low, inc100_up, inc100_low]\n", "Index: []" ] }, "execution_count": 5, "metadata": {}, "output_type": "execute_result" } ], "source": [ "raw_data[raw_data.isnull().any(axis=1)]" ] }, { "cell_type": "code", "execution_count": 6, "metadata": {}, "outputs": [ { "data": { "text/html": [ "
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weekgeo_inseeindicatorincinc100inc_upinc_lowinc100_upinc100_low
0201601FR7145572216108130062520
1201602FR7116401813031102492016
2201603FR7162872517937146372822
3201604FR7147852316341132292520
4201605FR7190072920783172313226
5201606FR7189242920716171323226
6201607FR7215453323470196203630
7201608FR7193383021170175063227
8201609FR7142892215867127112420
9201610FR7181402819881163993125
10201611FR7152452316841136492621
11201612FR7183072820062165523125
12201613FR7168122618509151152823
13201614FR7208373222746189283529
14201615FR7198703021766179743328
15201616FR7184892820334166443126
16201617FR7163072518060145542822
17201618FR7145012216117128852520
18201619FR7198113021683179393328
19201620FR7144792216085128732520
20201621FR7189552920809171013226
21201622FR7180372819823162513025
22201623FR7186792920486168723126
23201624FR7185402820365167153126
24201625FR7162452517946145442822
25201626FR7210403223009190713529
26201627FR7143622216031126932519
27201628FR7155592417369137492721
28201629FR7144192216203126352519
29201630FR710675161221691341914
..............................
463202447FR7429665090350285
464202448FR7373664469300375
465202449FR7485375704400296
466202450FR75496864074585107
467202451FR7500585885412596
468202452FR7392964817304175
469202501FR76059996672451144
470202502FR75966991752757144
471202503FR7246243763116162
472202504FR768951093244466147
473202505FR7208733118105652
474202506FR7345554952195873
475202507FR74502766222382104
476202508FR7283544384128672
477202509FR7338155294146882
478202510FR7292144421142172
479202511FR75878990092747134
480202512FR7385565715199593
481202513FR75964983203608125
482202514FR74984771102858114
483202515FR75557878523262125
484202516FR76151991093193145
485202517FR76246990683424145
486202518FR75003772882718114
487202519FR75084881711997123
488202520FR7308354631153572
489202521FR74693767332653104
490202522FR768371097343940156
491202523FR74858770932623114
492202524FR74234666121856103
\n", "

493 rows × 9 columns

\n", "
" ], "text/plain": [ " week geo_insee indicator inc inc100 inc_up inc_low inc100_up \\\n", "0 201601 FR 7 14557 22 16108 13006 25 \n", "1 201602 FR 7 11640 18 13031 10249 20 \n", "2 201603 FR 7 16287 25 17937 14637 28 \n", "3 201604 FR 7 14785 23 16341 13229 25 \n", "4 201605 FR 7 19007 29 20783 17231 32 \n", "5 201606 FR 7 18924 29 20716 17132 32 \n", "6 201607 FR 7 21545 33 23470 19620 36 \n", "7 201608 FR 7 19338 30 21170 17506 32 \n", "8 201609 FR 7 14289 22 15867 12711 24 \n", "9 201610 FR 7 18140 28 19881 16399 31 \n", "10 201611 FR 7 15245 23 16841 13649 26 \n", "11 201612 FR 7 18307 28 20062 16552 31 \n", "12 201613 FR 7 16812 26 18509 15115 28 \n", "13 201614 FR 7 20837 32 22746 18928 35 \n", "14 201615 FR 7 19870 30 21766 17974 33 \n", "15 201616 FR 7 18489 28 20334 16644 31 \n", "16 201617 FR 7 16307 25 18060 14554 28 \n", "17 201618 FR 7 14501 22 16117 12885 25 \n", "18 201619 FR 7 19811 30 21683 17939 33 \n", "19 201620 FR 7 14479 22 16085 12873 25 \n", "20 201621 FR 7 18955 29 20809 17101 32 \n", "21 201622 FR 7 18037 28 19823 16251 30 \n", "22 201623 FR 7 18679 29 20486 16872 31 \n", "23 201624 FR 7 18540 28 20365 16715 31 \n", "24 201625 FR 7 16245 25 17946 14544 28 \n", "25 201626 FR 7 21040 32 23009 19071 35 \n", "26 201627 FR 7 14362 22 16031 12693 25 \n", "27 201628 FR 7 15559 24 17369 13749 27 \n", "28 201629 FR 7 14419 22 16203 12635 25 \n", "29 201630 FR 7 10675 16 12216 9134 19 \n", ".. ... ... ... ... ... ... ... ... \n", "463 202447 FR 7 4296 6 5090 3502 8 \n", "464 202448 FR 7 3736 6 4469 3003 7 \n", "465 202449 FR 7 4853 7 5704 4002 9 \n", "466 202450 FR 7 5496 8 6407 4585 10 \n", "467 202451 FR 7 5005 8 5885 4125 9 \n", "468 202452 FR 7 3929 6 4817 3041 7 \n", "469 202501 FR 7 6059 9 9667 2451 14 \n", "470 202502 FR 7 5966 9 9175 2757 14 \n", "471 202503 FR 7 2462 4 3763 1161 