From 903b07c85e9e78a7cbda02f4e4c8aa39351d0df3 Mon Sep 17 00:00:00 2001
From: 3447a552022e9b60e8a4c5d442e78097
 <3447a552022e9b60e8a4c5d442e78097@app-learninglab.inria.fr>
Date: Thu, 14 Nov 2024 18:58:31 +0000
Subject: [PATCH] no commit message

---
 module3/exo1/inc-3-PAY.csv                    | 2091 +++++++++++++++++
 .../influenza-like-illness-analysis.ipynb     |  202 +-
 2 files changed, 2125 insertions(+), 168 deletions(-)
 create mode 100644 module3/exo1/inc-3-PAY.csv

diff --git a/module3/exo1/inc-3-PAY.csv b/module3/exo1/inc-3-PAY.csv
new file mode 100644
index 0000000..74d5c50
--- /dev/null
+++ b/module3/exo1/inc-3-PAY.csv
@@ -0,0 +1,2091 @@
+# {"source":"r&#233;seau Sentinelles, INSERM, Sorbonne Universit&#233;, https:\/\/www.sentiweb.fr","meta":{"period":[198444,202445],"geo":["PAY",0],"geo_ref":"insee","indicator":"3","type":"all","conf_int":true,"compact":false,"age_group":false,"span":"all"},"date":"2024-11-13T18:41:04+01:00","bundle":"1731519663"}
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+200524,3,5892,2029,9755,10,4,16,FR,France
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+200514,3,21988,14834,29142,36,24,48,FR,France
+200513,3,42971,33053,52889,71,55,87,FR,France
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+200440,3,25639,17291,33987,43,29,57,FR,France
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+200438,3,17483,9417,25549,29,16,42,FR,France
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+200424,3,6737,2394,11080,11,4,18,FR,France
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+200227,3,1882,0,6151,3,0,10,FR,France
+200226,3,4523,0,12320,8,0,21,FR,France
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+200216,3,17762,9887,25637,30,17,43,FR,France
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+200214,3,23877,15709,32045,40,26,54,FR,France
+200213,3,27497,16289,38705,46,27,65,FR,France
+200212,3,33510,20938,46082,56,35,77,FR,France
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+200209,3,63735,48368,79102,107,81,133,FR,France
+200208,3,117204,95548,138860,197,161,233,FR,France
+200207,3,170251,137065,203437,286,230,342,FR,France
+200206,3,325084,296111,354057,546,497,595,FR,France
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+200152,3,57999,43225,72773,98,73,123,FR,France
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+200150,3,31309,22878,39740,53,39,67,FR,France
+200149,3,34792,23268,46316,59,40,78,FR,France
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+200147,3,27455,20021,34889,46,33,59,FR,France
+200146,3,21127,14294,27960,36,24,48,FR,France
+200145,3,20766,13979,27553,35,24,46,FR,France
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+200141,3,20241,14032,26450,34,24,44,FR,France
+200140,3,18113,9971,26255,31,17,45,FR,France
+200139,3,25407,7785,43029,43,13,73,FR,France
+200138,3,9736,4985,14487,16,8,24,FR,France
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+200134,3,2990,0,6419,5,0,11,FR,France
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+200131,3,18999,4286,33712,32,7,57,FR,France
+200130,3,2144,0,5670,4,0,10,FR,France
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+200128,3,3555,553,6557,6,1,11,FR,France
+200127,3,4739,1122,8356,8,2,14,FR,France
+200126,3,3335,466,6204,6,1,11,FR,France
+200125,3,2643,527,4759,4,0,8,FR,France
+200124,3,4784,2158,7410,8,4,12,FR,France
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+199524,3,8058,5054,11062,14,9,19,FR,France
+199523,3,13820,9801,17839,24,17,31,FR,France
+199522,3,14124,9999,18249,24,17,31,FR,France
+199521,3,11931,8655,15207,21,15,27,FR,France
+199520,3,18846,14311,23381,33,25,41,FR,France
+199519,3,26261,21488,31034,45,37,53,FR,France
+199518,3,39231,33258,45204,68,58,78,FR,France
+199517,3,88640,79343,97937,153,137,169,FR,France
+199516,3,140488,129439,151537,243,224,262,FR,France
+199515,3,181007,169110,192904,313,292,334,FR,France
+199514,3,248704,235144,262264,431,408,454,FR,France
+199513,3,209839,197191,222487,363,341,385,FR,France
+199512,3,122434,112497,132371,212,195,229,FR,France
+199511,3,81730,73346,90114,142,127,157,FR,France
+199510,3,49387,42703,56071,86,74,98,FR,France
+199509,3,39696,33259,46133,69,58,80,FR,France
+199508,3,38008,32225,43791,66,56,76,FR,France
+199507,3,30550,25479,35621,53,44,62,FR,France
+199506,3,37351,32007,42695,65,56,74,FR,France
+199505,3,27876,23218,32534,48,40,56,FR,France
+199504,3,27643,22818,32468,48,40,56,FR,France
+199503,3,24844,20391,29297,43,35,51,FR,France
+199502,3,23480,19249,27711,41,34,48,FR,France
+199501,3,26556,21916,31196,46,38,54,FR,France
+199452,3,22036,17495,26577,38,30,46,FR,France
+199451,3,26912,21750,32074,47,38,56,FR,France
+199450,3,28831,23470,34192,50,41,59,FR,France
+199449,3,21161,16559,25763,37,29,45,FR,France
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+199446,3,14252,10525,17979,25,19,31,FR,France
+199445,3,12152,8448,15856,21,15,27,FR,France
+199444,3,11307,7688,14926,20,14,26,FR,France
+199443,3,11254,8002,14506,20,14,26,FR,France
+199442,3,14406,10653,18159,25,18,32,FR,France
+199441,3,14073,10341,17805,24,18,30,FR,France
+199440,3,15962,11850,20074,28,21,35,FR,France
+199439,3,15878,11643,20113,28,21,35,FR,France
+199438,3,15366,11100,19632,27,20,34,FR,France
+199437,3,5949,3561,8337,10,6,14,FR,France
+199436,3,2806,1133,4479,5,2,8,FR,France
+199435,3,4556,2358,6754,8,4,12,FR,France
+199434,3,3459,1444,5474,6,2,10,FR,France
+199433,3,4272,977,7567,7,1,13,FR,France
+199432,3,4786,1613,7959,8,2,14,FR,France
+199431,3,5027,1580,8474,9,3,15,FR,France
