{ "cells": [ { "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 = \"http://www.sentiweb.fr/datasets/incidence-PAY-7.csv\"\n", "data_file = \"incidence-PAY-7.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": 3, "metadata": {}, "outputs": [ { "data": { "text/html": [ "
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weekindicatorincinc_lowinc_upinc100inc100_lowinc100_upgeo_inseegeo_name
0202536711211182124213FRFrance
1202535712361772295204FRFrance
220253471438482828204FRFrance
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42025327238404809408FRFrance
5202531757030130829020FRFrance
62025307710235901061411616FRFrance
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1020252675872328584599513FRFrance
1120252575953369882089612FRFrance
1220252474580255866027410FRFrance
1320252374911266371597410FRFrance
14202522768373940973410614FRFrance
1520252174693265367337410FRFrance
162025207308315354631537FRFrance
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1820251875003271872887410FRFrance
1920251776246342490689513FRFrance
2020251676151319391099513FRFrance
2120251575557326278528511FRFrance
2220251474984285871107410FRFrance
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242025127385519955715639FRFrance
2520251175878274790099414FRFrance
262025107292114214421426FRFrance
272025097338114685294528FRFrance
282025087283512864384426FRFrance
2920250774502238266227410FRFrance
.................................
17841991267176081130423912312042FRFrance
17851991257161691070021638281838FRFrance
17861991247161711007122271281739FRFrance
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1788199122715452995320951271737FRFrance
1789199121714903897520831261636FRFrance
17901991207190531274225364342345FRFrance
17911991197167391124622232291939FRFrance
17921991187213851388228888382551FRFrance
1793199117713462887718047241632FRFrance
17941991167148571006819646261834FRFrance
1795199115713975978118169251832FRFrance
1796199114712265768416846221430FRFrance
179719911379567604113093171123FRFrance
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17991991117155741118419964271935FRFrance
18001991107166431137221914292038FRFrance
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18061991047791345631126314820FRFrance
18071991037153871048420290271836FRFrance
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18111990517190801380724353342543FRFrance
1812199050711079666015498201228FRFrance
18131990497114302610205FRFrance
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1814 rows × 10 columns

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" ], "text/plain": [ " week indicator inc inc_low inc_up inc100 inc100_low \\\n", "0 202536 7 1121 118 2124 2 1 \n", "1 202535 7 1236 177 2295 2 0 \n", "2 202534 7 1438 48 2828 2 0 \n", "3 202533 7 3579 692 6466 5 1 \n", "4 202532 7 2384 0 4809 4 0 \n", "5 202531 7 5703 0 13082 9 0 \n", "6 202530 7 7102 3590 10614 11 6 \n", "7 202529 7 6385 3384 9386 10 6 \n", "8 202528 7 5584 3123 8045 8 4 \n", "9 202527 7 5667 2850 8484 8 4 \n", "10 202526 7 5872 3285 8459 9 5 \n", "11 202525 7 5953 3698 8208 9 6 \n", "12 202524 7 4580 2558 6602 7 4 \n", "13 202523 7 4911 2663 7159 7 4 \n", "14 202522 7 6837 3940 9734 10 6 \n", "15 202521 7 4693 2653 6733 7 4 \n", "16 202520 7 3083 1535 4631 5 3 \n", "17 202519 7 5084 1997 8171 8 3 \n", "18 202518 7 5003 2718 7288 7 4 \n", "19 202517 7 6246 3424 9068 9 5 \n", "20 202516 7 6151 3193 9109 9 5 \n", "21 202515 7 5557 3262 7852 8 5 \n", "22 202514 7 4984 2858 7110 7 4 \n", "23 202513 7 5964 3608 8320 9 5 \n", "24 202512 7 3855 1995 5715 6 3 \n", "25 202511 7 5878 2747 9009 9 4 \n", "26 202510 7 2921 1421 4421 4 2 \n", "27 202509 7 3381 1468 5294 5 2 \n", "28 202508 7 2835 1286 4384 4 2 \n", "29 202507 7 4502 2382 6622 7 4 \n", "... ... ... ... ... ... ... ... \n", "1784 199126 7 17608 11304 23912 31 20 \n", "1785 199125 7 16169 10700 21638 28 18 \n", "1786 199124 7 16171 10071 22271 28 17 \n", "1787 199123 7 11947 7671 16223 21 13 \n", "1788 199122 7 15452 9953 20951 27 17 \n", "1789 199121 7 14903 8975 20831 26 16 \n", "1790 199120 7 19053 12742 25364 34 23 \n", "1791 199119 7 16739 11246 22232 29 19 \n", "1792 199118 7 21385 13882 28888 38 25 \n", "1793 199117 7 13462 8877 18047 24 16 \n", "1794 199116 7 14857 10068 19646 26 18 \n", "1795 199115 7 13975 9781 18169 25 18 \n", "1796 199114 7 12265 7684 16846 22 14 \n", "1797 199113 7 9567 6041 13093 17 11 \n", "1798 199112 7 10864 7331 14397 19 13 \n", "1799 199111 7 15574 11184 19964 27 19 \n", "1800 199110 7 16643 11372 21914 29 20 \n", "1801 199109 7 13741 8780 18702 24 15 \n", "1802 199108 7 13289 8813 17765 23 15 \n", "1803 199107 7 12337 8077 16597 22 15 \n", "1804 199106 7 10877 7013 14741 19 12 \n", "1805 199105 7 10442 6544 14340 18 11 \n", "1806 199104 7 7913 4563 11263 14 8 \n", "1807 199103 7 15387 10484 20290 27 18 \n", "1808 199102 7 16277 11046 21508 29 20 \n", "1809 199101 7 15565 10271 20859 27 18 \n", "1810 199052 7 19375 13295 25455 34 23 \n", "1811 199051 7 19080 13807 24353 34 25 \n", "1812 199050 7 11079 6660 15498 20 12 \n", "1813 199049 7 1143 0 2610 2 0 \n", "\n", " inc100_up geo_insee geo_name \n", "0 3 FR France \n", "1 4 FR France \n", "2 4 FR France \n", "3 9 FR France \n", "4 8 FR France \n", "5 20 FR France \n", "6 16 FR France \n", "7 14 FR France \n", "8 12 FR France \n", "9 12 FR France \n", "10 13 FR France \n", "11 12 FR France \n", "12 10 FR France \n", "13 10 FR France \n", "14 14 FR France \n", "15 10 FR France \n", "16 7 FR France \n", "17 13 FR France \n", "18 10 FR France \n", "19 13 FR France \n", "20 13 FR France \n", "21 11 FR France \n", "22 10 FR France \n", "23 13 FR France \n", "24 9 FR France \n", "25 14 FR France \n", "26 6 FR France \n", "27 8 FR France \n", "28 6 FR France \n", "29 10 FR France \n", "... ... ... ... \n", "1784 42 FR France \n", "1785 38 FR France \n", "1786 39 FR France \n", "1787 29 FR France \n", "1788 37 FR France \n", "1789 36 FR France \n", "1790 45 FR France \n", "1791 39 FR France \n", "1792 51 FR France \n", "1793 32 FR France \n", "1794 34 FR France \n", "1795 32 FR France \n", "1796 30 FR France \n", "1797 23 FR France \n", "1798 25 FR France \n", "1799 35 FR France \n", "1800 38 FR France \n", "1801 33 FR France \n", "1802 31 FR France \n", "1803 29 FR France \n", "1804 26 FR France \n", "1805 25 FR France \n", "1806 20 FR France \n", "1807 36 FR France \n", "1808 38 FR France \n", "1809 36 FR France \n", "1810 45 FR France \n", "1811 43 FR France \n", "1812 28 FR France \n", "1813 5 FR France \n", "\n", "[1814 rows x 10 columns]" ] }, "execution_count": 3, "metadata": {}, "output_type": "execute_result" } ], "source": [ "raw_data = pd.read_csv(data_file, skiprows=1)\n", "raw_data" ] }, { "cell_type": "code", "execution_count": 4, "metadata": {}, "outputs": [ { "data": { "text/html": [ "
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weekindicatorincinc_lowinc_upinc100inc100_lowinc100_upgeo_inseegeo_name
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" ], "text/plain": [ "Empty DataFrame\n", "Columns: [week, indicator, inc, inc_low, inc_up, inc100, inc100_low, inc100_up, geo_insee, geo_name]\n", "Index: []" ] }, "execution_count": 4, "metadata": {}, "output_type": "execute_result" } ], "source": [ "raw_data[raw_data.isnull().any(axis=1)]" ] }, { "cell_type": "code", "execution_count": 5, "metadata": {}, "outputs": [ { "data": { "text/html": [ "
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weekindicatorincinc_lowinc_upinc100inc100_lowinc100_upgeo_inseegeo_name
0202536711211182124213FRFrance
1202535712361772295204FRFrance
220253471438482828204FRFrance
3202533735796926466519FRFrance
42025327238404809408FRFrance
5202531757030130829020FRFrance
62025307710235901061411616FRFrance
7202529763853384938610614FRFrance
820252875584312380458412FRFrance
920252775667285084848412FRFrance
1020252675872328584599513FRFrance
1120252575953369882089612FRFrance
1220252474580255866027410FRFrance
1320252374911266371597410FRFrance
14202522768373940973410614FRFrance
1520252174693265367337410FRFrance
162025207308315354631537FRFrance
1720251975084199781718313FRFrance
1820251875003271872887410FRFrance
1920251776246342490689513FRFrance
2020251676151319391099513FRFrance
2120251575557326278528511FRFrance
2220251474984285871107410FRFrance
2320251375964360883209513FRFrance
242025127385519955715639FRFrance
2520251175878274790099414FRFrance
262025107292114214421426FRFrance
272025097338114685294528FRFrance
282025087283512864384426FRFrance
2920250774502238266227410FRFrance
.................................
