diff --git a/module3/exo1/analyse-syndrome-grippal.ipynb b/module3/exo1/analyse-syndrome-grippal.ipynb index 4933e016e5d0241312815f3bee24f6b3e7bfad67..fe822c9372df8ba927bc8a8d8142d50d138a4563 100644 --- a/module3/exo1/analyse-syndrome-grippal.ipynb +++ b/module3/exo1/analyse-syndrome-grippal.ipynb @@ -9,14 +9,16 @@ }, { "cell_type": "code", - "execution_count": null, + "execution_count": 27, "metadata": {}, "outputs": [], "source": [ "%matplotlib inline\n", "import matplotlib.pyplot as plt\n", "import pandas as pd\n", - "import isoweek" + "import isoweek\n", + "import requests\n", + "import os" ] }, { @@ -28,13 +30,25 @@ }, { "cell_type": "code", - "execution_count": null, - "metadata": { - "collapsed": true - }, + "execution_count": 28, + "metadata": {}, "outputs": [], "source": [ - "data_url = \"http://www.sentiweb.fr/datasets/incidence-PAY-3.csv\"" + "file_path='incidence-PAY-3.csv'\n", + "if not os.path.isfile(file_path):\n", + " data_url = \"http://www.sentiweb.fr/datasets/incidence-PAY-3.csv\"\n", + " r = requests.get(data_url, allow_redirects=True)\n", + " with open(file_path, 'wb') as f:\n", + " f.write(r.content)" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "Je vérifie l'existence du fichier local *incidence-PAY-3.csv*.\n", + "S'écris le contenu de la variable r dans le fichier *incidence-PAY-3.csv*\n", + "Je récupère le contenu du fichier qui est stocké à l'URL *data_url*" ] }, { @@ -61,11 +75,978 @@ }, { "cell_type": "code", - "execution_count": null, + "execution_count": 29, "metadata": {}, - "outputs": [], + "outputs": [ + { + "data": { + "text/html": [ + "
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weekindicatorincinc_lowinc_upinc100inc100_lowinc100_upgeo_inseegeo_name
020205332388117956.029806.03627.045.0FRFrance
120205231816613646.022686.02821.035.0FRFrance
220205132161917370.025868.03327.039.0FRFrance
320205031684513220.020470.02620.032.0FRFrance
42020493129399923.015955.02015.025.0FRFrance
520204831380410641.016967.02116.026.0FRFrance
620204731908515285.022885.02923.035.0FRFrance
720204632480120503.029099.03831.045.0FRFrance
820204534251636857.048175.06556.074.0FRFrance
920204434456738521.050613.06859.077.0FRFrance
1020204334373737523.049951.06657.075.0FRFrance
1120204233514529812.040478.05345.061.0FRFrance
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19202034360843090.09078.094.014.0FRFrance
20202033361063411.08801.095.013.0FRFrance
21202032359183330.08506.095.013.0FRFrance
22202031343512269.06433.074.010.0FRFrance
23202030381795442.010916.0128.016.0FRFrance
24202029386875860.011514.0139.017.0FRFrance
25202028383405701.010979.0139.017.0FRFrance
26202027340662406.05726.063.09.0FRFrance
27202026340392389.05689.063.09.0FRFrance
28202025328531488.04218.042.06.0FRFrance
29202024330581690.04426.053.07.0FRFrance
.................................
185819852132609619621.032571.04735.059.0FRFrance
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1888 rows × 10 columns

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6.0 FR France \n", + "29 7.0 FR France \n", + "... ... ... ... \n", + "1858 59.0 FR France \n", + "1859 64.0 FR France \n", + "1860 97.0 FR France \n", + "1861 93.0 FR France \n", + "1862 80.0 FR France \n", + "1863 116.0 FR France \n", + "1864 149.0 FR France \n", + "1865 281.0 FR France \n", + "1866 395.0 FR France \n", + "1867 485.0 FR France \n", + "1868 544.0 FR France \n", + "1869 689.0 FR France \n", + "1870 722.0 FR France \n", + "1871 762.0 FR France \n", + "1872 926.0 FR France \n", + "1873 1113.0 FR France \n", + "1874 1236.0 FR France \n", + "1875 832.0 FR France \n", + "1876 459.0 FR France \n", + "1877 207.0 FR France \n", + "1878 190.0 FR France \n", + "1879 198.0 FR France \n", + "1880 224.0 FR France \n", + "1881 266.0 FR France \n", + "1882 219.0 FR France \n", + "1883 176.0 FR France \n", + "1884 163.0 FR France \n", + "1885 195.0 FR France \n", + "1886 308.0 FR France \n", + "1887 213.0 FR France \n", + "\n", + "[1888 rows x 10 columns]" + ] + }, + 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weekindicatorincinc_lowinc_upinc100inc100_lowinc100_upgeo_inseegeo_name
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weekindicatorincinc_lowinc_upinc100inc100_lowinc100_upgeo_inseegeo_name
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620204731908515285.022885.02923.035.0FRFrance
720204632480120503.029099.03831.045.0FRFrance
820204534251636857.048175.06556.074.0FRFrance
920204434456738521.050613.06859.077.0FRFrance
1020204334373737523.049951.06657.075.0FRFrance
1120204233514529812.040478.05345.061.0FRFrance
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21202032359183330.08506.095.013.0FRFrance
22202031343512269.06433.074.010.0FRFrance
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.................................
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1887 rows × 10 columns

\n", + "