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+199428,3,1581,316,2846,3,1,5,FR,France
+199427,3,713,0,1459,1,0,2,FR,France
+199426,3,990,80,1900,2,0,4,FR,France
+199425,3,5431,3222,7640,9,5,13,FR,France
+199424,3,6288,3723,8853,11,7,15,FR,France
+199423,3,6440,1052,11828,11,2,20,FR,France
+199422,3,845,0,2449,1,0,4,FR,France
+199421,3,2197,395,3999,4,1,7,FR,France
+199420,3,2217,852,3582,4,2,6,FR,France
+199419,3,1483,406,2560,3,1,5,FR,France
+199418,3,3705,1940,5470,6,3,9,FR,France
+199417,3,2288,1064,3512,4,2,6,FR,France
+199416,3,5156,3176,7136,9,6,12,FR,France
+199415,3,6952,4678,9226,12,8,16,FR,France
+199414,3,4671,2784,6558,8,5,11,FR,France
+199413,3,3343,1641,5045,6,3,9,FR,France
+199412,3,4305,2412,6198,7,4,10,FR,France
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+199409,3,5635,3251,8019,10,6,14,FR,France
+199408,3,9539,6652,12426,17,12,22,FR,France
+199407,3,14639,11188,18090,25,19,31,FR,France
+199406,3,17308,13395,21221,30,23,37,FR,France
+199405,3,18489,14290,22688,32,25,39,FR,France
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+199403,3,29882,24817,34947,52,43,61,FR,France
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+199335,3,5589,3066,8112,10,6,14,FR,France
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+199239,3,13535,10301,16769,24,18,30,FR,France
+199238,3,9837,7106,12568,17,12,22,FR,France
+199237,3,7480,5130,9830,13,9,17,FR,France
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+199231,3,4233,1733,6733,7,3,11,FR,France
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+199227,3,5568,3134,8002,10,6,14,FR,France
+199226,3,5886,3229,8543,10,5,15,FR,France
+199225,3,5304,2805,7803,9,5,13,FR,France
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+199223,3,3914,1855,5973,7,3,11,FR,France
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+199221,3,5059,2889,7229,9,5,13,FR,France
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+199218,3,3887,1777,5997,7,3,11,FR,France
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+199216,3,5460,2934,7986,10,6,14,FR,France
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+199211,3,11689,7575,15803,20,13,27,FR,France
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+198927,3,3641,1350,5932,6,2,10,FR,France
+198926,3,5753,2885,8621,10,5,15,FR,France
+198925,3,6299,3454,9144,11,6,16,FR,France
+198924,3,6337,3537,9137,11,6,16,FR,France
+198923,3,11779,7984,15574,21,14,28,FR,France
+198922,3,9104,4764,13444,16,8,24,FR,France
+198921,3,9554,4316,14792,17,8,26,FR,France
+198920,3,6093,1023,11163,11,2,20,FR,France
+198919,3,-,,,-,,,FR,France
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+198915,3,9667,6209,13125,17,11,23,FR,France
+198914,3,15230,10469,19991,27,19,35,FR,France
+198913,3,10564,6767,14361,19,12,26,FR,France
+198912,3,13419,9542,17296,24,17,31,FR,France
+198911,3,16633,12140,21126,30,22,38,FR,France
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+198909,3,12895,9183,16607,23,16,30,FR,France
+198908,3,19746,15258,24234,35,27,43,FR,France
+198907,3,27277,21760,32794,49,39,59,FR,France
+198906,3,47844,40320,55368,85,72,98,FR,France
+198905,3,52840,45665,60015,94,81,107,FR,France
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+198903,3,66010,58065,73955,118,104,132,FR,France
+198902,3,112284,102003,122565,200,182,218,FR,France
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+198852,3,467971,447033,488909,837,800,874,FR,France
+198851,3,872748,846468,899028,1562,1515,1609,FR,France
+198850,3,1001824,974799,1028849,1793,1745,1841,FR,France
+198849,3,966523,940068,992978,1729,1682,1776,FR,France
+198848,3,637811,614785,660837,1141,1100,1182,FR,France
+198847,3,246062,231234,260890,440,413,467,FR,France
+198846,3,92484,83160,101808,165,148,182,FR,France
+198845,3,53940,46148,61732,97,83,111,FR,France
+198844,3,42106,35336,48876,75,63,87,FR,France
+198843,3,38252,31909,44595,68,57,79,FR,France
+198842,3,45495,38467,52523,81,68,94,FR,France
+198841,3,46336,39344,53328,83,70,96,FR,France
+198840,3,39882,33507,46257,71,60,82,FR,France
+198839,3,43730,36755,50705,78,66,90,FR,France
+198838,3,35243,29367,41119,63,52,74,FR,France
+198837,3,15537,11911,19163,28,22,34,FR,France
+198836,3,7539,4840,10238,13,8,18,FR,France
+198835,3,7797,4762,10832,14,9,19,FR,France
+198834,3,4950,2005,7895,9,4,14,FR,France
+198833,3,7937,3861,12013,14,7,21,FR,France
+198832,3,7033,2595,11471,13,5,21,FR,France
+198831,3,8758,3591,13925,16,7,25,FR,France
+198830,3,4205,1224,7186,8,3,13,FR,France
+198829,3,6103,1013,11193,11,2,20,FR,France
+198828,3,8562,3483,13641,15,6,24,FR,France
+198827,3,4690,2196,7184,8,4,12,FR,France
+198826,3,7065,3905,10225,13,7,19,FR,France
+198825,3,7657,4664,10650,14,9,19,FR,France
+198824,3,6676,3978,9374,12,7,17,FR,France
+198823,3,8695,5755,11635,16,11,21,FR,France
+198822,3,11566,8282,14850,21,15,27,FR,France
+198821,3,11107,7742,14472,20,14,26,FR,France
+198820,3,14118,10223,18013,25,18,32,FR,France
+198819,3,18260,13847,22673,33,25,41,FR,France
+198818,3,20415,16281,24549,37,30,44,FR,France
+198817,3,21750,17436,26064,39,31,47,FR,France
+198816,3,33730,27496,39964,60,49,71,FR,France
+198815,3,70616,61754,79478,126,110,142,FR,France
+198814,3,123868,113211,134525,222,203,241,FR,France
+198813,3,193710,181519,205901,347,325,369,FR,France
+198812,3,283445,268834,298056,507,481,533,FR,France
+198811,3,316175,300858,331492,566,539,593,FR,France
+198810,3,235142,222004,248280,421,397,445,FR,France
+198809,3,135564,125263,145865,243,225,261,FR,France
+198808,3,87753,78449,97057,157,140,174,FR,France
+198807,3,77099,68423,85775,138,122,154,FR,France