17841991267176081130423912312042FRFrance
17851991257161691070021638281838FRFrance
17861991247161711007122271281739FRFrance
1787199123711947767116223211329FRFrance
1788199122715452995320951271737FRFrance
1789199121714903897520831261636FRFrance
17901991207190531274225364342345FRFrance
17911991197167391124622232291939FRFrance
17921991187213851388228888382551FRFrance
1793199117713462887718047241632FRFrance
17941991167148571006819646261834FRFrance
1795199115713975978118169251832FRFrance
1796199114712265768416846221430FRFrance
179719911379567604113093171123FRFrance
1798199112710864733114397191325FRFrance
17991991117155741118419964271935FRFrance
18001991107166431137221914292038FRFrance
1801199109713741878018702241533FRFrance
1802199108713289881317765231531FRFrance
1803199107712337807716597221529FRFrance
1804199106710877701314741191226FRFrance
1805199105710442654414340181125FRFrance
18061991047791345631126314820FRFrance
18071991037153871048420290271836FRFrance
18081991027162771104621508292038FRFrance
18091991017155651027120859271836FRFrance
18101990527193751329525455342345FRFrance
18111990517190801380724353342543FRFrance
1812199050711079666015498201228FRFrance
18131990497114302610205FRFrance
\n", "

1814 rows × 10 columns

\n", "
" ], "text/plain": [ " week indicator inc inc_low inc_up inc100 inc100_low \\\n", "0 202536 7 1121 118 2124 2 1 \n", "1 202535 7 1236 177 2295 2 0 \n", "2 202534 7 1438 48 2828 2 0 \n", "3 202533 7 3579 692 6466 5 1 \n", "4 202532 7 2384 0 4809 4 0 \n", "5 202531 7 5703 0 13082 9 0 \n", "6 202530 7 7102 3590 10614 11 6 \n", "7 202529 7 6385 3384 9386 10 6 \n", "8 202528 7 5584 3123 8045 8 4 \n", "9 202527 7 5667 2850 8484 8 4 \n", "10 202526 7 5872 3285 8459 9 5 \n", "11 202525 7 5953 3698 8208 9 6 \n", "12 202524 7 4580 2558 6602 7 4 \n", "13 202523 7 4911 2663 7159 7 4 \n", "14 202522 7 6837 3940 9734 10 6 \n", "15 202521 7 4693 2653 6733 7 4 \n", "16 202520 7 3083 1535 4631 5 3 \n", "17 202519 7 5084 1997 8171 8 3 \n", "18 202518 7 5003 2718 7288 7 4 \n", "19 202517 7 6246 3424 9068 9 5 \n", "20 202516 7 6151 3193 9109 9 5 \n", "21 202515 7 5557 3262 7852 8 5 \n", "22 202514 7 4984 2858 7110 7 4 \n", "23 202513 7 5964 3608 8320 9 5 \n", "24 202512 7 3855 1995 5715 6 3 \n", "25 202511 7 5878 2747 9009 9 4 \n", "26 202510 7 2921 1421 4421 4 2 \n", "27 202509 7 3381 1468 5294 5 2 \n", "28 202508 7 2835 1286 4384 4 2 \n", "29 202507 7 4502 2382 6622 7 4 \n", "... ... ... ... ... ... ... ... \n", "1784 199126 7 17608 11304 23912 31 20 \n", "1785 199125 7 16169 10700 21638 28 18 \n", "1786 199124 7 16171 10071 22271 28 17 \n", "1787 199123 7 11947 7671 16223 21 13 \n", "1788 199122 7 15452 9953 20951 27 17 \n", "1789 199121 7 14903 8975 20831 26 16 \n", "1790 199120 7 19053 12742 25364 34 23 \n", "1791 199119 7 16739 11246 22232 29 19 \n", "1792 199118 7 21385 13882 28888 38 25 \n", "1793 199117 7 13462 8877 18047 24 16 \n", "1794 199116 7 14857 10068 19646 26 18 \n", "1795 199115 7 13975 9781 18169 25 18 \n", "1796 199114 7 12265 7684 16846 22 14 \n", "1797 199113 7 9567 6041 13093 17 11 \n", "1798 199112 7 10864 7331 14397 19 13 \n", "1799 199111 7 15574 11184 19964 27 19 \n", "1800 199110 7 16643 11372 21914 29 20 \n", "1801 199109 7 13741 8780 18702 24 15 \n", "1802 199108 7 13289 8813 17765 23 15 \n", "1803 199107 7 12337 8077 16597 22 15 \n", "1804 199106 7 10877 7013 14741 19 12 \n", "1805 199105 7 10442 6544 14340 18 11 \n", "1806 199104 7 7913 4563 11263 14 8 \n", "1807 199103 7 15387 10484 20290 27 18 \n", "1808 199102 7 16277 11046 21508 29 20 \n", "1809 199101 7 15565 10271 20859 27 18 \n", "1810 199052 7 19375 13295 25455 34 23 \n", "1811 199051 7 19080 13807 24353 34 25 \n", "1812 199050 7 11079 6660 15498 20 12 \n", "1813 199049 7 1143 0 2610 2 0 \n", "\n", " inc100_up geo_insee geo_name \n", "0 3 FR France \n", "1 4 FR France \n", "2 4 FR France \n", "3 9 FR France \n", "4 8 FR France \n", "5 20 FR France \n", "6 16 FR France \n", "7 14 FR France \n", "8 12 FR France \n", "9 12 FR France \n", "10 13 FR France \n", "11 12 FR France \n", "12 10 FR France \n", "13 10 FR France \n", "14 14 FR France \n", "15 10 FR France \n", "16 7 FR France \n", "17 13 FR France \n", "18 10 FR France \n", "19 13 FR France \n", "20 13 FR France \n", "21 11 FR France \n", "22 10 FR France \n", "23 13 FR France \n", "24 9 FR France \n", "25 14 FR France \n", "26 6 FR France \n", "27 8 FR France \n", "28 6 FR France \n", "29 10 FR France \n", "... ... ... ... \n", "1784 42 FR France \n", "1785 38 FR France \n", "1786 39 FR France \n", "1787 29 FR France \n", "1788 37 FR France \n", "1789 36 FR France \n", "1790 