6 \n", "472 202504 FR 7 6895 10 9324 4466 14 \n", "473 202505 FR 7 2087 3 3118 1056 5 \n", "474 202506 FR 7 3455 5 4952 1958 7 \n", "475 202507 FR 7 4502 7 6622 2382 10 \n", "476 202508 FR 7 2835 4 4384 1286 7 \n", "477 202509 FR 7 3381 5 5294 1468 8 \n", "478 202510 FR 7 2921 4 4421 1421 7 \n", "479 202511 FR 7 5878 9 9009 2747 13 \n", "480 202512 FR 7 3855 6 5715 1995 9 \n", "481 202513 FR 7 5964 9 8320 3608 12 \n", "482 202514 FR 7 4984 7 7110 2858 11 \n", "483 202515 FR 7 5557 8 7852 3262 12 \n", "484 202516 FR 7 6151 9 9109 3193 14 \n", "485 202517 FR 7 6246 9 9068 3424 14 \n", "486 202518 FR 7 5003 7 7288 2718 11 \n", "487 202519 FR 7 5084 8 8171 1997 12 \n", "488 202520 FR 7 3083 5 4631 1535 7 \n", "489 202521 FR 7 4693 7 6733 2653 10 \n", "490 202522 FR 7 6837 10 9734 3940 15 \n", "491 202523 FR 7 4858 7 7093 2623 11 \n", "492 202524 FR 7 4234 6 6612 1856 10 \n", "\n", " inc100_low \n", "0 20 \n", "1 16 \n", "2 22 \n", "3 20 \n", "4 26 \n", "5 26 \n", "6 30 \n", "7 27 \n", "8 20 \n", "9 25 \n", "10 21 \n", "11 25 \n", "12 23 \n", "13 29 \n", "14 28 \n", "15 26 \n", "16 22 \n", "17 20 \n", "18 28 \n", "19 20 \n", "20 26 \n", "21 25 \n", "22 26 \n", "23 26 \n", "24 22 \n", "25 29 \n", "26 19 \n", "27 21 \n", "28 19 \n", "29 14 \n", ".. ... \n", "463 5 \n", "464 5 \n", "465 6 \n", "466 7 \n", "467 6 \n", "468 5 \n", "469 4 \n", "470 4 \n", "471 2 \n", "472 7 \n", "473 2 \n", "474 3 \n", "475 4 \n", "476 2 \n", "477 2 \n", "478 2 \n", "479 4 \n", "480 3 \n", "481 5 \n", "482 4 \n", "483 5 \n", "484 5 \n", "485 5 \n", "486 4 \n", "487 3 \n", "488 2 \n", "489 4 \n", "490 6 \n", "491 4 \n", "492 3 \n", "\n", "[493 rows x 9 columns]" ] }, "execution_count": 6, "metadata": {}, "output_type": "execute_result" } ], "source": [ "data = raw_data.dropna().copy()\n", "data" ] }, { "cell_type": "code", "execution_count": 7, "metadata": {}, "outputs": [], "source": [ "def convert_week(year_and_week_int):\n", " year_and_week_str = str(year_and_week_int)\n", " year = int(year_and_week_str[:4])\n", " week = int(year_and_week_str[4:])\n", " w = isoweek.Week(year, week)\n", " return pd.Period(w.day(0), 'W')\n", "\n", "data['period'] = [convert_week(yw) for yw in data['week']]" ] }, { "cell_type": "code", "execution_count": 8, "metadata": {}, "outputs": [], "source": [ "sorted_data = data.set_index('period').sort_index()" ] }, { "cell_type": "code", "execution_count": 9, "metadata": {}, "outputs": [], "source": [ "periods = sorted_data.index\n", "for p1, p2 in zip(periods[:-1], periods[1:]):\n", " delta = p2.to_timestamp() - p1.end_time\n", " if delta > pd.Timedelta('1s'):\n", " print(p1, p2)" ] }, { "cell_type": "code", "execution_count": 10, "metadata": {}, "outputs": [ { "data": { "text/plain": [ "" ] }, "execution_count": 10, "metadata": {}, "output_type": "execute_result" }, { "data": { "image/png": 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\n", 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\n", 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" ] }, "metadata": { "needs_background": "light" }, "output_type": "display_data" } ], "source": [ "sorted_data['inc'][-200:].plot()" ] }, { "cell_type": "code", "execution_count": 12, "metadata": {}, "outputs": [], "source": [ "first_september_week = [pd.Period(pd.Timestamp(y, 9, 1), 'W')\n", " for y in range(2016,\n", " sorted_data.index[-1].year)]" ] }, { "cell_type": "code", "execution_count": 13, "metadata": {}, "outputs": [], "source": [ "year = []\n", "yearly_incidence = []\n", "for week1, week2 in zip(first_september_week[:-1],\n", " first_september_week[1:]):\n", " one_year = sorted_data['inc'][week1:week2-1]\n", " assert abs(len(one_year)-52) < 2\n", " yearly_incidence.append(one_year.sum())\n", " year.append(week2.year)\n", "yearly_incidence = pd.Series(data=yearly_incidence, index=year)" ] }, { "cell_type": "code", "execution_count": 14, "metadata": {}, "outputs": [ { "data": { "text/plain": [ "" ] }, "execution_count": 14, "metadata": {}, "output_type": "execute_result" }, { "data": { "image/png": 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\n", 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