+198806,3,69349,61502,77196,124,110,138,FR,France
+198805,3,72705,64952,80458,130,116,144,FR,France
+198804,3,72818,64944,80692,130,116,144,FR,France
+198803,3,68869,60922,76816,123,109,137,FR,France
+198802,3,59743,51907,67579,107,93,121,FR,France
+198801,3,60929,52573,69285,109,94,124,FR,France
+198753,3,47257,38170,56344,85,69,101,FR,France
+198752,3,11935,2353,21517,21,4,38,FR,France
+198751,3,47744,34266,61222,86,62,110,FR,France
+198750,3,57767,50181,65353,104,90,118,FR,France
+198749,3,49380,42461,56299,89,77,101,FR,France
+198748,3,41871,35115,48627,75,63,87,FR,France
+198747,3,29688,23465,35911,53,42,64,FR,France
+198746,3,37216,30199,44233,67,54,80,FR,France
+198745,3,35456,29024,41888,64,52,76,FR,France
+198744,3,41024,33829,48219,74,61,87,FR,France
+198743,3,46356,38370,54342,83,69,97,FR,France
+198742,3,38021,30236,45806,68,54,82,FR,France
+198741,3,42021,32016,52026,76,58,94,FR,France
+198740,3,24641,15930,33352,44,28,60,FR,France
+198739,3,32328,23548,41108,58,42,74,FR,France
+198738,3,16782,11870,21694,30,21,39,FR,France
+198737,3,11208,6542,15874,20,12,28,FR,France
+198736,3,7906,4014,11798,14,7,21,FR,France
+198735,3,6149,2970,9328,11,5,17,FR,France
+198734,3,6631,2734,10528,12,5,19,FR,France
+198733,3,6404,1834,10974,12,4,20,FR,France
+198732,3,7215,2353,12077,13,4,22,FR,France
+198731,3,8233,3655,12811,15,7,23,FR,France
+198730,3,4642,1301,7983,8,2,14,FR,France
+198729,3,4389,913,7865,8,2,14,FR,France
+198728,3,2702,138,5266,5,0,10,FR,France
+198727,3,10171,5904,14438,18,10,26,FR,France
+198726,3,12341,7824,16858,22,14,30,FR,France
+198725,3,23413,15490,31336,42,28,56,FR,France
+198724,3,11289,7282,15296,20,13,27,FR,France
+198723,3,15857,10943,20771,29,20,38,FR,France
+198722,3,14887,9743,20031,27,18,36,FR,France
+198721,3,17619,12649,22589,32,23,41,FR,France
+198720,3,10344,6454,14234,19,12,26,FR,France
+198719,3,12539,7943,17135,23,15,31,FR,France
+198718,3,16095,10330,21860,29,19,39,FR,France
+198717,3,21256,14850,27662,38,26,50,FR,France
+198716,3,32416,25100,39732,58,45,71,FR,France
+198715,3,44292,36456,52128,80,66,94,FR,France
+198714,3,50642,41866,59418,91,75,107,FR,France
+198713,3,62246,52749,71743,112,95,129,FR,France
+198712,3,59625,50653,68597,107,91,123,FR,France
+198711,3,53561,45035,62087,96,81,111,FR,France
+198710,3,93067,80519,105615,167,144,190,FR,France
+198709,3,147006,133519,160493,264,240,288,FR,France
+198708,3,217779,202179,233379,391,363,419,FR,France
+198707,3,288180,270718,305642,518,487,549,FR,France
+198706,3,296702,279051,314353,533,501,565,FR,France
+198705,3,236046,219483,252609,424,394,454,FR,France
+198704,3,158333,143625,173041,285,259,311,FR,France
+198703,3,103841,91699,115983,187,165,209,FR,France
+198702,3,74213,64014,84412,133,115,151,FR,France
+198701,3,69745,59207,80283,125,106,144,FR,France
+198652,3,76263,64958,87568,138,118,158,FR,France
+198651,3,72920,63047,82793,132,114,150,FR,France
+198650,3,73413,64019,82807,133,116,150,FR,France
+198649,3,56296,48229,64363,102,87,117,FR,France
+198648,3,46031,38578,53484,83,70,96,FR,France
+198647,3,36740,29710,43770,66,53,79,FR,France
+198646,3,32134,25327,38941,58,46,70,FR,France
+198645,3,38964,31382,46546,70,56,84,FR,France
+198644,3,28646,22048,35244,52,40,64,FR,France
+198643,3,27532,20842,34222,50,38,62,FR,France
+198642,3,31815,25124,38506,57,45,69,FR,France
+198641,3,32864,25939,39789,59,47,71,FR,France
+198640,3,33516,26776,40256,60,48,72,FR,France
+198639,3,28665,22477,34853,52,41,63,FR,France
+198638,3,26615,20479,32751,48,37,59,FR,France
+198637,3,15998,10802,21194,29,20,38,FR,France
+198636,3,9182,4982,13382,17,9,25,FR,France
+198635,3,10587,4470,16704,19,8,30,FR,France
+198634,3,5762,858,10666,10,1,19,FR,France
+198633,3,3115,554,5676,6,1,11,FR,France
+198632,3,1027,0,2311,2,0,4,FR,France
+198631,3,2247,0,4574,4,0,8,FR,France
+198630,3,2346,141,4551,4,0,8,FR,France
+198629,3,3654,931,6377,7,2,12,FR,France
+198628,3,2327,0,5318,4,0,9,FR,France
+198627,3,7529,3353,11705,14,6,22,FR,France
+198626,3,8778,5106,12450,16,9,23,FR,France
+198625,3,11075,6804,15346,20,12,28,FR,France
+198624,3,11160,7252,15068,20,13,27,FR,France
+198623,3,14372,9896,18848,26,18,34,FR,France
+198622,3,9717,5594,13840,18,11,25,FR,France
+198621,3,14460,9575,19345,26,17,35,FR,France
+198620,3,17133,12106,22160,31,22,40,FR,France
+198619,3,22177,16008,28346,40,29,51,FR,France
+198618,3,31736,24115,39357,57,43,71,FR,France
+198617,3,34874,27440,42308,63,50,76,FR,France
+198616,3,41196,32894,49498,74,59,89,FR,France
+198615,3,42659,33537,51781,77,61,93,FR,France
+198614,3,49792,39728,59856,90,72,108,FR,France
+198613,3,87249,63562,110936,157,114,200,FR,France
+198612,3,124777,97237,152317,225,175,275,FR,France
+198611,3,168146,151035,185257,303,272,334,FR,France
+198610,3,257305,231225,283385,464,417,511,FR,France
+198609,3,321140,296644,345636,580,536,624,FR,France
+198608,3,448786,419219,478353,810,757,863,FR,France
+198607,3,490723,460150,521296,886,831,941,FR,France
+198606,3,439300,411764,466836,793,743,843,FR,France
+198605,3,364727,339868,389586,658,613,703,FR,France
+198604,3,348509,322464,374554,629,582,676,FR,France
+198603,3,271539,248654,294424,490,449,531,FR,France
+198602,3,178138,159344,196932,322,288,356,FR,France
+198601,3,112614,96539,128689,203,174,232,FR,France
+198552,3,86452,72250,100654,157,131,183,FR,France
+198551,3,114666,99538,129794,208,181,235,FR,France
+198550,3,86031,73604,98458,156,133,179,FR,France
+198549,3,65931,55326,76536,120,101,139,FR,France
+198548,3,68291,57581,79001,124,105,143,FR,France