45 FR France \n", "1791 39 FR France \n", "1792 51 FR France \n", "1793 32 FR France \n", "1794 34 FR France \n", "1795 32 FR France \n", "1796 30 FR France \n", "1797 23 FR France \n", "1798 25 FR France \n", "1799 35 FR France \n", "1800 38 FR France \n", "1801 33 FR France \n", "1802 31 FR France \n", "1803 29 FR France \n", "1804 26 FR France \n", "1805 25 FR France \n", "1806 20 FR France \n", "1807 36 FR France \n", "1808 38 FR France \n", "1809 36 FR France \n", "1810 45 FR France \n", "1811 43 FR France \n", "1812 28 FR France \n", "1813 5 FR France \n", "\n", "[1814 rows x 10 columns]" ] }, "execution_count": 5, "metadata": {}, "output_type": "execute_result" } ], "source": [ "data = raw_data.dropna().copy()\n", "data" ] }, { "cell_type": "code", "execution_count": 6, "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": 7, "metadata": {}, "outputs": [], "source": [ "sorted_data = data.set_index('period').sort_index()" ] }, { "cell_type": "code", "execution_count": 8, "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": 9, "metadata": {}, "outputs": [ { "data": { "text/plain": [ "" ] }, "execution_count": 9, "metadata": {}, "output_type": "execute_result" }, { "data": { "image/png": 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\n", 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1z+uPtBDsgLRLzKYl8rgDpwD5yQrMcmj3cMuBUxwuDnUmmdHx9rkwdp6HSwnIDgPyytleTDxjiVOIfMtBsi0HLg6c4nBxqDNvnp2DZlDsGgqe1+vkBKQty4HXOnAKkT/rg1sOnErg4lBnjk/FAADb+hcfbwCcdQ7ccuCUpnjMwYVwgosDpzBcHOrMudkkXCKxu7EuFlEguHZTD3asCXLLgVMSdtNgjQLJsRyiaQ2GI5OJw2Fwcagz5+aS6G/3QKigRUY5Hv7ty3Hz9n47rZVbDpxCsESFvoBZQyMJViqrxwVKgShvocEpABeHOnNuNoGBDk9VX1Nx8SZqnOKkrBGyg0HzcydLWbcSwKukOYXh4lBnRudSGAhWWRwsy4G7lTiFYAN92OeOWQ5cHDil4OJQRzKagYloCiurbDm4ueXAKQGzHJjF6ow5AFwcOIXh4lBHxsMpUAoMVtutxGIO3HLgFIClsrLxs17ZvJlo4+LAKQFv2V1HRuYSAFB9txJvn8EpwImpGAJuyXY33rC1F1/8zctw0aCZRs0sB95Cg1MIbjnUkXOz5ijPagekbbcStxyWLQdHI/hfT7ydk5b6Ow/txT//6IjtbvTKIm7e3g9CeECaUx4uDnVkdM6cG93fUVlb7krhqaycF45M4uFXhjFuzSbXDYozMwmEYhnbcmDTAxleWYQkEC4OnIJwcagj5+YS6AkodtFatZBFAYRwy2E5k8yY7/25OdM6nYqmoRsUkaSKlGpAFoV5tTWEEN5Cg1MULg515NxcsuouJcA8yRVJ4JbDMiZp3Rgw1+Vo2PweTWlIqbodl8qHiwOnGFwc6siZmUTVg9EMv+LCVCxdk9fmND+JPMthPGy6l6IpFWnNKGqttnlcfBocpyBlxYEQ8hVCyCQh5G3H2icJIecIIW9aX+93PPcJQshxQsgRQshNjvUdhJD91nMPECsqRghRCCHfstZ3E0KGqvsnNgcTkRTOziRx6aqO8hsvgivXdeKnR0Mt3yfn4GgEp0LxRh9G08HiCkwcRueylkNa1e3mjPlwy4FTjEosh68CuLnA+mcopZdYXz8AAELINgB3ALjA2ufzhBB2y/IFAPcA2Gh9sde8G8AspXQDgM8A+PQi/5am5hcnpwEAV67rqsnrv3trH0KxNN4amavJ6zcLf/Ltt/A3Tx5o9GE0HXbMwXIrjTHLIa0hkdGLDpbq8ssIRbnFyZlPWXGglP4UwEyFr3crgG9SStOU0lMAjgO4nBDSD6CNUvoKpZQCeBjAbY59HrIePwbgRmZVtBK/ODmNgFvC1v62mrz+dZt7IAoEzx2arMnrNwtj4SSOT0QbfRhNR8KyHEbz3EoAMB1P2xlt+fS1uTEVS7e8xclZOOcTc/g4IWSf5XZik2sGAJx1bDNirQ1Yj/PXc/ahlGoAwgAK3l4TQu4hhOwlhOydmpo6j0OvP784OYMr1nZCrEI31kJ0eGXsXBPEs4cmavL6zUBa0zGXUDEaTiGe5p1EnaQcMQdKqR2QBoBQLFPUcugLKFB1itlEpi7HyVk6LFYcvgBgPYBLAIwB+BdrvdCVj5ZYL7XP/EVKH6SU7qSU7uzp6VnYETeQ8XAKp0LxmrmUGNdv6cXh8Shm4q15ok853B887pBLQjXFMpExBXRsLgW/YjZAmIqmi8YcetvMmpuJCHctcXJZlDhQSicopTql1ADwnwAut54aAbDKsekggFFrfbDAes4+hBAJQDsqd2MtCfacNv+cWotDj98cIBRt0XYIkw5xOGFN1OOYJDM6ZMt1dGYmgcloCpv6/ACAWFqbVwDH6GszPzMT0VTB5wHzf/3I7uEqHzGn2VmUOFgxBMYHAbBMpicB3GFlIK2FGXjeQykdAxAlhFxpxRM+AuAJxz53WY8/BOB5Ky7RMkxaVauru7w1/T1Ki48LnYw4xYFbDk6SGR3rus3Gem+cmYVBgU19Afv5YnUOvdYAoKkSlsOje8/irx5/m7eEX2aUbbxHCPkGgOsAdBNCRgD8DYDrCCGXwHT/nAbwMQCglB4ghDwK4CAADcB9lFL2iboXZuaTB8DT1hcAfBnA1wghx2FaDHdU4w9rJiJJFYQAfrm2fQ7Z3WFabU1xmLLubgOKxC2HPJKqjsvWBHF4PIq9w7MAcsWhmOXQyyyHSHHLIZI0XVbT8YxdxDkZTSGguOCRq1vtz2keyl6tKKV3Flj+cont7wdwf4H1vQC2F1hPAbi93HEsZSIpDW1uV1VGg5Yiazm05h3eZDQNgQCXrQnixCQXBydJVcfKDg+8sogfHzCTEjavcFoOhS/iiiSiw+sq6VZiXVunomlbHD70hVfwSxf3409v2lKtP4HTZPCW3XmMhZOQRQFdlv++GkSSKto8tf9XsyrYVItaDpORNLr8Cjb2+vGLk9MwDFpzwV0KGAZFSjXgcYn4pw9djB8fHEdK1XGxo+CyWCorYM6WnizhVmIV1KweglKKc3NJjId5ELuV4eLgQDcobv/iK9jcF8CXf2vXgvY9O5NAX5vbDgo6CSdVtLld1TrMomS7s7aq5ZBCb0DB+l4/0pqBc3NJrOqsbRxnKcAmvXllEbdc1I9bLsqGBGVJQEYziqayAqZraaJEIVw0ZbqVWHuWpKpDNyiSKk8nbmV4byUHzx+exMhsErtPzUAvUBQ0l8jg6n94Dm+fC+esp1Qd7/nMi/jWq2cKvm4kVR9xaPVxoVOxNHoDClZbgjAymyyzx/KA9VUq5P9vc5v3f8VSWQGzEG6yVMzB4VYCsmIRT7fmTQjHhIuDg//6hZmuF0trODweAWDehX/ppZNIqTpGZpMYDadweDy3QjeSMtsinwolCr5uJKnVya3U4pZDJI3egBsdXj6kxglrnVHIOghYNyUlLYeAgqlo8SppFpAOxZg4mP/3RIZbDq0MFweL4ek4Xjw6hdt3mOUYe0+bGR/fe2sMf/f9Q/jFyWn7opvMS+ljJ+dkkaBevSwHe1xoC8YcdIMiFEujt01Bh1cGAISTrVnst1DY59FbwHIIWJZDyZhDmxuaQTFjVUn/8O2xnFqZfMshksoW3HFaFy4OFntOmYVqH3vXeqxoc9vpgN/bZ9bqJTO6nSKazLtjYub1ZBG/bSSp2iMZa4kite640Ol4GgY173I7rP/lXKK6lsMTb57Da8NLr/6S3Zx4CloOzK1U3HLoc6SzTkRS+L3/eh1PvTUGwHSZZiw3ZdZy4OKwHOABaYtpq+VEf7sbO4eCePXUDMIJFS8dCwEwg36KZmpp/knBAnNTBcRB0w3EMzra6iIOrVsEx7JpegIKvLIIl0gwV2W30v/54RHsHApix5rOqr5urWGWQ+GYA3MrFb8PZC00JiNpuERzO2YtMCEAnDEH8zne36q14ZaDRSiahsclwqdI2DXUifFICp986gA0yw+bUg3bXZPMEwfbcnAE9Yan4/jiiydsE5wFBmtJK4sDuzD1BNzWeEu56pZDWjOg6s3zvzMMiq+8fKpsO5RKLIdSo2m7fKabbjqeQcy64Ces70wkuv0yQjHzBooJRv55wGktuDhYhGJpdPnNk+R9F67Ahl4/Hn/jHDqtEyel6nb7gHzLgf0cz+j23dSTb47iH58+bFfy1sNykEQBkkBaMiDNmgmyC1mH11X1mENG05HRmqdzy8GxCD71vYN4/nDpNuylLIdABZYD2yaWUu3Pb9z6TLMah3XdfsTSGpIZPWs5ZDS0WKcbjgMuDhbT8Qy6rcK33oAbP/7Da/GV39qJ//jwDgCm5cDuyIu5lYBs3IFl0hweM7Oe6hGQBkzroRUD0uwOlsVuOjyuqlsOGd1ApoksBzbVrVw7FPZ59LrmW6d2zKGE5eBTzOdiaQ0xO57ALAfz+7oes29TKJa2LQeDtqaVyjHh4mAxFU2j27IcAEAQCG7Y0oeda8xRFU7LIb8BmTPfm7mWmDgcHDPTXuthOQBmm4RWtBzY/5Nd7Dq8NRAHzYDaRBe7MSYOZd5PZjm45fmnM7MKijXeA0yXkywJiKY1263EPtPMcljfY3Z4nYymc+IQPCjdunBxsHBaDk4IIebduKbbd+T5+d1O3+s8y8Gql6hHnQMAuCWhJRvvRZIa/IoEyQqYmjGH6rmVNN2AQdFUMQc26rPc3TnLnvMWaOxYScwBMJsZxlKa7VZin3EmBOt7s5ZDxBED4UHp1oVnK8EM/M0UEQfATANMZXSkpMIxh3imuFvpiFUwV49UVoBZDs1zgasWZq1I9uPa4XVVNVuJuZOWpjiYz7sL1DJctjqIy1Z3YE2ZdvEBt4RoqoDlkMrGHADTwnZaDvk1P5zWgVsOAOaSKnSD2gHpfNwuISfmUKgITpYEyKJgF8IxcWBCUt+YQ+udsGbzwuz/MOh1IZHRK3KhUUrx+BsjJVtEsFz+jN48AdaxMHMrlREHVYcsCrZV5WRDrx/f/f1rbPdSMfxuyYw5pFlyhRVzSKqQBIKBoAeEMHHglsNygIsDssU9JS0HrXS2kl+R0BNQ7KEpEcddrSiQgtWrtUCRhJa0HMJ54tBuV0mXtx5+fmIaf/Stt/D1PYV7XwEOcWiieM3oHLMcysQcMtp5z1Xw57mV4o5U1jaPCy5RQF/AjXNzSURTGgLWCFIec2hduDgg24q4qOUgiUip2bvUeXUOGQ0el4iegDLPrQSYNQ7mALza06oBaTYTg8GqpMMVBKU/+9wxAOb4zGIwQVWbxHIwDGoP4CkXQ0qqesEah4UQcLsQSanZOgc7lVWz3XmrOj04O5NANKWhr92dsx2n9eDiACBk5dD3FLUchNwiuAJuJa8sojegYCKSgmpVRTNroV6ZSkDrWg75MzFY871ycYdfnJzGnlMzEAgwMlO8i2uzxRxCsbRdgFksvTaW1nB0IoqE47O2WAIKcysVthwAYFXQi5HZJKIp1W65wZvvtS5cHOC0HAqLg+LKtRzyT4h4RodXkczWx9G07VJik7jqFW8AzKyUVq1zcAb1OzymlVcunfXbe0fQ4XXhfdv7cXa2uOWQ0ZpLHEbD2fhIMcvhqz87hV/63MuYiWdK9k6qBBZziDssB0qp6UKyLIfBTi9Gw0lEUhr6rNnTvG1368LFAWZTN1EgtqsiHzPmkLUcUqqR0944mdHgdYnoa1MQTqqYsOIO2/rbANQvjRUw89lbza2kG+ZFKsetxCyHMumsr5+ZxeVDndjQ68d4JFX0f5ONOTSHOIyHs1ZOsWOeiqaR1gy8eXauKjEHZ7aSZlBkdMO02NzMcvCAUvP9yLqVuOXQqnBxABCKZtDlk4uOnDRrB/ScLCCnayme1uFTRKy05uuy2oatljjUK40VsNxKLWY5sKrd3IB0+ZkO07E0ToXiuGxNEKs7vaAUOFdkQBBz3TRLhTQLRq9ocxd1E0Ydd/nn7VZyu8y26I7mkYm0ntNu3jl1ry/A3EqtdSPCycLFAayvUvGZ0W7LreQUB+dJkVR1eGTJFodDVsuMTX0BCKS+biV3C9Y5sFx7Z51DQJEgCqSkW+mNM3MAzFx/dmE7W0wcmiwgPRZOQpEE9LUpRa2ZmKPeoBpuJcCs05Gsm6R4RssZVOUUh6BPhiwJOTU+nNaCiwPMgHR3kUwlYH6dA5CbsZSw3EoDtjiYhW+dPhl3v2MtbrpgRY2OfD6KZeW0Esw6cFpgZmdWF+ZKNN977cwsJIHgosF2rOo035uzRTKW2AVYN2jBEbH1ZiycQn+7u2T2mbMYrRoBacB0J/VYVkE4qSKp6naNxIo2N1yiKRwBtwSvLPLOrC3MshYH1hL54Gi45KB6Z52DaN1VOd1KibQOryKir80NQrKWQ5tHwl/dsg3Xb+mt7R/iQJFa0HKwxCE/66tc873Xh2dxwco2uF0i+gJuyKKA4ek4/vjRN/GyNaeD4fyfNUNQOprS0O6VS2afxRwFaOefypq1yth8ByakrDOxKBD7BijgdsEnSzwg3cIsa3H40YFxfOp7B3Htxh78yXs2Fd0u61Yy7KA1C8RRSpFQTZ+vLAnoDSj24KB6xhoYiiQgoxtF5wEvRbJupdz/Z3uJ5nuqbmDfSBiXrjYbJwpWle+3XxvBd18/h2cPTeRs74w1NIM4mLULQskYUiytod8KDJ+3W0lxiINlOZwMxXN+BrKuJdtyULnx1i7vAAAgAElEQVRbqVVZ1uLAiqIeuPPS0jEHidU56Ahad1HMnE5rBnSD2k3PWNzB7RLKNjurBewi0SyB1WrABtyzIDSj0yvbcx7yGZtLIanqdsYYAAwGPbaY5O/n9Os3Q8ZSyipsUySx6HsZTWm4al0XZElA0FvcLVoJfoflwGoYTjNxsCwJABgMMnFwwSuL3HJoYZa1OERTWkWtLRTrghtNaQh6meWQWy3NXoOJQyOsBiA7Da6V+iuxmEP+NL0uv4zpeOG53TNWiquz6p3d9UoCwWyiuDg0Q1A6kdHhkUXLrVQs5qCiJ6DgifuuwUffMXRevy+gZD+vvVYNw+lQwvo5e+O0odcPl2imfXtliaeytjDLuitrNKXCr5RvbeG8G2d3aAk1t0EZE4eBRouDq/VGhUZSKgQC+OR8cVAwE8+AUjrvPZyxRIP5ywHgfdtXIJHWMJdU7ZnUDGdPpaZwK2V0uF1iUbdSRjMTJPyKZKdMnw+BQpbDtGk5OHuO/cYVq3HVui74FNOtNB6p7kwNTvOw7C2HQAWznZ0jFjttt5KGb716BuNWJavtVrJ8wI2zHEyRaqVah0hSRcDtmleH0uWToerUnlbmZCZuXrSc4vDOjT34tzsuRY8lKk6crptmcMmlWBxLLByQZpXM/irNJvflxBzMz/BkNI2g1wXZ0Qrc7RKxbaUpRl5F4nUOLcyythwiKS0nEFcM54jFDstyODgawUOvDOOWC/sBNI9byW1bDq1z0kZSWsH/J7ujnY6l5z0/a138neLA6PTL8yyOTJNlK7FmeoSQgjEQlsZarhV3pciSYGdG9TjcSEwoCuGTRd6yu4VZ5paDWlGBmjMThMUcDlrpqq+fmQWQHe7OxKGezfacMMuhlforhfOa7jHYhX86nsHfPnUA9zy8135uOp6BSyQFxb/LJyNjNUdk5IiD1tiYA6XUFgcWc6A095iiadMyquTmplKYFd1mBZsBoLeteKKGh9c5tDTLXBwW7lZq97isWgaz0I1N62L+8IbHHKQWtByShUWcBZunY2m8enoGu0/N2M/NxjPo9MkF40ksbjQTy7qW0jlupcb+79KaAUoBtxWQNijsDq2MmG05VFMczP+xTxFtN6nTisjHJ0uIZ7R5wsVpDZa3OKTVCsVBzHnsdYk5BUhA1q3U4XXhynWd2Lmms7oHWyFZcWgdyyG/IyvDdivFMxiZTSKcVG130nQ8UzS90xYVR6aT01rINNhyYJlmHpdo+/vz30/2+aum5cBey++W4FMsy6GEW8mriDBoa33WOFnKigMh5CuEkElCyNuOtU5CyDOEkGPW96DjuU8QQo4TQo4QQm5yrO8ghOy3nnuAWLd0hBCFEPIta303IWSoun9icUzLYWFuJbdLgKfAIHevdWIRQvDNe67CLRf1V+9AFwBLu20lyyGW0nICpgx28R+eTtj1CyzDZjaRKTq8qdNnioozKO20Fhodc2BBXlbnAMyvvYjWwHLwKxJcIoEiZS2H3hKWg9f6rPGgdGtSieXwVQA35639BYDnKKUbATxn/QxCyDYAdwC4wNrn84QQdmX9AoB7AGy0vthr3g1gllK6AcBnAHx6sX/MQsjvVV8Kp1tJcYm2lbC5L2Cve8+zQrVasGNtpZhDWjNy3gOGLAloc0t46+ycvTY8bebmz5ayHKxYRY44NFFAmrVmYXUOwHyxj1Y5WwkwhYaJsK+CmEOPZVUU63TLWdqUFQdK6U8BzOQt3wrgIevxQwBuc6x/k1