" + ], + "text/plain": [ + " week indicator inc inc_low inc_up inc100 inc100_low \\\n", + "0 202053 3 23881 17956.0 29806.0 36 27.0 \n", + "1 202052 3 18166 13646.0 22686.0 28 21.0 \n", + "2 202051 3 21619 17370.0 25868.0 33 27.0 \n", + "3 202050 3 16845 13220.0 20470.0 26 20.0 \n", + "4 202049 3 12939 9923.0 15955.0 20 15.0 \n", + "5 202048 3 13804 10641.0 16967.0 21 16.0 \n", + "6 202047 3 19085 15285.0 22885.0 29 23.0 \n", + "7 202046 3 24801 20503.0 29099.0 38 31.0 \n", + "8 202045 3 42516 36857.0 48175.0 65 56.0 \n", + "9 202044 3 44567 38521.0 50613.0 68 59.0 \n", + "10 202043 3 43737 37523.0 49951.0 66 57.0 \n", + "11 202042 3 35145 29812.0 40478.0 53 45.0 \n", + "12 202041 3 27877 23206.0 32548.0 42 35.0 \n", + "13 202040 3 20443 16381.0 24505.0 31 25.0 \n", + "14 202039 3 19810 15900.0 23720.0 30 24.0 \n", + "15 202038 3 25562 21142.0 29982.0 39 32.0 \n", + "16 202037 3 18485 14649.0 22321.0 28 22.0 \n", + "17 202036 3 10390 7646.0 13134.0 16 12.0 \n", + "18 202035 3 9918 6842.0 12994.0 15 10.0 \n", + "19 202034 3 6084 3090.0 9078.0 9 4.0 \n", + "20 202033 3 6106 3411.0 8801.0 9 5.0 \n", + "21 202032 3 5918 3330.0 8506.0 9 5.0 \n", + "22 202031 3 4351 2269.0 6433.0 7 4.0 \n", + "23 202030 3 8179 5442.0 10916.0 12 8.0 \n", + "24 202029 3 8687 5860.0 11514.0 13 9.0 \n", + "25 202028 3 8340 5701.0 10979.0 13 9.0 \n", + "26 202027 3 4066 2406.0 5726.0 6 3.0 \n", + "27 202026 3 4039 2389.0 5689.0 6 3.0 \n", + "28 202025 3 2853 1488.0 4218.0 4 2.0 \n", + "29 202024 3 3058 1690.0 4426.0 5 3.0 \n", + "... ... ... ... ... ... ... ... \n", + "1858 198521 3 26096 19621.0 32571.0 47 35.0 \n", + "1859 198520 3 27896 20885.0 34907.0 51 38.0 \n", + "1860 198519 3 43154 32821.0 53487.0 78 59.0 \n", + "1861 198518 3 40555 29935.0 51175.0 74 55.0 \n", + "1862 198517 3 34053 24366.0 43740.0 62 44.0 \n", + "1863 198516 3 50362 36451.0 64273.0 91 66.0 \n", + "1864 198515 3 63881 45538.0 82224.0 116 83.0 \n", + "1865 198514 3 134545 114400.0 154690.0 244 207.0 \n", + "1866 198513 3 197206 176080.0 218332.0 357 319.0 \n", + "1867 198512 3 245240 223304.0 267176.0 445 405.0 \n", + "1868 198511 3 276205 252399.0 300011.0 501 458.0 \n", + "1869 198510 3 353231 326279.0 380183.0 640 591.0 \n", + "1870 198509 3 369895 341109.0 398681.0 670 618.0 \n", + "1871 198508 3 389886 359529.0 420243.0 707 652.0 \n", + "1872 198507 3 471852 432599.0 511105.0 855 784.0 \n", + "1873 198506 3 565825 518011.0 613639.0 1026 939.0 \n", + "1874 198505 3 637302 592795.0 681809.0 1155 1074.0 \n", + "1875 198504 3 424937 390794.0 459080.0 770 708.0 \n", + "1876 198503 3 213901 174689.0 253113.0 388 317.0 \n", + "1877 198502 3 97586 80949.0 114223.0 177 147.0 \n", + "1878 198501 3 85489 65918.0 105060.0 155 120.0 \n", + "1879 198452 3 84830 60602.0 109058.0 154 110.0 \n", + "1880 198451 3 101726 80242.0 123210.0 185 146.0 \n", + "1881 198450 3 123680 101401.0 145959.0 225 184.0 \n", + "1882 198449 3 101073 81684.0 120462.0 184 149.0 \n", + "1883 198448 3 78620 60634.0 96606.0 143 110.0 \n", + "1884 198447 3 72029 54274.0 89784.0 131 99.0 \n", + "1885 198446 3 87330 67686.0 106974.0 159 123.0 \n", + "1886 198445 3 135223 101414.0 169032.0 246 184.0 \n", + "1887 198444 3 68422 20056.0 116788.0 125 37.0 \n", + "\n", + " inc100_up geo_insee geo_name \n", + "0 45.0 FR France \n", + "1 35.0 FR France \n", + "2 39.0 FR France \n", + "3 32.0 FR France \n", + "4 25.0 FR France \n", + "5 26.0 FR France \n", + "6 35.0 FR France \n", + "7 45.0 FR France \n", + "8 74.0 FR France \n", + "9 77.0 FR France \n", + "10 75.0 FR France \n", + "11 61.0 FR France \n", + "12 49.0 FR France \n", + "13 37.0 FR France \n", + "14 36.0 FR France \n", + "15 46.0 FR France \n", + "16 34.0 FR France \n", + "17 20.0 FR France \n", + "18 20.0 FR France \n", + "19 14.0 FR France \n", + "20 13.0 FR France \n", + "21 13.0 FR France \n", + "22 10.0 FR France \n", + "23 16.0 FR France \n", + "24 17.0 FR France \n", + "25 17.0 FR France \n", + "26 9.0 FR France \n", + "27 9.0 FR France \n", + "28 6.0 FR France \n", + "29 7.0 FR France \n", + "... ... ... ... \n", + "1858 59.0 FR France \n", + "1859 64.0 FR France \n", + "1860 97.0 FR France \n", + "1861 93.0 FR France \n", + "1862 80.0 FR France \n", + "1863 116.0 FR France \n", + "1864 149.0 FR France \n", + "1865 281.0 FR France \n", + "1866 395.0 FR France \n", + "1867 485.0 FR France \n", + "1868 544.0 FR France \n", + "1869 689.0 FR France \n", + "1870 722.0 FR France \n", + "1871 762.0 FR France \n", + "1872 926.0 FR France \n", + "1873 1113.0 FR France \n", + "1874 1236.0 FR France \n", + "1875 832.0 FR France \n", + "1876 459.0 FR France \n", + "1877 207.0 FR France \n", + "1878 190.0 FR France \n", + "1879 198.0 FR France \n", + "1880 224.0 FR France \n", + "1881 266.0 FR France \n", + "1882 219.0 FR France \n", + "1883 176.0 FR France \n", + "1884 163.0 FR France \n", + "1885 195.0 FR France \n", + "1886 308.0 FR France \n", + "1887 213.0 FR France \n", + "\n", + "[1887 rows x 10 columns]" + ] + }, + "execution_count": 31, + "metadata": {}, + "output_type": "execute_result" + } + ], "source": [ "data = raw_data.dropna().copy()\n", "data" @@ -122,7 +2134,7 @@ }, { "cell_type": "code", - "execution_count": null, + "execution_count": 32, "metadata": {}, "outputs": [], "source": [ @@ -152,10 +2164,8 @@ }, { "cell_type": "code", - "execution_count": null, - "metadata": { - "collapsed": true - }, + "execution_count": 33, + "metadata": {}, "outputs": [], "source": [ "sorted_data = data.set_index('period').sort_index()" @@ -179,9 +2189,17 @@ }, { "cell_type": "code", - "execution_count": null, + "execution_count": 34, "metadata": {}, - "outputs": [], + "outputs": [ + { + "name": "stdout", + "output_type": "stream", + "text": [ + "1989-05-01/1989-05-07 1989-05-15/1989-05-21\n" + ] + } + ], "source": [ "periods = sorted_data.index\n", "for p1, p2 in zip(periods[:-1], periods[1:]):\n", @@ -199,9 +2217,32 @@ }, { "cell_type": "code", - "execution_count": null, + "execution_count": 35, "metadata": {}, - "outputs": [], + "outputs": [ + { + "data": { + "text/plain": [ + "" + ] + }, + "execution_count": 35, + "metadata": {}, + "output_type": "execute_result" + }, + { + "data": { + "image/png": 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ybOs+bNw9UO9qMHWABUoZ1C3KK0rYcPVqEaLs4P3gA/Owo7zqzw2PvoE/vrm7buVHDbSo93jn4pufwTu//UR9K8HUBRYoZVD/sOEQJKCKlXRsSsNKgl/glifX4rJb/1i38tX7FqR1JqCpmMMcFihlUD8fSoQdGxt8teF6j7KTRE6+b2GbhM2F8ZDLFzD16odw0+9X17sqDQMLlDKoV5RXmGLVKLVeoc06jdKtFQoCm/ck1+afy1sPk1cPqC1KkN+0aFWda9I4sEApg0IDmLwafBpKTTWU7y5ajbNueAKbepMpVIalQAl67VSbsdyJB9WODfC5JwYWKGVQNw0lRJqiA7eeJq/aLl9faXl/WGVta7C7f7iifKpFLm/dXyrAR8L9Xryw6TA6LFDKoBGc8kmoYRzzUML4mSuVX1kZlpsJ6rHrhDK9BAUoFCL6Whh/GuAzTxwsUMqgfkuvBKdRnU7D74dSw/Jy8oE2pav3OWzY3R84j8SMFBQN0MEdSn6eJM83SyosUMqg/kuvBNPoa3kVIqgolXZiWWlSyqRLC4urg3zXt5/EvBufKuvaom/Evy6qzSqpcjZfwP0vbS7bT9gAn0ZoDqV7qRX12Naj4WmMsOEkUH4tIu39UnYpFsPS5JXyMCkloVMRrr/GdDHU9dan3sS3H1sJIuBDp04OvsBdh8qrkBgOJW2rVrCGEgFlYvcTKPe8uBEvb9xTlfIbZoOtGhu9Kvah2FFUpRklwexh+0ZCaiiVdOu7+qwVi/cM+C9EaSJJnfDFNz9d0VL+7EOJDguUCKSlRPETKF+8fyk+9IPnalUlIw2/llcEp3yl93pwOO8o01GPinKOB1WHwLDhGMpKVeiDS0J7KZZt3Y+v/Ob1sq9PknBsFFigREA5vOvVWdfSUR0HjbKn/EBW7URdWmoS+pTifAj/yogYfCiVLt+ShPaKC9ZQosMCJQJhTF61IMxHW995KLXNo9LyimtllZ5LgslLhIzyirOq1brtvsFsw6xEzBpKdFigRECZA+oW5RWi3ETs2CippApRFoeMawJaEtrMk9BRXo7kZWFPjC0zl6Dr3v+9xlmJOKmvQ5JhgRIBJVCSvPSKLVAafcfGOgQgeLVZEoRMWB9KHNpUpQOSoOvWN4h2AiRDO200WKBEgOps8gpTqr3BVh0Xh1Qj6UrM8VH2VInraXi1WRI6lfA+lMrLSsJ2AUkhwePGxMICJQKpejvlazg3Iw4qqkMkDSUmk5eXhhJLzpVhT1gMmy6WtdTKvC4JDYaY2iApN9NAsECJgHLK5wxDlyS8gPby9YfR0itxjSQ9w4YT8ExFyY/qEXV3SDdJWVCR9+SpDyxQIhA0D6XaKnKkzq2eExtr/TFXUaAkweyhnnvQICGsJuNLhT64pHTCcVQjCebORoMFSgSC5qHUO5wYKI4wk/AxVDK6t30oEdJWimc+9W/Gmi69QhV5vhLRXADief8T8Ak1HCxQIlCch+J9vtqdeONMbKy8dCWbQ4UNV9PklYQuUrVFQLI4Foe0iyw7yivchdU2JcbxLSZhUNZosECJQFDYsMm3EhdRlq9v/KVXwmcS15165ZMApTO0UIujqrXaEqbar2cc+Sfh2TcaLFAiEDSxMUkmryQMriqpQiRtLKab9RLCiXDK29paULrKo7yK81DK9KGETFftycHxZF//Z99osECJQNA8lGpPeAyVe4UdQhzU+luuZpRX3I+0nOdSXCjTX6IkYemVsNdVe/AVh6kyAePDhqNigUJEaSJ6hYh+J/8/mogWEtFq+XeUlvYaIlpDRCuJ6ALt+GwiWirP3UzSbkNELUR0jzz+PBFN1a6ZL8tYTUTzK72PMNgaSp1MXlGoZ01iMXlF2vulekavuH0o5bwiYTcbi2fplUpXhwyZrMovaByfYgKU04YjDg3l8wBWaP+/GsAiIcQMAIvk/0FEMwFcBuAEABcC+AERpeU1twC4EsAM+e9CefwKAHuEENMB3AjgBpnXaADXAjgNwFwA1+qCq1oEhw1XW40Pzt+O8kqAcKtoteGQjmgrcfnl6Hg2WczNWM47EvaKOLTS4tI95RFWAFff5MVO+XpQkUAhoskALgbwE+3wJQDulL/vBHCpdvxuIcSQEGIdgDUA5hLRBABdQojFwnoL7nJdo/K6D8B5Unu5AMBCIUSvEGIPgIUoCqGqETRpMAk+FEVdNZQYSq/HlJvamLzKvyY4yktdEL0MRcUTG0NeV+3OOo7nxgIlOpVqKN8F8G8A9EDa8UKIbQAg/46TxycB2KSl2yyPTZK/3ccd1wghcgD2ARjjk1dVCTJ5JUGgqCivr/12ub21bb2oZJRYXG04TDllF+PKpxYmr3LyCxvlFV9dy19tOBxV9zfyPJS6ULZAIaL3AdgphHgp7CUex4TP8XKvcRZKdCURLSGiJbt27QpVURP2PJQ6aShRX/Bn1lR2v+USjw8lStq4orw88k6QhhI2XUVVtndsLO/ysB159VeVSEYecdA3mMWNC1chZ5oAlyAq0VDOBPABIloP4G4A5xLRzwDskGYsyL87ZfrNAKZo108GsFUen+xx3HENEWUAdAPo9cmrBCHErUKIOUKIOT09PeXdqSRoHkrd9knRSMJasXG0QlKWr9c1inrZ5e3RVWDYcPT6uCnuh1IeocOGqyxRDqWJjTc8+gZuWrQaDy3dVu+qBFK2QBFCXCOEmCyEmArL2f64EOKvATwIQEVdzQfwgPz9IIDLZOTWNFjO9xekWayPiE6X/pHLXdeovD4iyxAAHgMwj4hGSWf8PHmsqpBt8vI+3wihkI2Dn5LqJLYPP0BDiWeyXPlhw9XI2w1V6kQJSZJWlahmHnEwMGRtUZ3NJ6VGZjJVyPNbAO4loisAbATwUQAQQiwjonsBLAeQA3CVEEJt5v0ZAHcAaAPwiPwHALcB+CkRrYGlmVwm8+olousAvCjTfV0I0VuFe3GgvrV6T2z0K0UfxZYbArpi234czOZx6pHlBc7V2n4dV98UZPIqCIFUhTpgOa9IcV2zgHko5VTIRZh3ZveBIbQ3Z9DWnC45lxynvFOzLGefl6RoKI1ELAJFCPEkgCfl790AzjOkux7A9R7HlwCY5XF8EFIgeZxbAGBBuXUuB/V65Q27VyXBh1LxPAIA773paQDA+m9dXHFe5VKPTznI5BXP3IbomRTXNQtKJ8ouQxEmbHj2N36P444YgUe/8M6Sc6HDhqvuRNF+inDBHSVZsECJDM+Uj4B6wepl8gpDkjbcq6Q16uJD8QwbFp6/4ywj+BqloQQljJ63m7AWrze291VUh1pObCz3uSVFnoQ3/tYfFihlMJTLex6v+mStqBfU6Q2M09cQbgvguKK8vDQUrZw6+VCi5h2P/6C6YcO1dMqX+10mYHzYcLBAiYB6L/uHcp7nqx9bb/0NLSfq9EHEMrFR/g21H0r1fPIOs0c8kUPRrykuDln9tbwq1XCT4kPRcy+3KPahRIcFSgRUR9k/7K2h1Gotr4Z5zSuoaBT7dTWjvOIwnTiKKCtsONw1ceyHQpXOQ4lY12qhD+4a3eSlSJI52wQLlAioF2zQIFCqv9pwcP7kDPOqC7X+EOMqrhZO+Uo0lMB00bOOPa/wGkqZBZRBuWUlxSmflHqEgQVKBNRjNWkiSZjYmARqPUs5trBhj2CLRExsDGnqtPdDqeJaakG+jyT6UMrVUNiHEh0WKBEoRnl5v2lJ2LFR7/TqrSFXFOVVhw2PvX0oxd+xhA1Xck0tZsoHlJGNafmPWobYizKrfHhNJI4HFigRUK9XvTbYahRiiTKyHdHh01ZeZpDJKwYNpYx3xI54C0xn/Y1nLbXyBk3h95SPXKVIHEoaih2gUu8RYghYoERBPtkkrzacJCpbbdj6G2aiZlyt7vX44nfKl3NR2GTx1c9Uz6AFCsPeX7XNw3E8N47yig4LlAgUfSj1mikfnL+epJzlJqKWF+d15eYR33fvr6HUbS0vtfRKwPOMY8fGIOIy61a/s44hmILlSWRYoEQgyIcS16hLCIEd+wfLuxZ6B1hZfcqOjqmo1Oh5hOmcfvDkGtz74ibfNF7ZxD8PpXynfHC6+ExyprxyAQsUho7yqrpTvvi73HZJmoYSx7JK1YYFSgQCo7xi+kjuXbIJp/3HIizdvM9ZfiinfCxVAFD5/VR0dcxRXv/56Er82/1/8k0TbPIKX6coZQQR1oZut0MF9bSzMOQR5JQPPw8lQqXKII5giqRYsBMm13xhgRIB9WCr7UN5/k1r4eSVOwzrJfmg16BSk1fZI7QYncK1XHrFcx6KPkEuhudb1sTGGvpQgp55sFM+XDl+38oL63px6nULsf6t/nCZeRCHUz5p8z/YKX+IoT7YMBpKJS9jJm29OW4HaJgc4/wIyv4QqzgPotK0UfOJey2v8nzyIUf9hWjpPcsK8MMEOuVDluP3bj28dBt6+4fxzJq3QubmUY9YnPLh0n3z4RW44o4XgxNWSMLkmyfV2A/lkCVIQ3E7cL1GFNv2HcTAcB7H9HQay0mnLDnvFlyhTF7a70oHNPVU+etRtlfHkyQfSuDExujV8ShL+VC8z8e1yZNfO6hzlWj8cQRThB2c/eipN8srAMBPnn4T63f34xuXvj24Pg0QJcAaSgTU+2WK8tIFgOmDOeObj+O8//6DbzmZlNoZsgKDewyU+0HHOQ+ilotDehF32LDh1fHFXr4+MMrLXxiEKsv+W55ZN2wn7JdPWr7/lUSUxaGh1KL7/sZDK/CzP24MlbYBtpRngVIOpk7BuSBd+fmbPqgwI5Q4P4KgzuGZ1W9h78BwVeoQ1AdE0RwqmWwX/1peZWgo8m8t9kMJEkrZAIkYtgp+zVAcUPmX9dyat7Da4GfUv5XynfLJ0AhULZJSHz9YoERAdUxh5qFU8vCbDD6UMDiWXqnQ5uU3ihwYzuGvb3sen/CxHccxUjaNyh1LawTkFVbT8t4PJR6/WDGP6l0Tx34oxYmN3rkM54ImNlauoaRCaih/+ZPn8Z4bn/I8p19arqadlCgvRSOsxMECJQLqcYZZyytIoPi9HCnZibqTRO2MKu3//N5fda+rPHbui2UgFaR1OJL6p/XrmIRDYPhXw6+Uq+//Ex5eus23HkC5PhRl8gpIFzlncx6mJgsSKGHHQH7toDSUn4c0BXkhYhgIxJFHHKiyG0CesECJQtGH4v1ko5hHKrMP+3SQZedait9HL+yIIjMVRRsFnI8SFrpm5wGffPzLDFvO3S9uwt///GXfegTlYSLsFXHsKV/UcsrTUEzau6kcL1ozaQDAlr0HQ+Xlnb/37yjEMZclTtjkdYihPrK8IdJFH50Faih+58lZXrH8YPRsKzV5+dVRdRyekVE1CBvWzweNit/3vWeM54JMWg4zZgxO0XJaplit6u/YqCpo1FBkYystwk3YNvJ7Zs0Zq1uaPs4cCRlM5ebnOOayrN7Rh9/9aWtZ1/rVJ6lw2HAEgjQU3YkYtGS2n4ZiXGIhhI08ztBCP9uzqn+QmahcAh3t2n2GHRUHlRM0DyWOCXLl7dgYrZxKmj9Iy1Eaipor5UZ/FkIIhw8sbCBFHEsYxfPcouVRKAjb/6NQPp73nTixrDq48086rKFEIMiHEkVDCeMoNGXhl7VDQ6lwJopfOX4CJcz1Ycs2aVmOj70CzcHpI/HQtmKZz1D8Xd6OjfH5UFbt6MOS9b0+ZTn/ulEaStpQGT8BHbaDDlpPLAx651tuNlHnsvjd02DWe5fXKMQ0BaiqsECJQFFDMUR5aS9U0CjLT6AYO1H/6llpYnzp/OqozH6enXAMZUfJI+kaisN0UoZEsYVrUDkhhPy8G5/CR3642JyHbfLyzkSVYYq+0xePdOcR1oQUx6rJ+rVxzEMJpaH4JOkbzJVVB0d9GsDkxQIlEtYDLQjvhxtl3SdfgaJKM7xAtXqxwvhQPJNErN/7v/cMfvGCM6In6B7j2vgqyHkbppzguvqXEURYM2Y8gtxfKAXVP+9oL/O1fj6UfAwSJY75QyJiHr5mvEqCcGLIo1awQImA/r54+UD0Y5VoKGHKN6cpJqquU14Epgl7h0u37MM1v1oapWrOZ1GBLcChoQTsh2J6ZEGPstItBYLMf2HrEaUs872Gf69Lg0rCDQI/q3DHAAAgAElEQVTsbSIqspkWf8axllc4DSV4AGa81u/hBTyTJMECJQL68/QSCPoLFdTJ+b1gquMosUGr0WPIOlaqyPiNInN5c11EyY/oBEZ5ab8r0VD04ImgAAOTMAhejqT42y/po69vw4se/o2wdxdFWJk6sKJjP+C8oSx9UOXrQ/Ezp8qElQ0U9HLLNHnpeYSwqvo926B3JIzwbIQoLxYoEdBfTK8XJMpMeb8Bi3Kmu3Ows6/RexVGhffthEPtB2/ouAKWr3c+i+ByTASFDYfTUMKb5/zMV5/+2cv4qId/o+hDCR82HGRyNS2hYlubytTG/JzhYc1Q6pxfJxx0f3EvvRKmM3fXN6i/8LvWsz4NoKKwQImA/ji9TF76SxH0goTRUErKD2XyCs4nLP5hw+b6RxlJBZmRTJ2ofl1sTvmAckz3FZeGYrw+tA+lmC5ozS3T6F/lYXTK2xqMIV+fQZXDhxIiyssvTdCI3vHcyuyIw4Q5+4WED2sjneD+IIyGEpik7rBAiYD+vlSsoYTodMszecX31vlV0X85E7sygZg+NDt81ZRJiI4+DE7TiNf54Gca3LlFG+m6KceHErTMvGnnRbvd49BQSvIWnuncqHfCN8owoCKxOOUd+XmnyebN5eirCgQJDNNkaasewQI2KbBAiYAQwndpeUfYcEUTG2V5bqem/bGH6MwDWLWjD88GbGDk9wL72beL8iS6maCYR3iTRiW29qBRaJh5KMHmF+/84kbPOhuwRIpJ4ASFDUdZN61EQwk5T0vl4bc4auDOknn9uZXX5k7znXceunbsrlMUi4WfRmlvnHYoCxQimkJETxDRCiJaRkSfl8dHE9FCIlot/47SrrmGiNYQ0UoiukA7PpuIlspzN5MMcieiFiK6Rx5/noimatfMl2WsJqL55d5HFASKM4Q9BUo+/AtUzsTGMC+UnsJvQDvvxqfwVz953jevcsMggzZpcuRj7LhkHQzfmdOMVE0NJbicQJOX3pGWYZ2z534EpdPqF7T3u9lM6K8FBy1v7zevxzngMrdZmA22gkb8ujAq34fi/VsnmzNrXdmY+oN8iPZICpVoKDkA/yyEOB7A6QCuIqKZAK4GsEgIMQPAIvl/yHOXATgBwIUAfkBEaZnXLQCuBDBD/rtQHr8CwB4hxHQANwK4QeY1GsC1AE4DMBfAtbrgqhoCaEqr3RRLP8iwH0zQeXXG3YEVzUA+VYzxnfMbefv5LcLUU1H2Jl6OPMrKAkCwOSqM6aTqJi/5N2iDLZ3hIIFi0lACRsNBj8tPM3Buke2TRwgfSnDQQXCbL9+6H1Ovfgivb9nned5p8vLOQ1/A0l0l/X4DBWCIAZpfFr96eTOWb93vW0YtKFugCCG2CSFelr/7AKwAMAnAJQDulMnuBHCp/H0JgLuFEENCiHUA1gCYS0QTAHQJIRYLq+Xucl2j8roPwHlSe7kAwEIhRK8QYg+AhSgKoapREMIWKJ5hwzHNQynYL5DLZKA6at+stZMVz0Mxn/M3ealRbHDnadxOueCfR8EhvOs7Uz6oeGfHFKFyPvXyroeuofhfZBI4YTUQ446OPu3piHoK45SPSUMxlbVoxQ4AwKOvb/c8H8Yp/81HVhjT+JnD3Pj5UPIB3wIA/NO9r+Gim5/2LaMWxOJDkaaoUwA8D2C8EGIbYAkdAONkskkANmmXbZbHJsnf7uOOa4QQOQD7AIzxycurblcS0RIiWrJr167yblBSEP7b8zomNlai4hacfxVBETiA6yOuUFsp94OOQ0NRnUCYDbbCajnjRrT45uN1T2EWdoyioZTzUMqZKR9o8jKtmG0YzCiirABR4lMIqanZPpQKwobD+FCa5KrGprYKs5aX7nh3v4cODSUoSMJnVKIuPdRNXgAAIuoEcD+ALwgh/HQur55B+Bwv9xrnQSFuFULMEULM6enp8aleMAL+GkrYDwYIq+IK1/HgvON85fxGRGFMdmFG1kEdV9A8FSB4tDq2s8VRL1P5XpqOczkd7/wDnfIOLcc3aeD1fuj3ErRvSVCUV1A4twmnU955zrkVQJgRuTld0DPXO2jTc1PfsklbC+OnO3J0u2d6IJoPZSjrZ0JW/YFvFomgIoFCRE2whMnPhRC/kod3SDMW5N+d8vhmAFO0yycD2CqPT/Y47riGiDIAugH0+uRVVQqiuFeD1wvtMHkFhTWW4ZQUhuNGKp2H4juKjGceinErAHWvAU77MOX5ze7Wi/d8piHKCZ6HEjzQiGPTND2LQB+Kqd21ztyL4Am72qjeVXP9lQm1lhfMzz9wXofPIpUKtdW2WUPx/q0zvqvVWE6Y+1AczJoXj1T5HNIz5aUv4zYAK4QQ39FOPQhgvvw9H8AD2vHLZOTWNFjO9xekWayPiE6XeV7uukbl9REAj0s/y2MA5hHRKOmMnyePVZWgsOFcyBGYO60bdapEoGjna7FwpF8dfX0oEapgaif1jZuqEGSqcuTlI4iDlsuJxynv/duRh989hGxQ/dmXq6EE7YdSDCv2ztdv6ZWwwQlhwm0Dw3BDRHkpc2oY4Wmqb99gtlgnHx9KkJ/v4HDwAK3cAU0tqWSDrTMBfBzAUiJ6VR77EoBvAbiXiK4AsBHARwFACLGMiO4FsBxWhNhVQgi1ScBnANwBoA3AI/IfYAmsnxLRGliayWUyr14iug7AizLd14UQ5k0eYqIgENopH7aT8zxnGJG4OzevPY7ifLXCmCUqxeiUVx9RwHm/NO7zXsn0jtNbQxGeab3yNxFmcUhnR+zcmCpsU+vJAqOgggSKqYwggeMjUML7UIInBAYJcX3/kTgGWaY8+oZyxjRRfCj7NcHkpmD7VL3zCPKX1ZKyBYoQ4hmYjSrnGa65HsD1HseXAJjlcXwQUiB5nFsAYEHY+saBFeVl3bLn0isho1iAgJmxRpOXdn1BIO2xDWucTnm/SKEwPqAwmPIpGISqfd7h+/Avw8/3VHC0qUcoeME7rSNNJA0lWKDkCsX3DAgfNVeI8P4FhQ0HtXsYDcWdx8HhvPGcjt7mpu8kSGAezOpleacJu7+MXx45n5ny2RBmt9amFAazBazdecBcjwhtXm94pnwERICGki8UTWKB0TA+H1TRrOASKI403tfHafJ6bfNe4zk/FV6/9SidoCP/AH+RU7gGLA1uj6r9y/deny049DOKv8xUVT3M1d3Zh32k7gGHH6ZRbT6g8zKZY4vnNQ3Fde7fH3hdq5+5bnqbm74Tt0bnRjchBfrYDMej+s98o7wM7aX6k/5h846Oefv9NbRFgjQUFighUQ8zY2soXqPZCPNU/MxJAU55v+tjVFBwy5Nrjeccoy8fTSqoMwyeh+J9naPzDNIGfWzQTkexl0DR0hrNPL7FOzDVVO9w3CGkwvXXRJgO0C7DtDhkoA/FvyPP+bwXa7RRuG8EoXbKuDtqgPbg1FDKG3w5Viw2DQR8BhxOH4r/wOjgsNkpHyTEg+Yc1RIWKCFRz1IJDK8XLK+ZKrxeYrdZw0TR5OU+rpVl7Gm90weVFZW8bwcY3vQSNA8ljMkrSOU3aXzu8r0+TH20bLqVOGbK6x1x2RqK3u6Ba8n5d9RGR3XAoMivLVKaidZ/HlZwR+wc/Zfey1AuWKCEfW/88vCb/R8luMBPQ/HzAQKVrbYdNyxQQqJeKN+lVwoCzZm0PO8xGg7pSDbZsfX/GjdIAnDi5G5j3m7Kda47hKOrA4wyUjZ/aPJvCIESPA/E/EEO54sfsqcPJYQwiLJ8fZhFBt0mjKBteb3KiRJWq6MuM86ED/AphTERAgEh6T7C1et6r3sdzhXQbFsL/Msxa8FmYWHn4SM0HPcRMHA66CdQAgZXlSyOGjcsUEKinmWT3+KQQqAl4+9jUfiNjkwmr0LAR2TVsxghFGaGdbkOPb3jKLHHh/gQ7XwCooVM1dMPh9ZQPNINBSwxHsYpP5Q1dwbWdbpQ8k6jdwpZd6KQjyjK9glBS6+YBr1BAsMvbFh18F7nvOpglRdGQ/F+ri1NKWM9gRB7xoRoT7/5LmFWzlBCq9/H5BU0D4Wd8g2IepiZtP/ERj+Tl2O066ehKIHi45Q3TvgDoCwLYUwl5U6W0s1DblOR/r+yNRS7Y/P/EP3SuMvwqovf0hnWseAR918Grtqs/w7uFNwaim2GCpAskTZ4M2oo/mUFdbJ+69l9eLY1f7k5kwq9rE+YiY1ekWDDuQLamtIldXKUEzCyDyOgnT4U9/Uhwp/l8SdXmpeFUkWb2ixJTvlK5qEcNmzqHcCfNlsrkjbbPhTv0Vlzxqxm50OowIAW5urj7PbfQjg85Zq8nL4Hl4lGeKeLUn5w2LCWh4/Qcs5SLz3v0FA8fSjeeUUjhIbio/GFHYFG0VCCfCimIoO0LdOo/PfLd9hBHl2tmVgnNnq1z3CugPbmtLGe+nVhBI4pD782D5roLIRw5JvLF+wBq6MMO1DCuw5JcsqzQAnBRTc9bU9gUmHBpi2Am3wETth5KqYRdZjVWoXQZgAbSygtS6c5k8JwroARLebXI+cjUMKYeOzzgU750ol+7jL8V262/qZThHxBlOSlNJQUeXeyUe4lqA4AjL1CzkfjU/WKYj4MDhv2F9TmEFX/MvTnqWt/v35li/2biEILFKMPJUDoDOcLaJUaijH0WL63JtOXMyDDrLGpd8v9Lgf5UHQzejYv0DswjHEjWkvSBQ2u2CnfYOizYdUIwnuSnBY2HGQO8FFT1QtSutqwd17ONKJiDUV9PK3N6ZJzxev0EbVL8HnkZSLIFGDlUXo+rBaknpOaBOpOqjq9juaMZz5RliA34dAsA0bLQGknajuPA8oJE5au2sG8OKT/aNi5PL23lq7Qtb827V1KE/lq2PmCsM22QSZRwPtehnJ5W6AErU5gElp+C13qdbWtFq40Tm3NHPAxdUwHAODAoLcfxbS2nyJJGgoLlIgEreXlt3ikU0Mxl6FecF8NxehbAFL2GkXBL5qn4BOqHuav3ulDqcDkFSKKy7uO/qM/d/lNhuemnNNtzelAp3y5Fq8wYcMOAV2onslLvb/btI2hvMoqZyKf+zpdQ+nQBEqKAqK8CgItGX/tIsh8PJwroLXJHCADFN/bcHNdzBqb8pu6vzfHniyGaQYA0CEtAQcNwR1Bk031cuq9TTALlIiYtgAWQuDNXf3FpVk83qB8wIjFna40yktL4+OUVxadMK+WVzXUxxOmowY8BEoIn4EijEnD62N2+pPMhdhmBUP0ner02pvTRqe8GoGWvTd5iIGALqBLNZSQJi9ttBzkp92+f9DzeJA2FCRQ9LrrkWRtzUXzaSrlb/IqFIQdoWX6TvIGwaUfs53yxo7YOmEa4YdZOiWv+01dabIB37tK3qkEiiF0OGg5nKC5VLWEBUpEmgwmr4XLrd3fnl2zG4C3Gh42bDhrGCXq/zMumljwXuPLhHt0JoSwX3S/KJicz0usVzuoEw61dLiP0HPXxZSu2TB/SHVGbc0ZwzMrDiLK9aGE0dicfgNvDeWtA0O+5eRFcbQcpPkdGPI2r6g2COOEHvLoyE0dfbtDQ6GA7aWLgjHMgMPruVlOeaujNpWlJj+aNPEwk1pz2oCjxOSlL6fjY7HoaLHaxqShBM1DyQa0RS1hgRKRosnLeXx3/7Dj/96zrrURj+/oX/lQ3BqKvxlIpbEFiqEIv7Wl9Gz9nH1+81CCIqt0jAIliobi5+BVAiXj3UGpUXSHQUMpCG19Ns96BEuZMCsk6O3gnoei13lT74CxnHxB2JqYeVsA63ifwV5v1y9EeLPXXBa9DXWBouZnATJAwqfZHKP+EALYqx7D+eI8FNO3oupneiZh5qE42tyVJuh7L9gCxRJ8AyYNJcCHoguuv7triWeaWsECJSJFgWL2GwCVaSiqAyl5gURpGmcdrDBEJVBMcwl0G737Y1MvL5ElFMNE+/gtFRK0LIlJRQ+KiAsb5SXkraoOyu2fGLI1FG8fiu4X8yrG3Zl5tZepkzWlKdVQiv/f5aOl6FGGpmALddi0Q2BQ2HDQveQ0h7q+/InetikKGAT4mJGK+RXL9qrHUFY3eZk0FBnlZRjUhNlTJVcwR3ZmA/w8Kr0yeQ2afCiyGmHChp9bu9s7UY1ggRIR0werd97pFBkiT7QXNEDlB7xMXv4jJpVl2rAPu8LPl6NONft0THodAS8fipZfgIpiXPVWu054JNGz7XVph850TpOX+36Gcnk0p1PIyNDPkusLApmU2YfiNvt4ffRB5hnreDGNe6Sqt7Wp01HlNPtEIerCT+/snfVQJi/v56aX79WRFwrCNjV5TRo997hxoUxeLT5LGFn19G/ToXzwxEZbQzEMag5mC7Y/0ujLKfhEecl6md4tt1PepKGYtgS3y9HqdkxPh2eaWsECJQS6T0I9fPc7qD/rpjR5vqTDATZV97kSk5f2TvtF2KhF+MKMaNzfot0B+0Sruct3j9KdK9J610Ghj8ZNZi7vUap1bExHMzb6mIFK7sdt8soV0JxJIZ1KeT6zXKGApozZ5KU6pe62JmNdQ20YpR13C0i9Xl5+C0VB+JuK9Odu0pSC1rcaGM7bWrpXXXIFYYcIO953+fu2+XOQDnLKC20JI6PD3KyhCCEsp3zAxEZbQzEkODicw6j2ZgDAoEGjy2kmL3ebq3xbDCsDqENBTvmgrRzUMztqTDs6W5s809QKFigh0H3c9uxb7eF+9/er8P9+Y+31QGRpMZ52XX3E5vNBZWU697cUZNNVL1wmQKA4TW8Fz3Mqht80oh7KFTsWP5NX8JpS3maBoCgvdXpcVyv2HTTvdqfaucmwZM5wroCWjKWheC/4CTSlzCYv1SmNam8qqbddVy1bY0euJXL74xxzYQIGIn5O+axWtkkwqbJMz+3gcB4j5b2aNZR0yflcwfJFEVn//HzHuXwhcECT89FQlOC0JzYGaijelTmYzdvP1WyOEmhr8g74yOULyKQI6RT5LharQqqNTvmCv5BX99/enAlcV67asEAJgf5CnnHMGOuY9nRvfepN+/d9nz4DTWnv0a5DoPh4JfcMWB1KqU3WP67draGYcC7z4SxD1VuZC0zmgP6hPEbK0ZtfZEmwD0W3U2tCRMvS06Epj41qb8JgtmA04ZTej7Ou2/cNYjhXQDpt/uhNkX1AcWFIFRbrvWCiOYDBXU8A6O0fMp7z2ys+G2DmsefcNKWNAuWtA2bzIQAMZHO2Nqav1GzXtSDsOrgX3lTRcumUfzBDvlDUUIyRTbqG4npH1bugTJmm4JJilJd3GQPDeYzuCNBQtDb3WjInkyZk0t4aijrW1pxGinzChuWlQeuadbakjYt+1goWKCFQD/Sitx+B8V3W0gj6C6KbxI7p6ZRLKZQ+2C//Zqn92285iG37BkvKAJwdk58KnQ5YesWvg1JlqElhpmUp+odzxZGqj2M6MGw4593ZOpeNL71OHVN1MGkpOddo1S00Fr2xE31DOTQZ7Nx6R+h1K8P26DDctgXmWdnFfNwmL90kM2gQnACQzQm0+My9UM+6szXjKYB/L0Pf3XXWsTSUZkd+OgUh7LZ2aCj5oi8qReS/9JBm8grjQ3HXQ/2/OZNCW1PaKAyKJi+DhqLdq6+G4qGRWXUsoCmVklFtPiZqIrQ3Z4w+FNNSTHo5gGWONwVb1AoWKBE4YWK3PQtdHwFmNIHS2pRGJpXyjF7a1FucnWxSw//niTX2b/cLlM0JbQkR84gnaB6Kn0Bxm7zMGkoOI+VItWQiXsFfGOg4J38ZfnuF60px2d1mffD7TQKlUIzi8qqrwuRDKRREcbkdj5tRH7AyjXiNMv3MM8V6WmnGjWjBlr3OSYe6Q9ivwxjOF3y3T1DCb0RLBtl86dpTy7ftt3/7+VDUc/f0ociZ401pcvkMC7ZgTpG38FY4w4aDI7DcbarKbcmk0NqcNnbUQU75geE8RiuBYgxiEGhrkkEIHtp+Jk1IE3laJNStpYjQ2pQ2mrxsM6TJ1yOv625rYg2lEXjX23oAAJ9+1zF2Z613cnoH2pxOoTmTKn3JtY9vZHuTsWNYvcPaJnVsZ4vnh+LXYRRcAsWkHegfh9tsoTsSgSCTl9WxDLj2cvDbI8JN1tHpeF/nubKzLGN0h1WHoHkVrRlvOzcAzJ022hiJY01cM09s/NOWfbIeVsfjNWEwaM