+198547,3,66177,55221,77133,120,100,140,FR,France
+198546,3,70534,58788,82280,128,107,149,FR,France
+198545,3,57514,47167,67861,104,85,123,FR,France
+198544,3,67356,55744,78968,122,101,143,FR,France
+198543,3,87402,74208,100596,158,134,182,FR,France
+198542,3,76218,64604,87832,138,117,159,FR,France
+198541,3,45712,36755,54669,83,67,99,FR,France
+198540,3,49739,40335,59143,90,73,107,FR,France
+198539,3,39819,31234,48404,72,56,88,FR,France
+198538,3,27605,20614,34596,50,37,63,FR,France
+198537,3,22219,15626,28812,40,28,52,FR,France
+198536,3,27986,18992,36980,51,35,67,FR,France
+198535,3,30215,18546,41884,55,34,76,FR,France
+198534,3,40389,24786,55992,73,45,101,FR,France
+198533,3,22611,8819,36403,41,16,66,FR,France
+198532,3,7488,1851,13125,14,4,24,FR,France
+198531,3,16958,8479,25437,31,16,46,FR,France
+198530,3,11598,5507,17689,21,10,32,FR,France
+198529,3,13054,6474,19634,24,12,36,FR,France
+198528,3,14588,7659,21517,26,13,39,FR,France
+198527,3,19670,11761,27579,36,22,50,FR,France
+198526,3,18609,12637,24581,34,23,45,FR,France
+198525,3,19362,12454,26270,35,22,48,FR,France
+198524,3,19855,13577,26133,36,25,47,FR,France
+198523,3,19373,10010,28736,35,18,52,FR,France
+198522,3,24099,17190,31008,44,31,57,FR,France
+198521,3,26096,19621,32571,47,35,59,FR,France
+198520,3,27896,20885,34907,51,38,64,FR,France
+198519,3,43154,32821,53487,78,59,97,FR,France
+198518,3,40555,29935,51175,74,55,93,FR,France
+198517,3,34053,24366,43740,62,44,80,FR,France
+198516,3,50362,36451,64273,91,66,116,FR,France
+198515,3,63881,45538,82224,116,83,149,FR,France
+198514,3,134545,114400,154690,244,207,281,FR,France
+198513,3,197206,176080,218332,357,319,395,FR,France
+198512,3,245240,223304,267176,445,405,485,FR,France
+198511,3,276205,252399,300011,501,458,544,FR,France
+198510,3,353231,326279,380183,640,591,689,FR,France
+198509,3,369895,341109,398681,670,618,722,FR,France
+198508,3,389886,359529,420243,707,652,762,FR,France
+198507,3,471852,432599,511105,855,784,926,FR,France
+198506,3,565825,518011,613639,1026,939,1113,FR,France
+198505,3,637302,592795,681809,1155,1074,1236,FR,France
+198504,3,424937,390794,459080,770,708,832,FR,France
+198503,3,213901,174689,253113,388,317,459,FR,France
+198502,3,97586,80949,114223,177,147,207,FR,France
+198501,3,85489,65918,105060,155,120,190,FR,France
+198452,3,84830,60602,109058,154,110,198,FR,France
+198451,3,101726,80242,123210,185,146,224,FR,France
+198450,3,123680,101401,145959,225,184,266,FR,France
+198449,3,101073,81684,120462,184,149,219,FR,France
+198448,3,78620,60634,96606,143,110,176,FR,France
+198447,3,72029,54274,89784,131,99,163,FR,France
+198446,3,87330,67686,106974,159,123,195,FR,France
+198445,3,135223,101414,169032,246,184,308,FR,France
+198444,3,68422,20056,116788,125,37,213,FR,France
diff --git a/module3/exo1/influenza-like-illness-analysis.ipynb b/module3/exo1/influenza-like-illness-analysis.ipynb
index 7bdc071..6d18452 100644
--- a/module3/exo1/influenza-like-illness-analysis.ipynb
+++ b/module3/exo1/influenza-like-illness-analysis.ipynb
@@ -9,7 +9,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 1,
+   "execution_count": 27,
    "metadata": {},
    "outputs": [],
    "source": [
@@ -28,7 +28,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 2,
+   "execution_count": 28,
    "metadata": {},
    "outputs": [],
    "source": [
@@ -66,7 +66,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 3,
+   "execution_count": 29,
    "metadata": {},
    "outputs": [
     {
@@ -1031,13 +1031,20 @@
        "[2089 rows x 10 columns]"
       ]
      },
-     "execution_count": 3,
+     "execution_count": 29,
      "metadata": {},
      "output_type": "execute_result"
     }
    ],
    "source": [
-    "raw_data = pd.read_csv(data_url, skiprows=1)\n",
+    "data_file = \"inc-3-PAY.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)\n",
+    "\n",
+    "raw_data = pd.read_csv(data_file, skiprows=1)\n",
     "raw_data"
    ]
   },
@@ -1050,7 +1057,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 4,
+   "execution_count": 30,
    "metadata": {},
    "outputs": [
     {
@@ -1112,7 +1119,7 @@
        "1852        FR   France  "
       ]
      },
-     "execution_count": 4,
+     "execution_count": 30,
      "metadata": {},
      "output_type": "execute_result"
     }
@@ -1130,7 +1137,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 5,
+   "execution_count": 31,
    "metadata": {},
    "outputs": [
     {
@@ -2095,7 +2102,7 @@
        "[2088 rows x 10 columns]"
       ]
      },
-     "execution_count": 5,
+     "execution_count": 31,
      "metadata": {},
      "output_type": "execute_result"
     }
@@ -2124,7 +2131,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 6,
+   "execution_count": 32,
    "metadata": {},
    "outputs": [],
    "source": [
@@ -2153,7 +2160,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 11,
+   "execution_count": 33,
    "metadata": {},
    "outputs": [
     {
@@ -3133,7 +3140,7 @@
        "[2088 rows x 10 columns]"
       ]
      },
-     "execution_count": 11,
+     "execution_count": 33,
      "metadata": {},
      "output_type": "execute_result"
     }
@@ -3160,7 +3167,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 8,
+   "execution_count": 34,
    "metadata": {},
    "outputs": [
     {
@@ -3188,7 +3195,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 9,
+   "execution_count": 35,
    "metadata": {},
    "outputs": [
     {
@@ -3198,7 +3205,7 @@
      "traceback": [
       "\u001b[0;31m---------------------------------------------------------------------------\u001b[0m",