KappSeAnAcwOWEkH4AbZTSV6jpoHw4bx/2Wo8BuJEUchRXmaSqQzfogi0HRRLsPjY3bO21O1iebz/9amGnsraQ5ZBS9ZyMMSfdfgX7z4Xtn5nlMG3FHArR2ezi4LQcWPZZntjbMQelerGtlR0e9LebMTNmCZdyK1002A4AeHNkrug2nKXLYmMOfZTSMQCwvrPOcgMAzjq2G7HWBqzH+es5+1BKNQBhAF2Ffikh5B5CyF5CyN6pqalFHrrJQszy/JgDE4JNfX6s7/FDFIh9h9do7DvNFrIcUpphXyTz6fLLtlvDr0gYnk5A0w2Ek2pRcWB9sHLdSgZYGUWjfegph+Ugi0zs891KKkSBFLSoFsuf3rQZ/3X35QAclkMJt9Jg0IMun5xjuXFah2pf0Qrd8dMS66X2mb9I6YOU0p2U0p09PT2LPESTqNXMrSJxcBYBSVm30lCXD1v6A/DKYtkq63rRagFpVTd7VxWzHLqs+IHbJeCiwXacno5jNjG/AM4JIQRdPtlukAiYlgNzqTS6fUZSdcYczPczP+YQS5su0Wp+7nyKZPcYqyRbiRCCS1Z1cHFoURYrDhOWqwjW90lrfQTAKsd2gwBGrfXBAus5+xBCJADtmO/GqjqsqnahdQ5ul2CLw9puH+67fgP+4ZcvrM1BLgL3EgtIn51JlGx0x0SuWNdRFnQeDHox1O3D6VDc7ptUTBzYc07LIa0Z9kyDZnEruZ1upbz3M1ZhAedi6fLLCHpdBRMBnFy8qgPHp2L2zRandVisODwJ4C7r8V0AnnCs32FlIK2FGXjeY7meooSQK614wkfy9mGv9SEAz9M6JE4v1q1kBqQltHtc6PDK2NQXwAcuWlmz41wo2cZ7zW85pFQd7/nMi/jW3rMltwFQ1H3Cgsurgh4MdXkxm1Bxyuom2lmiU2m+OORaDs0UkM51K50KxfHjA+MVV/cvlnvftR7fvOeqsttdvKoDlAL7R8Jlt+UsLcp+uggh3wBwHYBuQsgIgL8B8I8AHiWE3A3gDIDbAYBSeoAQ8iiAgwA0APdRStktz70wM588AJ62vgDgywC+Rgg5DtNiuKMqf1kZsm6l8paDKBC4RAJVp3BLAu66egg3bq3fAJ+FIIkCRIEsCcshnFSRUg2MzRXPdmHioBS1HEy3x2DQizVdPgDZ8aCdJab7dfpkO7MJMGMOTBwa3bI7JyCdl6305ZdP4ht7zmJrf6Cqaaz5BH2y3Z6+FBdbQem9w7O4ekN3zY6HU3/KfroopXcWeerGItvfD+D+Aut7AWwvsJ6CJS71ZKF54m5JhKprcLtE7FgTxI41wfI7NYhSA2KaCfYeREq4JJgFVCzgn3UrebC+xxQHNshnoZYDS31tdOO9ZIEiOCZYM/EMdIPi7XMR3FDHCYPF6PDKuHiwHf/6zFGcCsXxz7dfbE9L5CxtmiPFpgEsJCANZO9cmyUrqRSlRks2E6zKN1qgqyoj61YqHZAeDHqxvsePq9d34fhkDEC2SWLh/WTE0pr9+qZbyfwdje6tVLjOwXw/Z+NZIa2lW2khPPTbl+POy1fh8TfO4eBopNGHw6kSzX+lqzK6QXFsIopoSgMpMCOgGG6XAEkgkMTm/5exsabNDhNoNiO6EOUC0juHgvizmzfjhi29IITgE+/bCsAUfbmEkLPWG6GY2UIjoxvwuESIAml4zCGV0UGIKfJ2xbtlQc05/lfVLIA7Hzq8Mj60w8xDKTZ8ibP0aP4rXZV54LljuPmzL2EsnIJfkebNCCiG2yWe95zeeuFXpJJ3481CzHYrFT/WNLMcilzoXaKA379ug117cuFgO27fMYhNjur1QrDK36moJQ6aAVkSrNhS491KrF13fsxhLpGxCy8DTWI5AIWrzjlLm+b5dNWJXUOd0A2KF49OVZTGynC7hKoWHNWSLr9s3xE3M6wFRCnLIaWVDkgX4tO/clHhQhkHzoE2gFMchIbFHL6++wwosu26AcxrvDebyOAdG7vxkyNTNQ1ILxQW/Ofi0Do0z6erTly2pgMukWAqmsaWFaXvLp24pWxaYbPT7VdwYAn4fhcSkF6IMFdiDbLK3xxxEM3Ja42yHP7jpyfgk82xn+68GFdaM5BSdaRUA7uGOvHOjT1477a+hhxnIQJW075QjItDq7A0boWriFeWcPFgB4CFdbR0FiQ1O91+ZUlYDrZbKVlBQLrKwmzOegCmIuY8jrTusBwaEMyPpFQMTycwGU0jqWq2m0wWs+LAOs92eF24+x1rsarTW/fjLAYhxMoAa/7PHacylsbVrspcuc5s3bSQEYsr2t3oby/ehKyZ6PLJiKa0pg9Kx6xpZklVL3pBLheQXiySKKDLp2Aqlgal1HYryZLQkPYZhyxLbzqeRjSl2W4lFndIa7pd+V2s22yj6fTNn83NWbosc3Go3HL41K0X4Iu/uaNWh1RVugPz5xU0I86BScXaL5SrkD4fegMKJiNpWwwUKyDdiJgDcwNSarYUcXb5lSXTmmHi0OFtzJTBcuT3q+IsbZalOOxYE4RLJOhYwChPryxVbZh7rWGZI83gWjo8HsFrw7MFn3NmKUVSGr7wkxN4+1xuG4ZsEVz14z29bQomo2lbDGTRdCupDXArsZnkADAym7QtB8D8251upWa1HLr8ctPfkHAqZ1mKg0cW8aW7duF33rmu0YdSE5jlMN0EwcF//tER/Pl39hV8LuYQh/FwCp/+4WF8fc+ZnG3s9hk1KD7s8SuYjKZsl1bWrZQVh8loquq/txAHRiO2qGsGzRMHs+K92cWh0yc3xWeOUx2WpTgAwLs29TRVQK+adPtyC7wayWxCxchsouAQ+lhasy/6h8fNO2dW3cxIW7GASutRFkJvm4JQLGMLUH4q676ROVzx98/NO6Zqk9Z0HJuI4l2bs23onW4lxZUbc2hmt1IsrS2Jvl6c8ixbcWhlWL+hUCyD7+8bw0+Pnt9gpPMhYjXXK+RuiKZUDHSYk8cOj0UBACfyLsTmFLjafEx7A27oBsW4lbEki4KZymq1zxidS4FSYCJSW+vh6HgMmkHxrk09YOMZnAF42cqgmktkrHqb5kypLjSbm7N04eLQgvgUCR6XiFAsjU8+dQB//p190BqUu89qGEbn5l9gYykNKy1xODTOsnUymM2Zs6AvqABuIbBaBzYDWZYEuKSs5cAsCtYltVZ8b/8oRIHgqnVddq8oT16b+LRmYDahNq1LCcjOz+CupdaAi0OL0uWXcWA0jKloGmPhFF440hjrgdUwnCvQljua1rCyw0wPPjIetdePT2Wth5Rq1KwynU05G3GIg+xon8Ea4CVrmBKc0Qw8tncEN27pRW+b2xYsj5z9m1kq61xCLdlMsNF08SrploKLQ4vS5Vew97SZJeQSCR7ZPVz3Y8hohn1hzRcHSiliaQ19bW5r/oRht4pw+vhNt1KtLAdTmEZmzbkOLObAxIHNpq6lOPzowDim4xn8+hWrAQB9bbljOoFsl925RAbBJo03AFnLgYtDa8DFoUXp8cvQDApJIPjtd6zFi0enMFpiqE4tcLbFyP/d8YwOSs1akzar3uTCgXa4XUKOOKQ1o2Y+dtZ8j1kOiijYNQVAfdxKj+49i8GgB9duNIPRTLDcBbKVZhOZpg1GA41NoT47k8Bl//sZHJ2Ilt+YUxFcHFoU5rvevCKAazf2gFLgzEyizF7VxdlQj/n1GSyN1a+40GbVmwwGPVjX7Z9vOdTIreR2iWj3uOzfl7UczIB0ssaWQ0YzsOfUDN67bYWdjcUsh/w6h4xuNL1bqc3tgiSQhlgOb43MYSaeweFxLg7VgotDi9IdMC8iFw122Heh9W6nwYrcRIFgNJwnDlbrDL9bsrvjDnR4sKF3vjjUsuHhOzZ02y6v/FTWZI0thwOjYaQ1AzuHslMFe9pMy8EZc/ApIsbmkphLqk3tVhIEgqCvMYVwp6bMueHhEh1+m53ToTh+6XMv1zw7rlK4OLQozHK4eLDdvvOuuzhYJ+r6Ht88t1LEMaa1zWO6lVZ2eLC+x49zc0n7WGsZkAaAWy7qtx/nB6RZzKFW/zdWOb7TMXK2LzDfcrjn2nXwKhJ0gzZ1thLQuBYap6YtcUiU/t2hWLphmXvl+P7+Mew/F8brRToK1BsuDi3K6k4vCDEnpXlsy6G+JwWLOWxZ0ZZTbAZk3UoBJddyWNGeO4QnVcNUVgC4fnMvvI4OqM72Gex4EzWyHPaensWqTg9627INHTf2BSAJBIPBbIHmht4AHv3YVbh6fRd2DXXW5FiqRYfXlZOKXC9Oh0xxYFXkhUhrOq7/p5/gsddG6nJMb5yZxT88faji7V85MQ2g/u7fYnBxaFFu2NKLZ/7oXdjQG2icW8lKY93a3wYgNyjNmu7luJWCHnt8J7v7TKtGzbKVALMS+cat5lwE1j7DdivVMOZAKcXe4VnsXJN7sV/b7cP+T96E7QPt89a//rtX4uJVHVU/lmrS6ZPtSu56coqJQwm3UiylIZrWMBauj9vme/vG8B8vnkQ8XX4qY0rV8erpGQBcHDg1RhAINvT6AWRdFLVMyQSA6Vga//Pbb2HaylaxLYd+c6iSM52VdWH1K1m3Un+7G11MHKzXMIvgavsx/eg