6Efj/Tx43Ayu37S85NG2tF7/g55ZU/yBSWq9p6RKvqAJ15TZVltDWljXNuDmbz6G43C5S8nAfVnE453vFcQddQQoQNB0xs9BUoJRqKd0c9FMKHot7xQQ+hJITAcL5gt2fWQ9tPSw3Fb2JjOkVob057bgOcLwh7cGqSwQeHi4Eh7ENpAP7jQ2/HH/71HKRThBRZH4T+EvdrnUgqRZ4mLzVy/cr7ZmLvQBb3LNlUUs5gNo+Hlm4DYAkxt6qeKxTs0WG/R8dlL4QYYPLSR9ElGorLRORn8honzX/rd/c7zmUDTHOOtIbl44Oc8kowKHu+aRSqnkObwSTV2ZLBrInd0ofi5WSG3RF61eMrMhhjdEcLAO8F/vK2acPP5GUdnzqmHYPZgqOTy+YLOGpMOwBzuK9K15RO2avflpzPSVu77ADdgxrV8R57xAhPDWUwW4AQwEipFXoKlIIUKJmUY7CiHNSA1dGrurgpFKy5Mips2CR49Oftvo8hl0Ax+SbU/XpFeeULwp5t39qUwqDX8i62qak0qg0oamuZtHdUm9K+UilCW5O3JqV/n0YzZDZv36vfgKMWsEAJwaSRbThKrghKROhsyaB/qPjwVWjhv15wLAB4mrwOyNGHvkieu3O4/LYX7N8tTamS89mcQM8Iq+PqHSh1nrpnhZs6c33E5n4Biz4Us4lICIGBYSsCZvKotpJONGilYGd5uqbnLVy8/QHWQdW5mZYSKfGhuO5nMJtHa1MKzemUYaKeZapJkb9wVCYvL0FvC7WmtI9T3jrepQSk9ozyBYGOZm8h4C6nKZ0y+ihUB6/CVN3vl+p4O1rSnoMRpYmO77Lewb7BUjOjtZx7Ci2ZdGmUl9T0WjJpo2AsWdnA0OYDWrSZWwOxNZS0NHkZRu1qFXEvDUXda1tzCq0GLUd942oqQamGIk1eBg1FfXutmRTamr1NXoOu98CLwWwebU1pKcQLdV0gkgVKGYxobXJ0YCrM8zPvOgaAtRChu+PYI9MoJ591zPlBvrC+18rnnGPQmkmXjiBzeUwe1Y6u1gxel6YWHdUf2w51Q+elf2BuwVfiQ/EYtff2DyNfEBjb2YLOlkzJhxDF5KWP6tymIWX2uGvxeky9+iFHB6bqNdKnI9fTeZm8svmCHZXULm3t7o9xMFtASyaNpnTKd8vYdtmp/FCL+FMogTuqo9lo8lKBGMp8MqANWA4M5TCiNYNMinyd8gPDebQ3p615Hl4+FKWhtHibrNRzbG/23gBLzdIf1dGMlkwK+wZKBUqhIJAm6x3UNWzLKa8ESso4klYdqNKiTFFtA8M5dLU2ebaJrqG0N6U9zVVDubyvD+WgFr3XmvEWKPbCok1pubKEwSlP5OkLCqNJ6e1k+pQODlsCpSWTghD1XSCSBUoZtDWn8fRqa8tOvRNU4bojWjIlUUcqcmdMZzNu+atTHccA4J/uedX+PZS11iHSP5RvPrICG3YPoClNOO6ILqzd6TQzAcDD0lymzAVeH+Oe/mF84vYX7f+XRqa4fA4eL6daqfaIrla0eqjqTvu2/8s9oAkCd+SO0sZuf3Y9AGdIq6qXEtAmgaLybPHQUFQn0dqURkdLBrmCKOnohnJ5tEgNxmSmAYphyU+tKt3KVS0YOqaj2bM93zowhDues+5R7Y2xac+ArG8Bu/uHMa6r1eqIDRrK4rW7sbNvyDI5GeZ5uH0o7ntVz3FES8aznh+XGrQSCD/yEJ4Dwzm0N2cworWpZACgfHstPqaZ/VL4HiHNqSZH9QOvbsXG3gHZETvzUu9CW1PaOPJXQr6tyTvUVnXu7U3pEuGoKPpqrAHHkIfJy9ZQPNpTvX8tmTQ6WzOeWrZ+zDSYOJjNo605bWt1+v088OoWPLlyp+d11YAFShms2XkAO/YPYdWOPlx9/58AWEtKKKaMbsfqHX2OzlqtRjy6o9l24CqBks0X8CttR7sUAa2ZNLJ5YQusH/3B+ni37hvEyPamEoG1cfcAvv675QDgG3K5dtcBx/+HXS+pUvWV6cVLQ1m2xXIaj+9u9XR66uV6mUV03tjeZ/92ayjjpGlFoY+aVedoaygBdnLViTqXMZHaS3PaPu/+qIfUxEcPv9gfNOFxzrE9xXrq/p+CwKPLtgOwnr3XWlzb9xWjutS7oaLWdvcPQwgr+quzNYP9hvZUz37bvkFkDP6g78sIQpPJS5n/OloyJYEWALCrz6p7ymdpH6UldbVlHBM0reNWuS2ZlNGvoe67Z0QLiLyd4fq1rR4CY4WMVpsxfgQ6WrzbTAVxjO5o9v1OJo9qM5q81r1lDeqO6G7xHHDkCgVkUimjD0UJ1ZamFEa0eAuUN2SAxqSRbcbAk4NZazMxNZBUjvlCQeDzd7+Kv9EGkNWGBUoF9A/l8MuXNgMA3n/SBPv4nKNGoX84b48yN+8ZwE//uAEAMLajpShQpB/E7YNIpcheKdX90f/l3CNLRn8AsLOv2CnZUSceIy9VJ4X7JVVCTo0QvUbEC1fswBFdrXj7pG4rOiVbqqGoOvjNYv/Dql0OgaJ3Ytl8AeNd26HqH7XqBDpbMkiRt4ay+8AQPvOzlwEUnfe6vdzWUDIp20fhfhaDWWsr2aZ0qRnzOwtX2b/HdrbgSxcdZ92HVs9+7Z5OnDwSa3cdKHmmezXTkZpEqcraud/qxMeNaEHPiBa7U3ejjo9ozaCjJeMZHPD8OsukqjS/Ug3F0i7aDaG2aq7NSZNHetYBsARyR0sGM8aNwIpt+20TYt9gzn4npo5px/b9g9jr4QdU72N3W5PRUa2CQC4+cYLUHvKu8wP2wG1idyu27s52CuIAABozSURBVD1YYspU5Yxsb0K+ULoIqgrdnja2wxIoHhqVqv/EkW2egTiD0tKQJoMPxdZQUuhszXgKjMeWWQPRGeM70TeYLalnNl/AwuU7ILRld5SG8la//3YH1YAFShn82dRRAJydse4bmTrWisjZuNvqvL/+2+X2ue72JlugKL/KrU87TQcpItvkpEbRXa0ZfGzukbj0lEkY0ZpxbEsMADv2F18ev4lnG3Y7Bcp/a53icK6AK3/6EgBg+vhOAMBbrkl2dy1ej4XLd+CEiV1okk5P92gzmy+gp9PqtEwCZcPuflwjtTuF3rFmc6UaitfChM1SGHiN7u5avMEWdipwQjcHqM6+vTlj2+xVPoWCwAOvbsHAcA4tmZTncjrucboagevCTa/X0T0dEKL4Xtj3fbDYxsVOweo4fv68NRAZ19WKns4W42rDaq+Udx83DiNam2zTEWAFUej1mD7OerbuwcLB4YL0J2UwlCuUOKvPnjEWM8Z14sgx7fiXeW+z6umamNo3aE14nTiyFdm8Ve7LG/fgpQ17bM3o7VIgvbRhT8l9KA2lq9USKF7mqvfe9DQA4IMnT/L0PewfzNrRkKM6mpHNixLBtGyr5YOcPKpN1t3ZUe/YN4gUAWM6Wyyh5SHYlNWhoznjOVVgYDiHjuaMMepOfRvdbU0YIU1eboGhvqO500Yjmy81yS5aYdXhje19tmVCPdcd+4rvSlC0ZVywQCmDb37oRADAa5v22sfGdBQFypGjLTv4BjmSWrPTUp+VWWRkezOIgD9t3oeXNvTi8RVOG2c6VbT5D+XydocwttMqo0u+fLppRd+BT80T2OMxAlQC5fzjx5Wc+1/ZeQHAseNHAEDJiPjfH1hm1UF+sJt7B7B2V7/jhe0fymOS/FD3ejhuAeDKu17CVmnq+fHlcwAUgxvUfAc1olXoPhSVb3dbEzpaMp4air6p09FyFVZ13eY9A/jPR1cCsPxaqrNTHe/vV+zA5+9+FQPDebRkLPu0V4SYV3n3Sa11yfpenPHNxwEAf/OOqfZckjffcvq/9sg6fefPT7IDEVRHrdp/xrhOTBjZhte37HeYcPYNZHHefz9p///P50yxBhxamm8/thKzrn0MAPB3Z0+z6+k2ax3M5tDWnMbYEdZ7ttP17A8M5eznroSnnoeq6/iuVntFiVU7+nDFHZbJRflQVGd/xZ2le3eoe+tqy1j+D4NpDLCem5fQ2TeQteup3iH36P/nz29EcyaFE6Vw002EO/sGsWzrPvSMaEE6RRjZ1uwQ+gplpm5vtjRY9wBuYLjo2/DS9HWB0tliaUpuX01v/xCmjG7DCLnoo9t8p9KfNGVkiYbyr/e9Zqf71/teww7DLp1xwgKlDI7p6cC4ES2O0f1Ro4vLRo/tbEZ7cxob5Cq4g9k85k4djQXz/wwA5EvahPtf3owP37IY804YDwC45OSJ1nki+6Pftm8Q/cN5FETx4+hszUAIOLQU9bIQWZ0PAHz/ibV28AAAXPvA6/j1K1tw9oyx+Mn8P8P7TpyAsZ1FLWCbZsuf0N2K5nTKIVD0EdjJU6wP8bXN1khPCbR9A1ks3bIPKSJ0tzUZt5pducMydTWnUzjt6NEAihrbY8u2oyCK4ZiK9VpHvGdgGCNaMmhKWzZqZXpUrNi2H9985A3tftqQIqsT2NM/jCvuWILH37AEuYpWA7xNZ81pa56Al39FZ9akbgDAb17Zgj++uRsf+eFi+9wHTp6IY3o60ZxOOUbm+YKw57J84KSJ9srGqq3TKcKx0heg2vy9333avn7RGzuwdpfVLhfI96jLZT75wZNr7d9/f8502/Gv+9M+9dMleHjpdrQ1pTFllKVhb95TXNnhhXW9eHbNbvu9VHMvdN/VDi1YY/ZRlha/cvsBHDnayu9Dp04GUPQTudmxfxD/dO9r8h68NZSzbnjc/n38hK6SGeaf+8UreGbNW3Zoc5dHR/zyxj1YumWfI/BDD3L5xO0v4omVu2yhOKaz2RUQUsCP/lBs0662JnS3NWGvpo3n8gVs2XsQI9ua0Gnwj+w7mEU6ZU1D6Gqz3j/3IHDJhj0Y09Fim2zdA7TXt+xDioB7rjzdvldlttbNyb96eUtNdnNsaIFCRBcS0UoiWkNEV9ewXFxx1jT7/1ecNc3WCtT5rtYm3P7seuwfzGLb/kG8Y/oYx6KNewb0CBhrMthR8sMjIrzrbT3IpAi/e22bPdpUo5QxchLdSV/7Pyxeuxv5gsD2fYOYPKoNS758PibLDgEomhUKBYE7F1saiPrYJ45sw1sHrOACoDhi+sL5M0BE6BnRYmtZQHG3wE+cORUfP/0oAMB/fPDtAGDP8n3vTU8BsByWJ07uxhNv7HSo8U+s3ImpVz9k12PlNy7ECNmZf+/x1RBC4NPS77GrbwifPXc6ju7pQFOaHBMo/7Bqlx1Vc8LELggB/Pf/rbTPK7MIAKz/1sVyyXRLq/yLWxfbAg2wBgAdLg1FN28t3bIPE7pb8dSqXbj1qbV2x+melfy28SNw4QlH4MBQDpfd+kfHuVOmjERHSwbHT+zCrU+9iX+691UMDOdwzJcettNk0qkSH8rjb+y0TX9KC96y96DtM9MFx6SR1nPvNDiiAcsENKqjGWM7W/CmFERCCNtWf0R3q20G0neH/PMfWcJxt+xYOzwEsFrlYVxXCyZ2t6E5k8L63f32oOM9My2BN2V0O6aN7bBNb4pvP1Z8fp2tloaiC6zn1rxlC7np4zrR2pS2Ons56BFC4MHXtgIAnnjDGkipQdi8G5/CvS9ughACH/rBcwCs5d7ffaylqT+/rrgx1bKtliNcaRxjOluwZ2DYNgH+3/Id9mDFejdTJf6t6363HH2DOcydNhrtzRmHLw0AFjyzDt9/Yi3yBQEiwqSRVptv3VsU4gPDOWzdexDTxnbYQnm9S7t9ddNenHLkKLQ2pe329DIlAtagqto0rEAhojSA7wN4L4CZAD5GRDNrVf6n5JwTwHKYulEj8zO/9biM0nE6mNVHCwC3PLkW08Z2YIY0Mx17xAiMbG/G1LEdWPDsOttsojqUY48YYV/7sR//EV99cBkefG0rJnS3YozUOH799+8AYPlW/rBql8MZ/2lZd7WkzIXffQqbegewY/8gZk7owhfOt+zjR3S34pHXt2OlHOkskS/qh0+dbAtHNRL8zsJV2LxnANvkfS/4mzmYd8IR2LZvEC9v3IthaZN/dvVbdj2++v4T7OXMAStkdJ32wZxx9Bj887xj8fg/n4O3T+rGq5usjunfH3gd697qtz/4f55nTSj93uNWFJMphFixakdxZH7UmHZ0tzWhS3Y8vf3D6BvM4h/+9xU7zZ6BLBa9sRO5gsB/PPwGTvuPRSgUBAayeRzd04FX//09dtrTjh7t0PQU6h7Vu/Krl7fgX35ZNEmoKEEVfnzHc+vx2qa9yBWE/e68bXzxuc+9fhG+9ttl2Kw91w/PngQAmDyqHZv3HMSanX22yWhMR7Mt/AFLYN394ibkC8Ixkv2bd0zFpFFtILJ2/1uvtTMAXP/BWQCKI//1b/VjMJvH61v24d+kT2x8VytSKUJXa8axErfO+0+cgDU7D2DL3oN4eeMebN170GFia0qncExPJ17btNcWrn98s9jpP/gPZwKwop+2SKf7yxuLHeknz7YGfCO0/UG++cgKLJAh6ADwsytOw1hp7ly2dT8ODudt8zQAfPni4wFYQQxCFE2A35ARdc2ZFB767NlWms6iQNk3kLUHb2dOH4vxXS3YsHsAa3b22W2vovIUylKgzL6FgsDV9y9FQQDvnXWEp7n0nhc3YsmGPThanps4sg3HHTECT7yxE1/7rWWaVt/6ly86PnCNvzjIBCdJLHMBrBFCvAkARHQ3gEsALPe9Kkb+66Mn4V9++RrePrm75NxvrjoTl37/WXsEqZa9V9x95en46A8X253PiZO68b4TJ+Dong6cMNHK76OzJzvMNkf3WCOQWZO6cf0HZ+HLv7ZMJSqCTA/nPOXIUThqTDt+8cJG/OKFjTh7xlgAwM8/eZo9afHM6daxggDO/s8nAFgvr+JLFx2PD9/yHC747lOOus+c0GX/VgLs4aXb8fBSKzz2H949HdPHjbA1ng/f8lxJ+/z48jmOdrvukhPwlQeWYf7t1lyHWz8+G/NOKNbl/Jnj8Z+PrsQ5334C66Uf6KbLTgYATO8pjnSV9qO46t1Fwe8eRf7d2dPwbxceByKyP+iv/XY5vqYFUaQIuOrd07FqR59jBD3z2kcxmC3gL+ZMcQRkqJGkYmJ3K348f479f33wodpL3S9QHPm/uasfl3z/WQDAedLfNWV0Oz5x5lR7Xo76O2tSF34nOzYAmDnRej7nf6f43L5+ySxcfGIxElE9m2O+9DA+qWnbpx89BukUQQjg/pc34/6XN9sRf199/0yccqSl3SotVwVx6Per2vL0o8fgd3+y5kbd/LFTHOneM/MI3Pz4Gpz5rcfhRmm/F799An79yhbM+PIjjvPnHTfO9uFMHtWOoVwB064panq3f+LPbM1D38Fwz0AW18mO/G/PnIYp8lkdGMrh169swa+10P2bLjsZZ8+wBlxvkyP/d3zrcXz1/TOxdd8gjhrTjt999ix7SZ9xXS3Yvn/Q8f5NGtmGCd2tuHDWBPz46XU4/ztP4fIzjsJDsk0A4HPnTgdQDH//1E9fwsfmTsGBoTx+K7Wtd76tB61NaYxqb8K3HnkDE7pb0d6cwRfvt1Yvv0D7Tk6bNhp3Lt5gD/7ed+IEfOH8GbbDvto0rIYCYBIAfUGszfJYzfjI7Ml4+SvvwTuOGVty7uQpI/G3Z1of6oTuVnuEoZg8qh2//exZACyb8jUXHQ8isoUJYGlBSov4wEkTHSaCvzrtKLz0/853zH/5tKY1AcCfTR1t/35aagazJjqF39P/9m6cNq2YTh8Fzz5qlG2XV5x73DiH6W7WxC77Y1Bceor1GE6aPLLErAEApx450jZ/6NeM7WzGpt6DaG9OY45Wd6D40Shh8penHYlLTrbKSaUIv5Iamc7ia87Fv0jtBQC+ceksRxt9ZPYU28SUShHOmu58jh86dRLe/ObFeM/M8bjq3dNxw4eLI3zlDFWdt+K0o50Dh3+ad6zjmV75zqNL6rnumxfZKxoDwDXvPc5xXn93rn3/CbavTXHucc62VL4WnZOmOJ/7586bYf/+yTPrAACrvvFeexSrBiBAUduePq74bnS0ZOzADZ1nvniu/ft7HzsFV5w1DZ87bwY+cJKzzm+f3I2vvK/UoPC7z56F6y61tKDzjh9nbxim+NQ7j8Ytfz3bkY+bc95WnBOkC3tFe3MaX3nf8fb/P3iKs9uYfdQo+91yl/FVOdj40kXHO7SfS0+ehCmjnSalJ/7lHBARZh81yvaB3LV4A3b3D4PIGkT843ssa4Dy1wDAL17YhN++thXHT+jCr/7+HfYAUD3nz9/9Kv7uLiug4X8/eRrO176lD0o/FQD8/TnHYNakbrQ2pW0NudpQPdd9qQQi+iiAC4QQn5T//ziAuUKIz7rSXQngSgA48sgjZ2/YsKEkr2qRzRfwwKtbccqRI3FMT2nHChRj/8tFCIGFy3fg7Bk99mhJMZwr4I7n1mFkWzN+8syb+OKFx+G848d75vPQn7aBCJg3c7yjcwMsB2M6RXK147Tn9QeGcti29yCO6eks2eBr7a4D+P7ja1AQAle9ezqO7un0VL+HcwUseHYd3n3sOIdZT7GrbwiPLtuOtTsP4PPnzcAol3N37a4D2Ll/CE+v3oXLz5iKI7pbS/IALKdsSybl6OgBy8yQKwjs7BvEgaEcjjuiy/P6R5Zuw7UPLsONf3Ey3nHMmJKPNZsv4OGl27B47W5849JZJe0JAG/uOoDH39iJdxwztkQoCSGwYfcANu0ZwM79Q/jw7Mkl16t0L6zrxdxpo0vqMJjNY+f+ITz8+ja8c0ZPSRmA9Vw/edcSPLlyF+791BmYO80pxLfvG8Ttz63Db17ZgsvPmIrPvOsYx7MVQuA3r24BgTBxZBumjG6LbKdfub0P3W1N+PHTb2LezPElAnkwm8fu/mHc++ImfPCUSfaKyDprdh4AkTWH6MTJ3SVtsWbnAew7OIy1O/tBZAVIuN/jgeEcdh8YRipF6GhOewqiHfsH8cK6XqzddQCfftcxdkevs6l3AEs29OKs6T22wx8Ann9zNx5eug1jOltw8YkT0NmScQgRwAokuefFTTjv+HHYM5DFuceNs4NFVFv8+pUtWLm9D0d0t2LWxG6cNaN0MJvNF5AmCtxoLwpE9JIQYk5gugYWKGcA+KoQ4gL5/2sAQAjxTdM1c+bMEUuWlIYqMgzDMGbCCpRGNnm9CGAGEU0jomYAlwF4sM51YhiGOWxpWKe8ECJHRP8A4DEAaQALhBDL6lwthmGYw5aGFSgAIIR4GMDDgQkZhmGYqtPIJi+GYRgmQbBAYRiGYWKBBQrDMAwTCyxQGIZhmFhggcIwDMPEQsNObCwHIuoDsNInSTeAfT7njwSwMaCYoDyCzseVR1BduZ7R8qi0nnHUg+sZfz0q/eYPl3oeK4QoXb7CjRDisPkHYEnA+VsDzu8KUUZQHr7nY8zDt65cz9rWM456cD3r8m5wPUVw36n+scnLyW8Dzu8NOB8mj6DzceURVFeuZ7Q8Kq1nHPXgesZfj0q/+cOpnoEcbiavJSLEejTVur6WNEpduZ7xwvWMF65ntPwPNw3l1jpfX0sapa5cz3jhesYL1zNC/oeVhsIwDMNUj8NNQ2EYhmGqxGEvUIhoARHtJKLXtWMnEdFiIlpKRL8loi55vImI7pTHV6g9WOS5J4loJRG9Kv+N8yqvRvVsJqLb5fHXiOgc7ZrZ8vgaIrqZYt7KLcZ6Vrs9pxDRE/I5LiOiz8vjo4loIRGtln9HaddcI9ttJRFdoB2vWpvGXM+qtWnUehLRGJn+ABH9jyuvxLRnQD2T1J7vIaKXZLu9RETnanlV9Zt3ECYU7FD+B+CdAE4F8Lp27EUA75K//xbAdfL3XwK4W/5uB7AewFT5/ycBzElIPa8CcLv8PQ7ASwBS8v8vADgDAAF4BMB7E1rParfnBACnyt8jAKwCMBPAfwK4Wh6/GsAN8vdMAK8BaAEwDcBaAOlqt2nM9axam5ZRzw4AZwH4NID/ceWVpPb0q2eS2vMUABPl71kAttSiPd3/DnsNRQjxFIBe1+FjATwlfy8E8GGVHEAHEWUAtAEYBrA/gfWcCWCRvG4nrJDCOUQ0AUCXEGKxsN60uwBcmrR6xlkfE0KIbUKIl+XvPgArAEwCcAmAO2WyO1Fsn0tgDSaGhBDrAKwBMLfabRpXPeOqT1z1FEL0CyGeATCo55O09jTVs9qUUc9XhBBb5fFlAFqJqKUW37zOYS9QDLwO4APy90cBTJG/7wPQD2AbrFmp/yWE0DvP26Xq+5WqqpXB9XwNwCVElCGiaQBmy3OTAGzWrt8sjyWtnoqatCcRTYU1wnsewHghxDbA+qhhaU6A1U6btMtU29WsTSusp6LqbRqyniaS1p5BJLE9PwzgFSHEEGr8zbNA8eZvAVxFRC/BUjeH5fG5APIAJsIyJ/wzER0tz/2VEOLtAM6W/z5ex3ougPXiLAHwXQDPAcjBUnnd1CLML2o9gRq1JxF1ArgfwBeEEH7apqntatKmMdQTqEGbRqinMQuPY/VsTz8S155EdAKAGwB8Sh3ySFa1b54FigdCiDeEEPOEELMB/AKWHRqwfCiPCiGy0kTzLKSJRgixRf7tA/C/qI2ZwbOeQoicEOIfhRAnCyEuATASwGpYnfdkLYvJALa6801APWvSnkTUBOtj/bkQ4lfy8A5pJlDml53y+GY4tSfVdlVv05jqWfU2jVhPE0lrTyNJa08imgzg1wAuF0KoPqum3zwLFA9UtAYRpQD8PwA/lKc2AjiXLDoAnA7gDWmyGSuvaQLwPlhmnrrUk4jaZf1ARO8BkBNCLJcqch8RnS7V88sBPJC0etaiPeX93wZghRDiO9qpBwHMl7/no9g+DwK4TNqlpwGYAeCFardpXPWsdpuWUU9PEtiepnwS1Z5ENBLAQwCuEUI8qxLX/JuP28vfaP9gjZi3AcjCkuZXAPg8rKiKVQC+heIE0E4Av4Tl9FoO4F9FMRLkJQB/kudugoysqVM9p8JaVXkFgN8DOErLZw6sF38tgP9R1ySpnjVqz7Ngqf5/AvCq/HcRgDGwAgVWy7+jtWu+LNttJbRImWq2aVz1rHabllnP9bACOA7Id2VmQtuzpJ5Ja09YA7V+Le2rAMbV4pvX//FMeYZhGCYW2OTFMAzDxAILFIZhGCYWWKAwDMMwscAChWEYhokFFigMwzBMLLBAYZiEQESfJqLLI6SfStqqzgxTbzL1rgDDMNZEOSHED4NTMkxyYYHCMDEhF/F7FNYifqfAmsh5OYDjAXwH1sTYtwD8jRBiGxE9CWv9sjMBPEhEIwAcEEL8FxGdDGtFgXZYE9L+Vgixh4hmw1oDbQDAM7W7O4YJhk1eDBMvxwK4VQhxIqytDa4C8D0AHxHWWmYLAFyvpR8phHiXEOK/XfncBeCLMp+lAK6Vx28H8DkhxBnVvAmGKQfWUBgmXjaJ4lpKPwPwJVgbHi2Uq5unYS1No7jHnQERdcMSNH+Qh+4E8EuP4z8F8N74b4FhyoMFCsPEi3stoz4Ay3w0iv4IeZNH/gyTGNjkxTDxciQRKeHxMQB/BNCjjhFRk9yzwogQYh+APUR0tjz0cQB/EELsBbCPiM6Sx/8q/uozTPmwhsIw8bICwHwi+hGsFWG/B+AxADdLk1UG1mZiywLymQ/gh0TUDuBNAJ+Qxz8BYAERDch8GSYx8GrDDBMTMsrrd0KIWXWuCsPUBTZ5MQzDMLHAGgrDMAwTC6yhMAzDMLHAAoVhGIaJBRYoDMMwTCywQGEYhmFigQUKwzAMEwssUBiGYZhY+P9cYq2RtHhluAAAAABJRU5ErkJggg==\n", 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\n", + "text/plain": [ + "
" + ] + }, + "metadata": { + "needs_background": "light" + }, + "output_type": "display_data" + } + ], "source": [ "sorted_data['inc'][-200:].plot()" ] @@ -252,10 +2316,8 @@ }, { "cell_type": "code", - "execution_count": null, - "metadata": { - "collapsed": true - }, + "execution_count": 37, + "metadata": {}, "outputs": [], "source": [ "first_august_week = [pd.Period(pd.Timestamp(y, 8, 1), 'W')\n", @@ -274,7 +2336,7 @@ }, { "cell_type": "code", - "execution_count": null, + "execution_count": 38, "metadata": {}, "outputs": [], "source": [ @@ -298,9 +2360,32 @@ }, { "cell_type": "code", - "execution_count": null, + "execution_count": 39, "metadata": {}, - "outputs": [], + "outputs": [ + { + "data": { + "text/plain": [ + "" + ] + }, + "execution_count": 39, + "metadata": {}, + "output_type": "execute_result" + }, + { + "data": { + "image/png": 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\n", 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" + ] + }, + "metadata": { + "needs_background": "light" + }, + "output_type": "display_data" + } + ], "source": [ "yearly_incidence.plot(style='*')" ] @@ -314,9 +2399,55 @@ }, { "cell_type": "code", - "execution_count": null, + "execution_count": 40, "metadata": {}, - "outputs": [], + "outputs": [ + { + "data": { + "text/plain": [ + "2014 1600941\n", + "1991 1659249\n", + "1995 1840410\n", + "2020 2042389\n", + "2012 2175217\n", + "2003 2234584\n", + "2019 2254386\n", + "2006 2307352\n", + "2017 2321583\n", + "2001 2529279\n", + "1992 2574578\n", + "1993 2703886\n", + "2018 2705325\n", + "1988 2765617\n", + "2007 2780164\n", + "1987 2855570\n", + "2016 2856393\n", + "2011 2857040\n", + "2008 2973918\n", + "1998 3034904\n", + "2002 3125418\n", + "2009 3444020\n", + "1994 3514763\n", + "1996 3539413\n", + "2004 3567744\n", + "1997 3620066\n", + "2015 3654892\n", + "2000 3826372\n", + "2005 3835025\n", + "1999 3908112\n", + "2010 4111392\n", + "2013 4182691\n", + "1986 5115251\n", + "1990 5235827\n", + "1989 5466192\n", + "dtype: int64" + ] + }, + "execution_count": 40, + "metadata": {}, + "output_type": "execute_result" + } + ], "source": [ "yearly_incidence.sort_values()" ] @@ -331,9 +2462,32 @@ }, { "cell_type": "code", - "execution_count": null, + "execution_count": 41, "metadata": {}, - "outputs": [], + "outputs": [ + { + "data": { + "text/plain": [ + "" + ] + }, + "execution_count": 41, + "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.hist(xrot=20)" ] @@ -341,9 +2495,7 @@ { "cell_type": "code", "execution_count": null, - "metadata": { - "collapsed": true - }, + "metadata": {}, "outputs": [], "source": [] } diff --git a/module3/exo1/incidence-PAY-3.csv b/module3/exo1/incidence-PAY-3.csv new file mode 100644 index 0000000000000000000000000000000000000000..0bcc4449b2d303a6042eedc5a8fe1578e6001496 --- /dev/null +++ b/module3/exo1/incidence-PAY-3.csv @@ -0,0 +1,1890 @@ +# @source="réseau Sentinelles, INSERM, Sorbonne Université, http://www.sentiweb.fr", @meta={"period":[198444,202053],"geo":["PAY","1"],"geo_ref":"insee","indicator":"3","type":"all","conf_int":true,"compact":false}, @date=2021-01-07T10:39:46+01:00 +week,indicator,inc,inc_low,inc_up,inc100,inc100_low,inc100_up,geo_insee,geo_name +202053,3,23881,17956,29806,36,27,45,FR,France +202052,3,18166,13646,22686,28,21,35,FR,France 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