       "\u001b[0;31mTypeError\u001b[0m                                 Traceback (most recent call last)",
-      "\u001b[0;32m<ipython-input-9-0966cd984262>\u001b[0m in \u001b[0;36m<module>\u001b[0;34m\u001b[0m\n\u001b[0;32m----> 1\u001b[0;31m \u001b[0msorted_data\u001b[0m\u001b[0;34m[\u001b[0m\u001b[0;34m'inc'\u001b[0m\u001b[0;34m]\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mplot\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0m",
+      "\u001b[0;32m<ipython-input-35-0966cd984262>\u001b[0m in \u001b[0;36m<module>\u001b[0;34m\u001b[0m\n\u001b[0;32m----> 1\u001b[0;31m \u001b[0msorted_data\u001b[0m\u001b[0;34m[\u001b[0m\u001b[0;34m'inc'\u001b[0m\u001b[0;34m]\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mplot\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0m",
       "\u001b[0;32m/opt/conda/lib/python3.6/site-packages/pandas/plotting/_core.py\u001b[0m in \u001b[0;36m__call__\u001b[0;34m(self, kind, ax, figsize, use_index, title, grid, legend, style, logx, logy, loglog, xticks, yticks, xlim, ylim, rot, fontsize, colormap, table, yerr, xerr, label, secondary_y, **kwds)\u001b[0m\n\u001b[1;32m   2501\u001b[0m                            \u001b[0mcolormap\u001b[0m\u001b[0;34m=\u001b[0m\u001b[0mcolormap\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0mtable\u001b[0m\u001b[0;34m=\u001b[0m\u001b[0mtable\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0myerr\u001b[0m\u001b[0;34m=\u001b[0m\u001b[0myerr\u001b[0m\u001b[0;34m,\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m   2502\u001b[0m                            \u001b[0mxerr\u001b[0m\u001b[0;34m=\u001b[0m\u001b[0mxerr\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0mlabel\u001b[0m\u001b[0;34m=\u001b[0m\u001b[0mlabel\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0msecondary_y\u001b[0m\u001b[0;34m=\u001b[0m\u001b[0msecondary_y\u001b[0m\u001b[0;34m,\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0;32m-> 2503\u001b[0;31m                            **kwds)\n\u001b[0m\u001b[1;32m   2504\u001b[0m     \u001b[0m__call__\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0m__doc__\u001b[0m \u001b[0;34m=\u001b[0m \u001b[0mplot_series\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0m__doc__\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m   2505\u001b[0m \u001b[0;34m\u001b[0m\u001b[0m\n",
       "\u001b[0;32m/opt/conda/lib/python3.6/site-packages/pandas/plotting/_core.py\u001b[0m in \u001b[0;36mplot_series\u001b[0;34m(data, kind, ax, figsize, use_index, title, grid, legend, style, logx, logy, loglog, xticks, yticks, xlim, ylim, rot, fontsize, colormap, table, yerr, xerr, label, secondary_y, **kwds)\u001b[0m\n\u001b[1;32m   1925\u001b[0m                  \u001b[0myerr\u001b[0m\u001b[0;34m=\u001b[0m\u001b[0myerr\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0mxerr\u001b[0m\u001b[0;34m=\u001b[0m\u001b[0mxerr\u001b[0m\u001b[0;34m,\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m   1926\u001b[0m                  \u001b[0mlabel\u001b[0m\u001b[0;34m=\u001b[0m\u001b[0mlabel\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0msecondary_y\u001b[0m\u001b[0;34m=\u001b[0m\u001b[0msecondary_y\u001b[0m\u001b[0;34m,\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0;32m-> 1927\u001b[0;31m                  **kwds)\n\u001b[0m\u001b[1;32m   1928\u001b[0m \u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m   1929\u001b[0m \u001b[0;34m\u001b[0m\u001b[0m\n",
       "\u001b[0;32m/opt/conda/lib/python3.6/site-packages/pandas/plotting/_core.py\u001b[0m in \u001b[0;36m_plot\u001b[0;34m(data, x, y, subplots, ax, kind, **kwds)\u001b[0m\n\u001b[1;32m   1727\u001b[0m         \u001b[0mplot_obj\u001b[0m \u001b[0;34m=\u001b[0m \u001b[0mklass\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mdata\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0msubplots\u001b[0m\u001b[0;34m=\u001b[0m\u001b[0msubplots\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0max\u001b[0m\u001b[0;34m=\u001b[0m\u001b[0max\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0mkind\u001b[0m\u001b[0;34m=\u001b[0m\u001b[0mkind\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0;34m**\u001b[0m\u001b[0mkwds\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m   1728\u001b[0m \u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0;32m-> 1729\u001b[0;31m     \u001b[0mplot_obj\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mgenerate\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0m\u001b[1;32m   1730\u001b[0m     \u001b[0mplot_obj\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mdraw\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m   1731\u001b[0m     \u001b[0;32mreturn\u001b[0m \u001b[0mplot_obj\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mresult\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n",
@@ -3221,32 +3228,9 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 16,
+   "execution_count": null,
    "metadata": {},
-   "outputs": [
-    {
-     "data": {
-      "text/plain": [
-       "<matplotlib.axes._subplots.AxesSubplot at 0x7fdba2453518>"
-      ]
-     },
-     "execution_count": 16,
-     "metadata": {},
-     "output_type": "execute_result"
-    },
-    {
-     "data": {
-      "image/png": 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\n",
-      "text/plain": [
-       "<Figure size 432x288 with 1 Axes>"
-      ]
-     },
-     "metadata": {
-      "needs_background": "light"
-     },
-     "output_type": "display_data"
-    }
-   ],
+   "outputs": [],
    "source": [
     "sorted_data['inc'] = sorted_data['inc'].astype(int)\n",