1Q7h6fRd6AoodkKaU1rTO4cxMAqFYGjscLiWGs3XGUqPDK5e8e68Fc4kMZq3fWep319pNmA/7DLOBUqV4/cws0poBgXBx4NQRd53cSj87MY3HXhvBv79wHIAZc5AEgosG2iEQ4Bcnp+1to3bMwYX3X9iP+65fj4DbNS8dMlVjywEALlsdxNd/90ookmjXWqg6tS2HVA3cSm+NmN1nL13d3JbAQgl6XZhLqgV7adUKZjUQUmbkbB2KGp2wqXiTFQSYf358GqJAcO2mHi4OnPrBmtvV+qRgxWSP7D6DsXASkZSKNo8LXX4F79zYg/9+YxSGQfHzEyH7hPYrEi5dHcSf3rQFAGy3EjuxapnKWgiXaKaUqnq2gK8WMQeWXbO+x1/1124kQa8M3aA57dhrzenp7P9yLlncpWUXNda4HQojtADL4ecnQrhwoB3b+ttwbjbZFEFzLg7LAEGwponVXByS8MoiKKX4wk9OIJLU7AK3X75sAOfmkviz7+zDr//nbjyy+wy8sggxr9uqRxbhk0VMxzLQdAOaQevaaI6N5XSKQy1E9fR0HCvb3U3bRG+xsDqMuTrGHU6FEhAIcNFAe0VupWq8n8mMjgd/egI3/9tPcbDIvHZ2gzNVRhxSqo7958K4cl0X1nR5oRm0bnGRUlQ+Co2zpHG7xKpf5J58axQDHW7ssIKqI7NJbOz1Y0W7Gz89OoWhbp9d4PbebSvgVyQ89toI3rGhG1et74JfKfzx6/IrmI6nHSNC62g5WFZWRjeybqUaicNQt6/qr9toWB3GbELFmq76/M5ToThWdnjQ06bkBKQnIikMTyewaygIQgiSqmnNVOP9/LPv7MNTb40CAF46NoVtK9tynjcMas/TLmc5vHV2DqpOsXNNEF7FvFk4M5No+EgBbjksEzwuseoXub///iF87vnj9s8jswkMBr3Y2t+G4ZkExsMpOxPJI4u48/JV2Njrx+fuvBT3Xb8Bd109VPB1u/0yQrG0Y9BP/e6uXZbl4OwLVRPLIdSi4mDFjOqZzjoym8DqTi86PDIymmF/bj79w8P41f94Bbf+359hMppatOWQyGj4t2eP2q8bT2v40YFx/MYVq9Htl20XqZO5pArDCrs4B0Y9e3ACzx6cgG5kYzJ7rbqGHWuCWG0JQjPEHbg4LBPcLmHRAem/eeLtnGAyI5JScWzCrGamlOLcbBKDQQ+2rGgDpcDRiaidiQQAf/n+rfjRH15rX0CK0eVXMB3LINUAyyHrVsoGpKsdcwgnVMwmVAx1td6wKVakV8901slIGiva3HbfKeZaGplJotuvYN9IGE/vH8+mJlfwfh6fjOK2//szhJMqXj4Wwr89ewwvWnNRfnJkChnNwAcuWom13T6cnJovDs7+UsytRCnF//ONN/A7D+/Fez7zIs5aAvDq6Rls7PUj6JPR3+6BSyRcHDj1Y7FupWRGx0OvDOP7+8Zy1lXdQCKj49xcEtGUiqmY6QYyxcFMXTUobMsBAAghFU10My2HbNFcPf3yTIgSGc3+f1U7W4kFUIe6WtBycLiV6gGlFJPRFHraFLRbLkwWlB6LJHH5WjNVOJbWHJZg+ZukN87M4c2zczg6EbVjByy28MMD4+jyybh8bSfWdftxsoDlwMQh4JYwGcm6l5Kqjl+6eCWmYxl85Ct7MBlJ4bXhWey0ihtFqwDyzDQXB06dcC/SrcQ+5PntL5zzn49NxuzOpoNBL1Z3eu3aCnbCLoQun4KZeNq+w6unW6ndY975sv42kkCq7lZi4rC2Bd1KbW4XBFK/gPRsQoWqU/QG3OjwZC0Hw6CYCKexutMHWRQQTWkLqnNg2VZT0bR9DhwYjSCl6nj+0ATes60PokCwtseHUCyd04EYyA482trfZruVhq0L/od2DOIrv7ULY+Ek3vVPP0E0pWGXo79Wf7sbY+H6dlAuBBeHZcJiYw5T1omRP4/BeTIcm4jaJvJg0ANBINhkWQ9tixCHbr8MwzGes55upaDPPF42uS7oM1ufq1VMLTwVioMQNDzgWAsEgaDd46qbW4ldePvaFLQ73EoziQwyuoH+djf8bgmxtLqgVFbWwC8Uy4rDwdEwfn4ihHhGx03bVwAA1lkCfyrPtcT22dbfhtmEioxmYNi6KVjT6cWONUF8995r8O5tfRjo8OAdG7rtfdvcLrsOqJGc11lHCDlNCNlPCHmTELLXWuskhDxDCDlmfQ86tv8EIeQ4IeQIIeQmx/oO63WOE0IeIIRUf5r8MmexMQd2BzRPHJLZD++R8azlMBA0x35u6bPEwb3whDhWJW3PWaij5cB85sxS6rR+rmbcYXg6gZXtnpZLY2UEvXLd3ErMZdMbcNtptJGkijFL3Fe0u+FXJMTTOpIZ8zNbiSXIiummomn7HBgNp/D13WcRUCRcvd5MxVrXY4rDyVDu7PPpWAYCATb2mXUsoVgaZ2bMlFs2GnfbyjZ87s5L8bO/uCGnv5YpZktcHCyup5ReQindaf38FwCeo5RuBPCc9TMIIdsA3AHgAgA3A/g8IYSdHV8AcA+AjdbXzVU4Lo6DxcYc2B1QNKXlWAus/YVAgGOTUYzMJtHlk+0JZqxlxmIsBzZukglSPS0HFtRkeebMkqhmpteJqRiGulvPamAEfXLdspWYddnXpmTdSsmM7Zbpb3fDp0iIprQFZZ+xz/pUNI2pWNpOVHj20ARu2Npr37Cs7vRBFMg8y2E6nkanT8EK66I/GU2bNwUdHrsKvxgBt5Tjtm0UtTjrbgXwkPX4IQC3Oda/SSlNU0pPATgO4HJCSD+ANkrpK9SsuX/YsQ+nSizWrRRy5GizuzEgt+Pq4fEoTkzGMGhZDQDsxnGs4nkh9Fj7sAFB9bzDViSzCM+2HKzMqmpV1T6yexj7RsK4al2digAaQNDrqp/lEM1aDl5ZhEskmEuoGI9kLYeAkutWymhGTippIZhlzNxKzpkb77NcSoDZrHFV0IO3RyN4ev+Y3WRvKppBt1+2J/tNRlIYnklgTQUZagFFQiyjwShzjLXmfMWBAvgxIeQ1Qsg91lofpXQMAKzvvdb6AICzjn1HrLUB63H+OqeKKC5xUW4lZ0qeMyjNTp6dQ0FMRdPYc3oGVzoueDvXBPHNe65c1EXQdivN1V8cALPKlw0nssWhCpbDvpE5/K8nDuD6zT2497oN5/16zYrZfK8+lsNUNI2AIsEjiyDEjHfMJVWMhVNwiQTdPsV20zgFvtyNktOtFIqmsaHXj4EOD9wuAddu6snZdm23D88fnsS9j7yO775xDoBpOXT7FXsU7WQ0jTPTcazuLJ+EEHC7QCkQzzTWejjfCulrKKWjhJBeAM8QQg6X2LZQHIGWWJ//AqYA3QMAq1evXuixLmsqtRxeODKJnx8P4a9u2QbAbAEQUCRE01pO3IFZDrddOoD958L4yFVrcNslWU0nhOSIxULo8LggCgQHzpnN6Xx17lIa9LlwxBo32WkNTapGzOGnR6egGxSf+bVL5rUNaSVMy6F+biV2AQbM7LhwQkUyo6OvzQ1BIPApEuIhPec9TKo6fEUq9IHs5/vcXAqRlIZuv4Lbdw4ioxm265Tx4avWYEW7B4/uPYsJyx05Hctg9WovunwyBAK8eXbOqhovbzn4rThdNKUh4G7c5L/zEgdK6aj1fZIQ8jiAywFMEEL6KaVjlsto0tp8BMAqx+6DAEat9cEC64V+34MAHgSAnTt3NtbmWmKYAenyF7in94/h0b0j+N13rkNvmxtTsTS29Afwxpm5XMshpYEQ4JLBDjz++9dU9VgFgeD6zT0IJ1XcvmNVTrCuHgS9sj1HutNbvZjDqVDC9I03+TS386XDKyOlGlbTxNoK+2Q0bbtu2O8OJ1VohpmpBJjNHaOpXMuhnJsw4shWAkz36K9fUfiG9IYtfbhhSx+eOzRhF7yFYqblIIkC3n9hvz1gaE0FGWoBSxwaHZRetFuJEOIjhATYYwDvBfA2gCcB3GVtdheAJ6zHTwK4gxCiEELWwgw877FcT1FCyJVWltJHHPtwqoTHJVaUkslS+H52IgTA/JD3BtxY0e7Ocyup8CtSRUVti+FLd+3Ct3/vavzqrlXlN64yzot3sIoxh+HpONa0YOFbPvWskp6IpNDnsByCXheGZ+I4N5fEinYzBhawUlmdrsGybqWUBsnx2e72lxf0noCCqVgaiYxZU8ESK/785i12EHp1JZaDwiyHxs7DPp+YQx+AlwkhbwHYA+D7lNIfAvhHAO8hhBwD8B7rZ1BKDwB4FMBBAD8EcB+llL1D9wL4Eswg9QkAT5/HcXEKUOk0OCYOLx8z22WEoml0+2UMdHjs3H/ANLvbGmjy1hJW5QtkZ3FXI+ZwejqBtctAHDqtDK/91syKWmFWR6dzLMvbLh3A2Zkkzs4kbcvBJ0tIqQaiKXVe+/oTUzH86zNHc+ZPaLqBWFrLuZB3VZBY0RNQMBVN2+fJSkucVnV68bFr18HjEiuqimeupEbXOixaHCilJymlF1tfF1BK77fWpymlN1JKN1rfZxz73E8pXU8p3UwpfdqxvpdSut167uO0npNClgluubJpcCzQ/PMTIaQ1HfY6H7cAABTESURBVJGUhi6/goEOT94kN21RaapLAaflUK1spVhaQyiWxpoWTmFlXLY6iG6/gnu+9hr+/fljNfs9kaSGjGagN5C9cN9yYb9dg8DSSJkPfyqatodJsffz0VfP4oHnjuV0TmUXZeesjZ5KxMHPxME8T1g9AwD88Xs24aU/v75knIOx5N1KnKWF27pjSpfJWAonVciigLFwCntPm90iu/0KVnZ4MB5JIWM1w4skVftD3Go4LYdqZSudDrVuP6V8etvc+MmfXoeLV3XghwfGa/Z7JqzqaKflQAjBp269AD0BBRevMtOpA9YFOZ7R0enPfT8PWYkHowWSLZzi0B2ozK0UiqXt4s2VHbnHVWlad9atxMWBUwcqdStFkiqu3WSW8j+618w87vbL2LEmCN2geObghLldSmtZtxITBFEgtgCerziwvjrLQRwA8wK3vseH2Xjt/ObZ6ujci+6G3gD2/OWN9pwR5906yz5j58HhMbOZnnO4DrOe11vVz15ZnJehVIiegALNoDg4FoZAgL5FJlLYlgMXB049YI3wSl3kdIMimtZwwcp27FwTxJPWMJPugIJrN/VgdacXD71yGoAZLHO2424lmFvJ4xKz/7dFuJWOTUTt3j+s2V4lqYytQqdXxkwNK6Wn4yyTaP5dvbMDj99h4XY5LMGZeMZ2JxWyHFZ1euESiR1YLkePJVL7RsLoa3Pbs0EWik+WQMjSDkhzlhBZy6G4W4ml77V7XPjYu9aDRX56/ApEgeDDV67BnlMzODQWQSTZ+gFpt0u0R6wu1HIIJ1V84HMv4+p/eB5//K03cXg8it6AUpHPuVUI+mQkVb0mk/SAbN8vZg0UwzlxkGVSJTMGDo9nx3uOOywHlpTR4XWh269U7A5icYlDYxE7GL4YBIHAL5u1RY2Ei8MywSPnZmkUIuwQhxu39NpmNTs5bt85CEUS8K1XzyKa1hbVVG8pwC4gXiuI75XFBVsOLx6dQlozcNP2FXj8zXN46q3RZeNSYjD3XK1SWmfiZnO7jjKJEU5xYFZAStVxeMyMN7R7XHluJfM8aHO7sK2/DVtW5I4ALQazHFSd5gSjF4PfLTU85tCaZzdnHqxRWKm7OKc4CALBX39gG36wfwwe6yLZ4ZWxcyiI5w5PgNLFNdVbCrDme8yl5FlE08JnD06gyyfjgTsuxVXruvD//vfbLd1srxBMZGfiGfS3n9/FshDT8Qw6fXLZWhunW8mZYDA8HUeXT8aW/oDdLgXIupXaPC48+JGdBVs4FKLHEfsYOE9xYM33NN0ABRbtojofuDgsE9gFvpQ4sJOC9cW/bnMvrtvcm7PNrqFO/Oy4WQPRqm4lvyJBEoid/uuWFyYOqm7ghSOTeN/2FRAFgt+8cg1WtLmxyWpjvlywp8LVKCg9HUvbF/tSOC2HDo85jCil6jgyHsXmFQH0t3vw8rGQvU0kqUEgZtuWhUwP8CuS3Rr/vC0HxewH9ddPvI2R2SS+dvcV5/V6i4GLwzKhkmwlp+VQjF3WOEMALZvKSghBh1eGx2oV7nGJCxoVuufUDKIpDe/e2mevvXtbX4k9WhN24Z6poVupEnFw9ubyyGaSQTyt48hEFHdevhoBRcJkNIVQLI1nDk5gLplBm8e1IGEAzM9NT0DJKcBbLAG3C3OJDPaeTtnnZb1pzbObM49Ksm7CDl9rMS5Z1QFRINAN2rJuJcDMgPEr5t/nlcUFNd57+u0xuF0C3rGxu/zGLQxrPVKrDq0z8Qy2riwfD5BEwXYNelwiPLKI4ek4UqqBdd0+iIIAgwJ/972D+O83R9EbUBZtFff4TXGoRszh9HQco3NJUAoYBq1Zq5picHFYJrCBOSmteLZSJZaDT5GwfWUb3hoJt6xbCQDu/+CF8CnZOdissKkcaU3HU2+N4aYLVlSUG9/KsEBxrdJZp+MZOzW1HH63hKSqwytLcLtEHLaK31Z3+WBYaXlP7RsDYDbz2z5QWRA6HxZ3OO+YgyLhzEzCzhgMJ1VbbOsFz1ZaJrgrDEjLolB28tpOy7XUqnUOALBjTdDOUun2K5iu8AL3wuEphJMqPngpH0kiiQLa3FJNpsKpuoFwUq3IrQRk4w7MrcRawQx1ee0eSLpBsdaaCV3qBqkU/e0eBBTJTmpYLAG3BGcTIVbTUU+4OCwTBIFALpOvH0mqFflaf+WyQbx3W19NMlCakS6/WcxVyWSu774+gp6AkjMwfjnT6ZMxU8FUuEd2D8+bU14KJjiVNMQDsuLglUU7OUMUCFZ2eNBvtbmQRQGfu/NSELL4ZIvfv349Hr778gXHK+Yfb+7vn4rWZz6GEy4Oywi3JJTsrRROqmivwBrYtrIND35kZ9lZuK1Ct1+BblDMlQkMJjM6Xjgyif9x8UpIDUg9bEaCvvJT4eYSGfzV42/jSy+dLLkdpdTunsosuYrdSg5xYMkZAx0euEQBAUVCm1vCtZt6sH2gHf/zvZvxy5cNlnq5ovQG3Lh0dbD8hmXIT/ZohOXQun4Bzjw8ZYq5THFo3TjCYmF3p+VSJ49NRqHqFLuGzv/i0Cp0emV7nnMx2ECdV0/bDZyRUnWcCsWxtd907VFK8cHP/xwXD7bjb2/dbscxKnUr+RxuJSYOrJUJIQRfumuXPQP9vusbP8KV1WZs7PXj2GTMrgavJ/z2ZhnhdolIaaXcSq3bhvt86LYuQFOx0ndvRydiALDs6hlKEfTJmI1n8MjuYXz22cLtu0PWhe/gaMSutfniiydwywMv4YzVsPD4ZAxvnp3DN189i9l4ZsGWQ8AtQSCm64ilKK92TGW7fG3neWcYVRPWfWDnUBACyZ3lXi+4OCwjPC5uOSyG7gCzHErfvR2diEKWhGUx7a1Sgl4XpuMZfPbZY/jSyydRaFQL+78aFHht2GwT/4P9YzAo8Njr5njNp982W3+nNQOPvTaCGetiWWnMod3jQsBtxtM8eZZDM8JiDht7A+j0ybaA1hMuDssIxSWWTWXl4jAfdnc6XdZyiGJ9jx9infPRm5mgT0ZaMzAZTSOa0jA8nUBGM5DIZPsGOf3pe07N4ORUDEcnYnCJBN95bQSGQfH02+PYsSaIXUNBPLJ7GKFYZX2VGL/zzrX4/G9cBiDbLWB1Z/OK+OpOLySB4LI1QXT5FG45cGpL0OvCeLhwRohhUERSXBwKEfTKlmlf+u7t2EQMm/r8JbdZbnR6c90++8+F8cmnDuBDX3jFXgtF0yAEuHhVB3afnMaPDpgzQ/74PZtxbi6Jzz53DIfGInjf9hX48FVDOD2dwHdeHzHflwqFeDDoxTVWBll+zKEZWd3lxYFP3YRLVnWgOyCXvTGpBVwclhFXruvC0YkYJgsECKNpDZQuPr+7lREEgk6fUjJjJJpScW4uyeMNebDCravXd0EWBbx5dg7f3zeGw+MRe6pgKJ5Bp1fGdZt68PqZOfzbs0dx0WA7PnrNEDq8Lnz2uWOQBIKbt6/ALRf244KVbRgLpyoORufjs4oTnTGHZoQ1y+zyVV5nU014ttIy4p0bu/GPTwMvHQvhV3bkpup99WenAQCbV/CLWyG6/XLJXPNjkzwYXQg2iOeWi/oRS2v49t6ziFitqM/OJrC+x4/pWBrdfgW/f/16+BUJ/7V7GL95xRq4XSKe+vg7MB3PoL/dbU9W++sPbMMdD/6i4iE8+fzarlXY2OdfMrM1uvwyQlGeysqpIVtXtKHbL+OlY1O2OKRUHT89OoUHnj+G2y5ZiXdu7GnwUTYnZpV08RP0qNWOgbuVcrlkVRD/51cuwq2XrsTB0Qj2jYTt54an41jf40colkGXX4Yiifjda9fhd69dZ2+zqtOLVXl3+Feu68LvvWs9BoKLyy4q9JrNTLdfQTyjI5nR7XhJPeDisIwQBIJ3bOjGy8dDMAyKUCyN9z/wEkKxDAaDHvztrdsbfYhNS5dfxpkziXnrlFJ8+eVT+M+XTsKvSFgVXDoXnXogCgS/umsVAODCgXYAwEWD7dg3EsapkPn/nI6lceFgx4Je9y/et6W6B9rEMOsrFEvXVdR4zGGZ8c6NPQjFMjg4FsGPD04gFMvgX26/GE//wTt5vKEE3f7CGSOvn5nF333/ENZ0+fClu3bWvXPmUoJVDt+xazUCbgnD1lzt6Vim4BxojgmbxFjvuAO3HJYZ123ugSQQPLVvFCcm4xgMevDLlw2cdy+YVqfLLyOR0ZHIaDndVp98cxSKJODLd+1EoIW71FaDzSsC+M69V+OSVR34xp4zOD2dQErVEU1rFc9pXo6wWo7xcBJYtTAL63zglsMyo8uv4LrNPXj89XP4+YkQrtvcw4WhArp98wvhNN3A9/eP4YYtvVwYKmTHmiBEgWBNlxenQ/EFVzovR9b3+NDtl/Gppw5idAHNCc8XLg7LkA9eOojJaBqJjI7rNvWW34GD7kDW78v4xckZhGIZ/I+LVzbqsJYsa7t9GJlN2HU33HIoTsDtwlc/ejmiKQ23f/EVvHB4si6/l4vDMuTGrb0IuCXIooCrN3Q1+nCWBOu6/RAI8Lnnj0PVzfz8774+Ap8s4votXGAXypouHwwKvHnWzF5abFrqcmH7QDu+9jtXwO0S8NGvvoqvvHyq5r+Ti8MyxO0S8fHrN+C3rhla9tPKKmWo24f