     "sorted_data['inc'].plot()"
@@ -3261,32 +3245,9 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 17,
+   "execution_count": null,
    "metadata": {},
-   "outputs": [
-    {
-     "data": {
-      "text/plain": [
-       "<matplotlib.axes._subplots.AxesSubplot at 0x7fdba02af278>"
-      ]
-     },
-     "execution_count": 17,
-     "metadata": {},
-     "output_type": "execute_result"
-    },
-    {
-     "data": {
-      "image/png": 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l/tyYqRctFBa+eJeXWZgWKKGW48FwlFBEUxlnoVjxlOFAOF+nVVJY1zExhlLuFJdXLkknhvJz4Iok69/VWq8yfx4BUEotB64HVpj7/FApZX2K7gBuAhaZP9YxPwL0aa0XAt8FvmEeqwG4FTgTWAPcqpSqn/QrFAoeK4ZS5rDjshtzwEvpjtISzPK4oLzdpqh02WN31sLxMTyey8sUlFJzoRYqEwqK1vpvQG+ax7sG+I3WOqC13gu0A2uUUq1Ajdb6Ja21Bu4Fro3b5x7z8e+Ai03r5XJgrda6V2vdB6wlubAJRY4/ZIxutdkUSinKHKU1w8KqkahMmNVRXeaMfREKx8eQP4RSUJGklxeU1g1KIXM8WV6fVkptMl1iluXQBhyM2+aQudZmPk5cH7WP1joMDACNKY4llBje4OgusWVOG/4SmmERy2JL8O9XlTkYCpRWvU220VpzsNc7ZjDZUCBMldsRmzdjITGU3DJVQbkDWACsAo4C3zbXVZJtdYr1qe4zCqXUTUqpdUqpdV1dXanOWyhAEtuOG/2XSsfn7TUtlMS75yq3Q1xeabLhYD8/eLqdt3//ec7/n6f584Yjo54f9ofHBORBXF65ZkqCorXu0FpHtNZR4CcYMQ4wrIhZcZvOBI6Y6zOTrI/aRynlAGoxXGzjHSvZ+dyptT5da316c3PzVF6SkEcSR7eWl1hDP0/AslASXV4iKOlwdMDHtT94gW8+toOoeUt5pN83apvhQHhM/ARGXF6BErpBKWSmJChmTMTiHYCVAfYgcL2ZuTUPI/j+qtb6KDCklDrLjI/cAPw5bh8rg+tdwFNmnOUx4DKlVL3pUrvMXBNKDF9wtKC4S8xCie8EEE91mUOyvNLg6IAfgB/9w2oe/dz5uB22MddtyB8eU9QIcVleJeRCLWQmrENRSv0auBBoUkodwsi8ulAptQrDBbUP+DiA1nqrUuoBYBsQBj6ltbb+Jz+JkTFWDjxq/gDcBdynlGrHsEyuN4/Vq5T6CvCaud2XtdbpJgcIRYQvGKHCGV+jUVoN/WIWSmJQ3i1B+XToHQ4C0FpbBhjJDIMJ120oEKau3Dlm35jLq4SSPAqZCQVFa/3eJMt3pdj+NuC2JOvrgJVJ1v3AdeMc627g7onOUShuvKFIrCkklN4c8FgMJVlQ3i9B+Yno9RiC0lDpApJbdsP+EDPry8fsWyZ1KDlFenkJeccfjIwKWJe77CXloohleTnHxlA8wQiRqLRfSUWv1xCUxqoRQUkU4qFxgvJ2m8JlL62swUJGBEXIO95QeFQMpdTmgI+kDY/N8gKplp+IXk+QMqctNk+myu0Y4yocDoTHtK63cDtt4vLKESIoQt7xBaMx1wRQcoWN3mAYh3mnHI/1BSiCkpqe4SANFa7YvxOz42LTGt1jYyhgBOYDYqHkBBEUIe/4guFRAWt3iX0BeAJGFpvZvi6G1XdK4iip6fUEaKgaEZQqt3OUCFuPk6UNQ+nVNRUyIihCXtFajylsLC+xLwBvMDwmZRjiXF6S6ZWSXk+Qhkp37N/VZQ4G40TYEuRkMRQwsus8YgXmBBEUIa8EI1GimiQxlNKxULzByJj4CYy4vKS4MTW93iCNlSMWSo2Z5RU1kxlGOg0nFxSp98kdIihCXol14k1ovVJKc8ATh2tZxARFvuxS0jscjKUMg+Ha0tpIN4fxOw3HtpcWNzlDBEXIK1aPpYoECwVKp6GfJxCOZSjFIzGUifGHIniCkVGCknjdYtMax3F5VZc5xULJESIoQl7xxmaFjLZQoHSK0XyhyJjW9SAxlHRILGqEsddtaJzhWrHtpYA0Z4igCHklfp68Ram1HB/PQqlw2bEpiaGkIpmgWK5Cq/2KJSypYihyjXODCIqQV5K7vIzHpZI6PF4MRSllFOmJO2ZcLEFpTCIo1nUbNmfKjOvycjsIhKMES2isdKEigiLklaRBeYfNfK40vgC8wQiVKfz7g+KOGZfkFsroGMq+Hi/VZY6koh2/vQh39hFBEfJKyhhKyVgoo1vLxFNdNraNiDBCT8xCGV2HAiOurjcO9LNqVt2YwlELy3KROEr2EUER8ooVJylPaA4Z/1wxEwxHCUV00qA8SErrRPR6AthtalR8ZEQgwngCYXYcG+TU2fXjHULqfXKICIqQV6wYyigLxVE6WV6WSy9ZUB6k6G4iej1B6itco2bFV7ocKGVYHJsODRDVcOrsunGPUSWCkjNEUIS8MtLaffSALSiNOeAeaxbKeBZKmVNcMSnoHAzQFNfHC8BmU1S5HAwFwrxxsA+AVTPHF5QaiaHkjAkHbAlCNrHcWmWukXubUkobHmldLxbKVNjX42HRtOox61Yq8KE+H/ObKqmvdCXZ20BiKLlDLBQhr3iD4dgQJAu3aaEESkBQLLGQGMrkiUQ1B3t9zG2qHPOcVaz4xoF+VqVwd4GMCcglIihCXvEFo5Q7R7d2Ly+hSvk+c9pgXUXyO2hjVkdUpjYm4Ui/j2AkyrymijHPVZc5eW1fH93DAc6a15jyOBJDyR0iKEJe8YXGptRaLq9SiKH0e8fWUcRjxVZK4bVmmn09HgDmNI61UKrLHPR6grjsNi5f2ZLyOG6HHZfDJoKSA0RQhLziC46ehQLgtNuw21RJxFD6PIbfvr4ieZ8pK7biDcqXXSL7ug1BmZfM5WVet4uXTaO2PPm1jafaLf28coEIipBXvEkEBYxq+VJxednUSKZRIhWWNVZCI48zxb4eL+VOO9Oq3WOes6rfr1nVltaxJPkhN4igCHnFF4okrSIvd9lLolK+zxukttw5qo4iHsvl5QkU/2vNNPu6PcxprEhaAT+3sYKWmjIuWtqc1rGqpEFkTpC0YSGv+EPJLRS3w14aLi9vKGVKa3kshiJfdons7fGwOEnKMMBNb5nPjefMxe1Inj2XSLXbKS1ucoBYKEJeGQ5EqEwyHrdUxgD3e41K7/GwKui94vIahZEy7E2aMgxGp+ayJDci41GVMIdeyA4iKEJeGQ6Ekg5GKnPaSyKG0usJjRuQhxGXlwjKaI70+whFdNKU4akgMZTcIIIi5JUhfzjpHItyZ2m4vPq9wXFrUCAubVgEZRQdg34AWmrLM3K8aikgzQkiKELe0Foz5A8nnbRXViKC0ucNTmChiMsrGf3e1OnWk8WaK6+1FJBmExEUIW/4Q0aFeHKXlw1fkbu8fMEI/lA0raC81KGMpt9nCEpd+fjXbjJUlTmIRLUUkGYZERQhb1iFZlVJLBS30170vbystiupg/ISQ0mG1WGgNmMWyuihXEJ2EEER8sag+eGuSebyKoG04RFBGf9L0Wm34bQrEZQEBn0hbMqIfWQCK043KIKSVSYUFKXU3UqpTqXUlri1BqXUWqXULvN3fdxztyil2pVSO5RSl8etr1ZKbTafu12Z1UpKKbdS6n5z/RWl1Ny4fW40/8YupdSNmXrRQmFgZd0ki6GUu2z4w8Xt8rLiAKmC8mDEUXzi8hpFvy+UsiB0stQkzKEXskM6FsrPgSsS1m4GntRaLwKeNP+NUmo5cD2wwtznh0opK1n8DuAmYJH5Yx3zI0Cf1noh8F3gG+axGoBbgTOBNcCt8cIlFD8xl5c7SQylhCyU8RpDWlS47GKhJNDvDU0oxJOhSlrY54QJBUVr/TegN2H5GuAe8/E9wLVx67/RWge01nuBdmCNUqoVqNFav6SNNIt7E/axjvU74GLTerkcWKu17tVa9wFrGStsQhFjpXGOl+XlC0WKOiunz2O1rk8dByh32fEWuXhmGstCyRQyVz43TDWGMl1rfRTA/D3NXG8DDsZtd8hcazMfJ66P2kdrHQYGgMYUxxJKhOGUgmJDawhGitft1edNL1OpwmXHK3fOoxjwBicU4slgxVAkKJ9dMh2UT+bw1CnWp7rP6D+q1E1KqXVKqXVdXV1pnaiQf6xWGONVykNxD9nq8wapcjtwOVJ/zCqcDnF5JdDvC1GXUQvFOJa0X8kuUxWUDtONhfm701w/BMyK224mcMRcn5lkfdQ+SikHUIvhYhvvWGPQWt+ptT5da316c3N63UeF/GO5H5JVyluCUsypw0YcYOIvxXKXPWl9hD8U4T/+tIXHtx7LxukVNP3ezLq8YhaKWIJZZaqC8iBgZV3dCPw5bv16M3NrHkbw/VXTLTaklDrLjI/ckLCPdax3AU+ZcZbHgMuUUvVmMP4yc00oEYYDYSpdduxJMnlKYWpj3wSNIS0q3WOD8v5QhJvuW899L+/np8/tzdYpFiSRqGbQH6I2g0F5u01R6bJLDCXLTJjkrZT6NXAh0KSUOoSRefV14AGl1EeAA8B1AFrrrUqpB4BtQBj4lNba+qR8EiNjrBx41PwBuAu4TynVjmGZXG8eq1cp9RXgNXO7L2utE5MDhCJmyJ+8MSQYMRQobpdX2haK0zGml9fvXz/E33Z2sby1hjcO9hmTLZPMjSlFhvwhtCajLi8wMr0khpJdJhQUrfV7x3nq4nG2vw24Lcn6OmBlknU/piAlee5u4O6JzlEoTob84aRV8mCkDQNFnTo86AvRVj9xc0MjbXj0F92hPh9Ou+KfL1/Ch37+Gq8f6OPchU3ZOtWCYqR+J7OCUl3mZCggMZRsIpXyQt4YDiRvDAkjPa6KWVAG0kx9rXDZ8SRYKF1DAZqq3JwxrwG7TfHS7p5snWbBEevjlWFBqSrCjsOBcIQXd3fzxoG+ovgsyMRGIW8M+sPjfuFaLq9ijaFordMWlHKXnWDYaJRpxZO6hw1BqXI7OKmtlpf2nECCYvXxylBjSIvqIhwD/MfXD3PzHzYD8L4zZ/Pf7zgpz2eUGrFQhLwx7A+N26vJ7SjutGFvMEI4qtO2UIx9Rr7suoYCNFe7AThrfiMbD/afMB2JB7JkoRTjkK2uoQAA5y5s5IltHQVf6CuCIuSN8WahQFzacLg4LRSr3iE9QTGuQXxgvmsoQHOVISirZtURjmp2d3qycKaFRyyGkuGgfLXbWXS9vIaDYVwOG9esaqNzKMD2o0P5PqWUiKAIeSOVoBR7DMW6y56chWK81mhU0+MJ0lRtuHzmNBpjcPf3nhiCMplrNxmKMctr2B+m2u3gwsVGfd0zOzsn2CO/iKAIeSEcieILRZI2hgQocxR32vCAd+qC0ucNEonqmIUyu8EUlB5vNk614Oj3Gq5Qhz2zX0/VZQ48wQiRaGG7jeIZDhiZkNNqyljWWsOzOwq7E4gIipAXUrWuh+IvbLTusmvGqbOJpzw2Bti4Jt3DRlC6yYyhVLodNFW5OXCiCIovmLHBWvEUY7X8sD8cO+8LlzSzfn9fQbePEUER8kKqTsMQ38uruAVlKhaKFYi1LBQw3F4nissr021XLIpxJspwYERQLlk2jXBU88S2jjyf1fiIoAh5YSJBsdsUTrsqXpfXcQhK97ApKNVxgtJQccJYKPt7PMxMoyB0shTjTJR4QTl1Vj1tdeU8tDFpS8OCQARFyAtDKToNW5Q5i3fI1qAvhFLjC2Y8sSyvkPFFZ1koTXGCMruxgqOD/qLNekuXUCTK/h4vC6dVZfzYxTgTxYqhANhsiref3Mpzu7pjtTqFhgiKkBdSdRq2KGZBGfAZgeV0RtiOcXkNB3A7bKNqdOY0VqA1HOz1ZeeEC4T9PR7CUZ0VQSnGmSjxMRSAq0+ZQTiq+euWwuxALYIi5AVPMLXLC4xq+WIWlHQDy1aKtFWH0m22XTEacxvMbqgE4ECJx1HaO4cBWNCcDQul+GaixFsoACtm1DCroZyn3izM9GERFCEvpGWhOOxFHUNJN7Bc6XLgtKuYq6trODAqfgInTupwdgWluGIowXCUQDhKlWvkM6KUYuWM2th1KjREUIS84DE/1JUpBKXcZcdfpDGDyQiK3aZY3lrDxkP9wEhjyHiaqlxUuOwxQfnmY2/yf/+8hXARj0hORnvnMDNqy1K+L6ZKscVQrM9IYkfuRdOq2NfjKch4mgiKkBc8gTBKjcQPklHmsI+ZE1IspGp8mYxTZ9ez6dAA4UiU7iQWilKK2Q0VHOg1BOXPG45w70v7+cyv3yAYLh1Rae8aZkEW4icA5U5jmFuxxFAsSyrRil8wrYqohn3dhWetiqAIeWEoEKbK5RgVJ0jE7bThL9Ivy8npkMpzAAAgAElEQVRYKACnzq7DG4zwyJZjdA8HWTx97JfqnMYK9vd4CEWiHB3ws3h6FY9uOcbH71tXtLGmeKJmv7JsuLvAEGWjhX1xxFDGK/5dNK0agF2dhdfXSwRFyAueQHhCt0aZ0160M+UHfKG0quQtTp1VD8A3Hn0Tm4K3ndw6Zps5jZUc7PNxuM9HJKr56Pnz+do7T+KZnV3c/PtNGTv3bOALRthwsD/lNkcH/fhCkaxkeFlUuR0MFUkMZcRCGf0+mt9ciU3Bro7Ci6OIoAh5wROIUOlOPdK2vEjThv2hCMFwlJpJWCizGspprHRxuN/HuQubmFZdNmab2Q0VBMNRXt3XG/v3e9fM5r1rZvP4to6Cjqf84uX9XPuDF3ihvXvcbfZ1Gxls85sqs3YexTQTxXLNJX5Oypx2ZjVU0N4lgiIIgOnymuAO3kgbLtwvyfGYSrdcpRSnzq4D4NpVbUm3sboOP7/L+FK2Mr/Ont+INxhh65HBKZ9ztnnNFMH/+POWcWM+VoeAaTXupM9nguZqN0cHiqOWZyhFv7tF06poFwtFEAw8gTBVE1goZU57UTaHnGr79fMXNVNf4eTylS1Jn59j1qK80N6Ny25jeo1hxayZ1wCMfGkXGlprNhzsZ25jBXu6PNz70r6k21lNMRsrsycoi6dX0945XBQdh4f9yV1eAAunVbOne7jgrFIRFCFjaK356XN7eOrNiZvXeQJhKl0Tx1CK0eU1VUH5wFlzeOmWi8etzZlRV4bDpujxBJlZXx4bFzy9pow5jRW8urcwBeXogJ/OoQAfOncey1pr+Nuu5G6vnuEAdpvKSmNIiyXTq/GHohzsLbwMqUTGSxsGWDitilBEs7/AXocIipAx+rwhvvrwdj7883V8+levpxxXOuQPJ/2gxFPmsBEIRwt+7GkivR7jTruhcnIz0W02FeuynAyH3Uab2TRxlunuslgzt4HX9vUSLcA7bysYv2pWHctba3jzaHLXXM9wkIZKV1rtaqbK4hYjQ2pHR+FlSCViubwqkrwn2uqM90HHgD+n5zQRIihCxjjUZ9wtrZ5Tz182HWXjoYFxt/UEwymr5AHKXNYY4MIy6yeix3LdVE1OUNLBipvMThCUM+Y10OcNFWSg9o0DfbgcNpa11rCstZrOoQA9Zrwknh7P2ILOTLPIzCDbeazwBcXq45VMYJvNaZ5dSa5jPhFBETLG4T4j2PlPly3BZbeN22Zba51e2rBjdI+rYqHXY3zIJ2uhpIMVmE8UlFWzjID+9nHu/vPJhoP9rJxRg8thY2lLDQA7knyhdw8HacqCCMdT6XYwq6G8KCyU4UBo3JsuK85kxZ0KBREUIWMcMgVl+YwaLljSzF82HUnqggmEo4QiemILxRqyVYAtJlLRPRyk2u3A7UiddDAVrMB8ostrhukCOVpgLhCtNVsOD3LyTEPwlrYaLqftSQSlxxOgMQsinMiS6dXsLAJB8QQi47qFa8udRjxNLBShVDnU56Xa7aC23MnVp8ygYzCQNPPIM05LiUTKnMU5V77HE8yKuwtgZVstdptiqRkLsKhyO6guc3C0v7BSYjuHAvhCERY0G0LYVOWmqcqdNI7SMxykMcsuLzAyvfZ0eQq+Zc1QCiveZlM0VrliqdZg1Pr89Lk9uTq9pIigCBnjUJ8vFjS+ZNk0XHYbT+/oGrOdJ2BYHBO5vMqLdAxwryeQFXcXwNkLGln3b5cwN0nx34zaco4UmIVi9R6b3Thyvstaq3kzwULxBsN4g5GsCXE8S1qqCUc1e7oLL94Uz7A/NGomTiJNVe5RLq+/bDrC41vzOx5YBEXIGIf7fcysN1wxFS4HLbVlHElyxzwUMNJq06lDAYquFiXbd9r144hVS21ZwRXtWWOL42M+S1sMl1N8DYWVyNCUxRqUkb9vxHEKMd4UT/z432QYgjJiofR5QtRXZi/lOh1EUISMoLXmUJ9v1Czwlpoyjg2OvWO2LJRkBVvxuGMur+ISlFwEl5Mxo66MYwVmoezv9WJTI2muAKfNricQjvKPD2zEaw5a6/FkLzMukQXNlbgdNrYcLmxBSRVDAVNQhkYEpdcbzJplnC4iKEJGGPCFGA6ERwnKtBo3HUkFJXmPokQsCyVQRDGUaFTTl6cPdmttOd3DwYKak3Gw10trbTkux8hXzRUrW/iXK5bwl01H+OrD2wFiweVcxFAcdiOFecvh8dPaC4Eh//hZXgBN1S66h4NordFa0+8NUl8hgiKUAFaGV6KF0jHoH1OYOJRuUN5RfDGUAV+ISFRntX3IeLTWGq1YCslKOdDrHZPirJTi/1y4kLcsambDAaPoMVa7kyMhXtlWw7YjgzkpBI1E9aT/TjgSnXCmTnOVm6C53XAgTCiii9tCUUrtU0ptVkptUEqtM9calFJrlVK7zN/1cdvfopRqV0rtUEpdHre+2jxOu1LqdmUOyVBKuZVS95vrryil5h7P+QqZxxsM8+4fv8QPnm4HiMVQwPDp+0NRBn2ju7umaikRjzV8y1tEdSg9HutOOx8uL0PMj/QXjqDs7/HGamcSWTitij3dw0Sjmu4cX7eVM2oZCoRjSQPZ5AsPbOATv1g/qX36vEacMdX1sIpAu4cD9HmM7UvBQrlIa71Ka326+e+bgSe11ouAJ81/o5RaDlwPrACuAH6olLJ8HncANwGLzJ8rzPWPAH1a64XAd4FvZOB8hQzy3K5uXt3by6NbjgEkuLzMO+YEt1c6438BmsyphYVWDZyKnhw0OBwPy0IplMC8NximezgwpmbGYuG0KvyhKIf7ffQMB6lw2amYoL9bpljZVguQ9Q7NgXCEx7d2xMY7p0s67XsssekZDtLrNbYvxaD8NcA95uN7gGvj1n+jtQ5orfcC7cAapVQrUKO1fkkbvpF7E/axjvU74GKVasSfkHOefrOTareDcxY0Mq3aPcpEbzEFJTGOYs2jmKg5ZJXbQaXLnjQOU6jkMricSGttYRU3Huw1hC3R5WVhDdJq7xymZziQ02u2aHoVTrtiy5HsxlFe39+PLxShYzAwKddtLKaU4sZktIViCkqeLZTjvR3QwONKKQ38WGt9JzBda30UQGt9VCk1zdy2DXg5bt9D5lrIfJy4bu1z0DxWWCk1ADQC40/pEXJGNKp56s1O3rKkmduvP5Uhf2jUSN+WFBZKhcse65abiuk1ZXQOFpOFkj+XV7nLTn2FM2mqdj7Y32MMzBrX5dUcJyieYE6tOrfDzuLp1VkPzD+3a6QO63C/L+3xxuncmMQLinVzVtQxFOBcrfVpwJXAp5RSb0mxbbJvD51iPdU+ow+s1E1KqXVKqXVdXWML6YTssPXIIJ1DAd66ZBp2m6Iu4e7IGpSU2BHVE5y4j5fFdDOwX2i8sqcn6ZdRT57vFFtrywvGQokVNY5jodRXumisdLHt6CCbDw8wL4uTGpOxckYtW48MZrWb9fPt3VSascDJtMxPx+XVUOnCpqB7KEBfzOVVxIKitT5i/u4E/gisATpMNxbm705z80PArLjdZwJHzPWZSdZH7aOUcgC1wJheHlrrO7XWp2utT29ubj6elyRMgqfe7EQpuHBJ8mte5rRTV+GkY2j0F9xwIDJhhpfF9Bp30lqWfOIPRfjgz17j6v/3PF/642ZCCQV6dRVOnPb8JFDOqEteTJoP2juHaah0pcxUWjCtir9sOkK/N8Q7Tk0+qTJbrGyrodcTzKgAR6KaV/b0oLWm1xNk8+EB/s6cwHmwL/3/lx5PEKVS35jYbYqGShddw0F6PUEcNpWysj4XTPldr5SqVEpVW4+By4AtwIPAjeZmNwJ/Nh8/CFxvZm7Nwwi+v2q6x4aUUmeZ8ZEbEvaxjvUu4CldbMMxSphNh/pZNK0qZe1AS00ZxwZGu6yG/aEJa1AsLJdXIf23v7K3F18owlsWNfOrVw7w/Sd3xZ7LVYPD8VjQXMWeLk9BTPJ789gQS6ZXkyrsaQ2KmlFbxrkLm3J4drDCDMxn0u31pzcO8547X+b+1w7ysxf2ojW8b81sXHYbhyZhofQMB6ivcE3oFm6qctM1FKDPG6K+0pXyWueC47mNmg48r5TaCLwKPKy1/ivwdeBSpdQu4FLz32ittwIPANuAvwKf0lpbUapPAj/FCNTvBh411+8CGpVS7cAXMDPGhMJgT7cnFlgdj2QuK88kLJRpNWUEI1H6zTTKQuCZHZ24HTZ+/IHVvGv1TP7f0+2sM5tgdg/nNhaQyNLWaoKRKHu7PXk7BzDiazs7hliS0MQyESuO8q7VM9OKqWWSZS012BRsyWCm12NbjWzH2x7Zzo+f3cO1q2Zw0sxa2urLY7Va6dDrSa84dnZDBXu6hunzBKmvyG+GFxxHUF5rvQc4Jcl6D3DxOPvcBtyWZH0dsDLJuh+4bqrnKGSPYDjKgV4vbzupNeV202vcY3omDQfCzKgrS+vvxDLFhvx59w9bPLujizPnN1LmtHPr1ct