/fdt2PH94En/1+H6cm0viybdGcfvOVXbFLadyhqzq5NeGzU6s3HIozyWrOvD0H1yLP795Cz5wUX/Nfx+/MixTPvau9Y0+hCXHb1yxBuPhFD73/HG7QZwzJ59TORt7A1AkwW6VwS2HypAlAfdeV59zl1sOHM4C+KN3b8K7t/bixFQcH7x04LxnBS9X2r0u/H8f3QWvS4RfkbgF24Twd4TDWQCCQPCvv3YJPv/CCfzW1UONPpwlzdXru/HEx6/BmZn5xYWcxsPFgcNZIG1u17Kq0K0l/397dx8qWV3Hcfz94d5VWNa08BbX1DbpgXSLzEWQlB7AaqMIeiBF3M2gByjK+qc1iv6oICPFtGi71ErPD6bSpuBiD6tZFG1UrMu6ri7RakutZetmVFif/ji/YYc7c73de8/MOXPP5wWHOfObw29+3y9z5zvnd8/85qyZdZw1kyVH2qg100qSXiNpv6QHJG1tejwREV3WiuIgaQr4PLAJOBu4VNLZzY4qIqK7WlEcgPOBB2wftP1v4NvAGxoeU0REZ7WlODwTONR3/6HSFhERDWhLcRi2uM/AL5FLeqek3ZJ2HzlyZAzDiojoprYUh4eAM/runw78cf5Btudsb7S9cWYmP0oTETEqbSkOvwKeK+nZkk4ALgF2NDymiIjOasX3HGw/Iem9wE5gCthue2/Dw4qI6CzZA1P7E0HSMWD/kIdOBo4OaV+uU4FHauyv7vG1vb8689f2WOvuryc5XL78/R7Xy8WzbC8+L297Ijdg9wLtc+N4nhX0V/f42t5fbfmbgFhr7S85bFfuJiTeBftbai7a8j+HOv2g6QEsou7xtb2/OrU91jbnrqftMbc9h22Pt7b+JnlaabftjavleVar5G/lksPlS+6OW2ouJvnMYW6VPc9qlfytXHK4fMndcUvKxcSeOURExOhM8plDRESMSOeKg6QzJP1E0j5JeyW9v7Q/TdKdkg6U26eW9osl/VrSnnL7ytK+VtLtku4r/XyqybjGpa78lcfukPS70s+2sjrvqldnDvv63CHp3nHHMm41v/52lZ8J+G3Znt5UXK1U52VUk7ABs8BLyv5JwP1Uy4R/Gtha2rcCV5f9c4HTyv4G4OGyvxZ4Rdk/AfgpsKnp+CYlf+X+U8qtgJuBS5qOb9JyWNreCHwTuLfp2CYpd8AuYGPTMbV1a3wATW/A94GLqb5QN1vaZoH9Q44V8BfgxCGPfRZ4R9PxTGL+gDVUl+C9tel4Ji2HwDrgnvIGueqLQ825S3F4kq1z00r9JK2n+mTxS+AZtg8DlNthp5hvAn5j+1/z+jkFeD3wo1GOt23qyJ+kncCfgWPA90Y85NapIYcfB64BOvdDzDX9/d5YppQ+KmnY6tCd1dniIGkd1VTGlbYf+z+OPwe4GnjXvPZp4FvA9bYPjmKsbVRX/my/muqT3onAwFz6arbSHEp6MfAc27eOdKAtVNPr7zLbLwQuKtvloxjrpOpkcZC0huqF9Q3bt5TmP0maLY/PUn2a7R1/OnArsNn2g/O6mwMO2L5u9CNvh5rzh+1/Uq3C25lf/6sphxcA50n6PdXU0vMk7RpPBM2p6/Vn++Fye4zqfzbnjyeCydC54lBOHb8M7LN9bd9DO4AtZX8L1Vxmb8roduAq2z+b19cnqBa6unLU426LuvInaV3fH/M08FrgvtFH0Ly6cmj7C7ZPs70euBC43/bLRx9Bc2p8/U1LOrXsrwFeB6z6q72WonNfgpN0IdWVRXuA/5bmD1PNW34XOBP4A/AW23+V9BHgKuBAXzevorpC6RDVG1pvDvNztr808iAaVGP+BNxGNZ00BfwY+IDtJ8YRR5PqyqHt/k/H64HbbG8YeQANqvH19zhwN9XFEFPAD4EP2v7POOKYBJ0rDhERsbjOTStFRMTiUhwiImJAikNERAxIcYiIiAEpDhERMSDFIWIEJL1b0uYlHL++C6uqxuSYbnoAEauNpGnb25oeR8RKpDhEDFG+VHYH1ZerzqVaGnoz8ALgWqrVUB8B3mb7cFm24ufAS4Edkk4C/m77M2UNpG1Uy7w/CLzd9qOSzgO2Uy2ad8/4ootYXKaVIhb2fGDO9ouAx4D3ADcAb7bde2P/ZN/xp9h+me1r5vXzVeBDpZ89wMdK+43A+2xfMMogIpYjZw4RCzvUtx7P16mWadgA3FlWd54CDvcd/535HUg6mapo3FWavgLcNKT9a8Cm+kOIWJ4Uh4iFzV9b5hiw90k+6T++hL41pP+I1si0UsTCzpTUKwSXAr8AZnptktaU3wlYkO2jwKOSLipNlwN32f4bcLQsJAdwWf3Dj1i+nDlELGwfsEXSF6lW9bwB2AlcX6aFpoHrgL2L9LMF2CZpLXAQuKK0XwFsl/SP0m9Ea2RV1oghurIEdsRCMq0UEREDcuYQEREDcuYQEREDUhwiImJAikNERAxIcYiIiAEpDhERMSDFISIiBvwPy12pUQW7iKYAAAAASUVORK5CYII=\n", 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" ] }, "metadata": { "needs_background": "light" }, "output_type": "display_data" } ], "source": [ "sorted_data['inc'][-200:].plot()" ] }, { "cell_type": "code", "execution_count": 16, "metadata": {}, "outputs": [], "source": [ "first_september_week = [pd.Period(pd.Timestamp(y, 9, 1), 'W')\n", " for y in range(1985,\n", " sorted_data.index[-1].year)]" ] }, { "cell_type": "code", "execution_count": 19, "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": 20, "metadata": {}, "outputs": [ { "data": { "text/plain": [ "" ] }, "execution_count": 20, "metadata": {}, "output_type": "execute_result" }, { "data": { "image/png": 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\n", "text/plain": [ "
" ] }, "metadata": { "needs_background": "light" }, "output_type": "display_data" } ], "source": [ "yearly_incidence.plot(style='*')" ] }, { "cell_type": "code", "execution_count": 21, "metadata": {}, "outputs": [ { "data": { "text/plain": [ "1986 0\n", "1987 0\n", "1988 0\n", "1989 0\n", "1990 0\n", "2020 221186\n", "2023 366227\n", "2021 376290\n", "2024 479258\n", "2002 516689\n", "2018 542312\n", "2017 551041\n", "1991 553090\n", "1996 564901\n", "2019 584066\n", "2015 604382\n", "2000 617597\n", "2001 619041\n", "2012 624573\n", "2005 628464\n", "2006 632833\n", "2022 641397\n", "2011 642368\n", "1993 643387\n", "1995 652478\n", "1994 661409\n", "1998 677775\n", "1997 683434\n", "2014 685769\n", "2013 698332\n", "2007 717352\n", "2008 749478\n", "1999 756456\n", "2003 758363\n", "2004 777388\n", "2016 782114\n", "2010 829911\n", "1992 832939\n", "2009 842373\n", "dtype: int64" ] }, "execution_count": 21, "metadata": {}, "output_type": "execute_result" } ], "source": [ "yearly_incidence.sort_values()" ] }, { "cell_type": "code", "execution_count": 22, "metadata": {}, "outputs": [ { "data": { "text/plain": [ "" ] }, "execution_count": 22, "metadata": {}, "output_type": "execute_result" }, { "data": { "image/png": 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\n", 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