5blcXP3p2Dz+d28C+bg/n5fhOO55Yn6pjQyyanvrLPJsc6vPhDUbGdEVO5NyFTSycVsV71szO0ZmNUO6ys3BaFVszZKH4ghH+tquLC5c08+LuHtwOG1962zLASKc/2DcJCyVNQVkxo5a12zuocNvznuEFUikvTJEDvR4iUc385tSB1JaaMrqHA6NcMH3eILXl6b35p5uB/UKp/j7Q42VPt4cLFxtxo+oyJ2fNb2TbkQF6hgN0DgVY1lqTt/Nb0FyFw6bGHbObK6wBVosnEJQlLdU88YULRvX6yiUrzMB8JnhuVxf+UJSPnT+fn9xwOj+58XSmVRs3RLMaKiYdlE/HdbpiRg1aGwky+c7wAhEUYYrs7jJcKhOlQc6sryCqR1qzhCJROgb9tKVpoUw3LZRCSB3WWnPnc7uB0YkIK2bUcGTAzyt7DbeXNUQqH7gcNhZOq0o6ETGX7DhmfEkvzqOVlA4rZtRwbNBP19Dxv7/WbuugpszBmnkNXLC4mbPmN8aem1VfQZ/X6HeXDunW5axoM25etM5/hheIoAhTZI8pKBNZKNYdqnXHemzAT1QTm5syEbHU4wLI9Pr+U+384uUDfPjcecyPE9LlrUZw9w+vHwZG3E75YknL2HkjuebNY0PMaihPO1aWL6yK+Y0HJ1fJnkggHOHxbR28dem0pBl+sxqM93s6Vkokqun3hWhIIxbXUlMWs0waxOUlFCt7uoZprnZTXZY6ELjIDNpbd8yWpdJWl7w2IRG3wyjWy3fqcCAc4fYnd3Hlyhb+3fSLWywzLZJndnTSVOWiuTp/QXkwBO1wv48BX/4SGXYcG2LJ9PwKazqcOruO6jJHrHXQVHn6zS4GfCGuGSf1ea45YCzZBNNE+rxBtE6vUaZSihUzjOssFopQtOzuGo6NdU1FpdvB7IaKmIVy2KyRSNdCAStTLL8urz1dHsJRzZUntWJLyEZqrHLTUlNGOKrzbp3AiMstX24vbzDM3m7PhAH5QsDtsHP5ihYe33rsuNr+//GNQzRVuTl/nISMFTNqWDO3ge+u3Um/N5h0G4t0ihrjWW4KSkOe+3iBCIowRfZ0e0a5fVKxeHo1O80vt8OmhWI1MkyH6TVldA5NzUKJRvVxuzMAdlpB5unJX7P1oZ4oTTYXLDeTArZluU/VeLzY3kM4qjl7QePEGxcAV58yg6FAmGeTjKtOh35vkKfe7OTvTpmBY5yCVqUU/3XNCgb9Yb71+I6Ux+ueZPueFTMMt11ip4p8IIIiTMjhfh9bDg/Eigs3HOyn3xtifpqtMpa2VLOn20MgHOFwv5fmandseFY6tNaWcbDXO6Xixoc2HeGaH7zAtuPM5NnZMYTDppjflFxQLLdDIdyVT6t201Tlzmh9xWR4ekcnlS47p8+tn3jjAuCcBY3UVzh5aNPRSe+rteYbf91BKKJ552mpK/2XtdZw9cmtPLzpaMr3smWhpFvPdPHSaXz8gvmcOa8h/RPPEiIoQkq01nzk56/x9u8/z1W3P88Hf/Yq1/3oRabXuLl8RUtax1jcUk0kqtnT5eFwv2/SKaInz6yjzxtif8/kZ1es3dYBjFgYU2XHsWHmNVWOmjwYz2lz6lEKVs2qO66/kwmUUqxsy89EQq01z+zo4tyFTbgd6d805BOn3ca1p7bxyOaj7Jrk++QHT7fz61cP8MkLF8QC/KlYNct4L6dy4U7W5VXpdnDLlcty1vo/FSIoQkpeP9DHm8eG+LtTZlDtdtA9HODqU2bw18+9Zdw5F4lYd+07jg1xuM83qfgJwOo5xp3u+v19k9ovHIny3C6jMfWeruFJ7ZvIrs6hlCmwFy5u5rl/uSivxYTxnNRWy67O4ZxPu9zVOczhfh8XLZ028cYFxKcvWkily86X/7ItbUtYa82Pnt3DJcum8y+XL0lrH6tGKbHYN57dncOUOW0FUfk+WURQhJT88pUDVLkdfO2dJ/HAJ87mL585n++8e9WkMkrmNVUasycOD3Ck38/MSVooi6ZVUe12sP7A5ARlw8H+WKbTnuNoReINGpP9UgmKUmrUtMp8s7KtlkhUp/ziygZPbjd6wY7XMLRQaaxy8/lLFvPcrm7uen5vWqJydMDPcCDMBUua0+6htdQSlGPJ/1+01jyxvZPzFjaNG48pZIrvjIWcMeAN8fCmo1yzakba7eaT4bTbOG9hE7969QDBSHTSForNpjh1Tj2vT9JCeXpHJ3ab4rTZdcfV26q9cxitYUlLekkIhcDKLDQ+nAitNX964zCnzKqLDfsqJj5w9hwuXT6drz68nS/9ccuE1l17p2H1LkwzOQWgttxJW105248md63t6BjicL+PS5ZNT//ECwgRFGFcHtt2jEA4yrtPnzXxxhPwxcuWxGbDT6XNxurZ9ezoGGLIn35txTM7ulg9u55TZhmCMtWOxTs7jC+OQnFnpcOMWqPgbXMOBWXL4UF2dAxx3eqZE29cgDjtNn78D6v5Pxcu4NevHuDq7z/P7hSu0pigTNAgNZFlrTXjWo5PmDG/ty4rLpehhQiKMC5Pbu+gtbaMk2dOHGyciJVttbFGkpO1UMCIo2htuLHSoWPQz9Yjg1y4tJn5zVV4g5Ep17JsOtRPudPOnDRjRoWAEZiv5YX2Ht6YpKtwqvxu/UFcDhtXnzwjJ38vG9hsin+5Yin3fWQNfd4g7/nxS7w5jnuqvWuY2nInTZOczrm8tZo9XWPjW/5QhL9uPcaqWXWxHmDFhghKhvAGwzkPgGYTfyjC33Z2c/GyaRmbsfAfb1/OP16ymMXTJn+nf8qsybXIsGoKLloyLZbePNXA/Iu7e1gzr6HofNo3nj2HIX+Id/zwRR7ZPPmU2MkQDEf588YjXL6ihdoiDCYncv6iZu7/+NnYbYoP3PVq0s92e+cwC6dVTfrzsay1hqgenXn4xLYOTv/qE2w5PMi1q4pYkPN9AqXCB+56lQ/+7NWCGgR1PLy0uwdfKMLFGfTlttSW8blLFo2pNE+H6jInsxsqxvU9J/LMzk5aaspY2lId6zc2lcB856Cf9s5hzimSIr14Ll42nRdvuZjW2jIenkKNxWTYeMioTZponEExsaC5im9ddwpdQwEe3TL2+rV3Dk8qfmJhxbce2ngktnbn3/bQUOniVx89kxvPmTvlc843IigZ4ECPl/X7+3h5Ty/Pt3fn+3QywhPbO6hw2Tl7fuF8kS5rrU4raykUifLczm4uNLNvpleXUe60Tykw/9KeHgDOWZC/GSfHQ5XbwXkLm3hhdzeRaPZudl7a3YNScNb8/BfXZZJzFzQxr6mSX7x8YNR6r8cYuzvZ+AkYrezfu2YWdz2/l9cP9NEzHGDd/l7ecWob5yxsyvvUxeNBBCUJkajm24/vSDvl8hHz7qWx0sV31+4sKivlkc1Hk/qIn9vVzTkLmiZV0Z5tlrbUsLfHgy+Y2rX42r5ehgJhLlxiBDZtNsWCaZU8v6ubYHhyo3FfaO+mttwZa61SjJy3qIl+b4itWWzF8vKeHpa11BRE+49MYrMp3rdmNuv39436PphqQN7iS1cto6WmjH/67Ub+sukoUQ2XLi/OzK54RFCScM+L+/j+U+3c/IfNaYnDo5uPcsrMWr542RJeP9Afu6stdHZ2DPGpX73OTfeuH9UYr3PIz4FeL2vmFVbrjGWtxjChHRNUM//42T3Uljs5f9GIVfGZty5iR8cQ33zszUn9zRd393DW/Iacj6fNJJZ1lS3rORCOsH5/36j5H6XEu1bPxGlX/OmNw7G1tduM7sRTFZTqMiffuu4U9nZ7+MpfttFWVx5r31PMiKAkcLjfx7ce30FTlZuNB/t5ekcnQ/7QqImD8Rzq87Lx0ABXntTKO09ro7bcyW9ePZjjs54a//vETpw2Gwd6vdzz4r7YulXvsXpOYbkvlqdRZfzS7h6e3dnFpy5aMKp25vIVLXzgrDn85Lm9bD6U3p36wV4vh/p8RevusmiudrO0pZrnd2VHUDYc6CcQjhZNM8jJUl/pYvWcev5mXr87ntnNT57by9+fNpOZU8hYtDhnYROfuWgh4ajm0uXTi9rVZSGCksB/P7IdreG3nzibWQ3lfOZXb3Dyfz3Oed94mh883U40wQ/9w2d2Y7cp3nZSK2VOO+84tY2/bjlGnyd1i+p88/SOTh7ZfIxPXDCfi5Y08/0n22Nttdft68PlsLGyrbDumGbWGwObxhMUfyjCbY9so7W2jBvOnjvm+X++YglOu+KhTUfG7pyEF3cbXyDFGJBP5KKl03hlb2/SlvbH66J90YyfrJlbWDcgmeT8Rc1sPzrI5kMDfPOxN3nbSa38z7tOPm4R+OzFi/jXK5by0fPnZehM84sIShwbD/bz8KajfOwt85nXVMmtb1/ByrZaPn3RQhZNr+Kbj+3gJ8/tiW2/5fAAv371ADecPSfW1+o9Z8wiGInyxzjzuJAIR6J87N51fOhnrzGroZyPnD+ff71yKUOBML94eT8A6/b3cXJbbcE197PZFEtbqnnjQD+v7u0dlcoZiWr+8f4NbDk8yK1Xr0ga+6kpc3LewiYe2Zy626vFC+09NFe7p+zWKCRuOn8+teVOvvTHzbGbIqNT7puc+/WnpjwCNxrV/PGNw5wxp6Ek0oXH4zxzzskXf7sBDdx85dKMuEEddhufvHBBQbXtOR5EUEy01nzt0e00Vbm46S3zAbhk+XTu//jZfPGyJdz74TXGXcljO3htXy9aa7780DbqK1x8/pLFseMsa61h1aw6/t/T7VkNgk6Vu57fy9ptHXzh0sWs/ccLqC13srSlhgsWN/PzF/cxYAZvVxdo6/GVbbVsPjzAu3/8Erc/uSu2/sOn23l0yzH+/W3LuGLl+F2QrzyplUN9PrYcTp1wobXmxd09nLOgsSRcEfWVLv7tqmWs39/HTfet49evHuDz92/gjmd2c2TAz89e2Dul4z67s4sDvV4+cPacDJ9xYbGyrZbacic7O4a5YHFz2o1RTzREUEz2dnt4/UA/n714UdI52Eopvv73J9FWV86//n4TT27v5NV9vfzjJYuoLR99Z/bd96yizGHj+jtfpr0zv7O949nX7eE7a3dy6fLpfOatC0fdxX/8gvl0Dwd5/10vE4poVs8uTEH57MWL+OH7T+OMufU8uPEIWmt2dQxx+1O7uPqUGXz0/Pkp979s+XQcNsXDExT6tXcO0z0cKAl3l8U7T2vjsxcvYv3+Pm75w2Ye3nSUT1ywgKtOauG+l/YzOIm2Nk9u7+B/n9jJHc/uZlp1+qMMihW7TXHuQuO98P4zS1s8j4f8N9AvEOY3V/HMP11IU9X4Q22qy5z81zUr+NDPXuPTv36dtrpy3nPG7DHbzWuq5LefPIe33/4ct/xhM/ffdPaUivkyzdce3Y7TbuMr16wcc9d99vxGLljcTHvnMG87qZVzxxllmm8aKl1cdVIrnkCYf/7dJtbt7+O2h7dT5Xbwn1cvn3D/ugoXFyxu5u4X9nLa7DouG+eL8IV2K35SmNdhKiil+MKli/nURQs42u9nRl05LoeNLYcHeGTzMX7+wj4+e/GiCY/zzI5OPn7fesKm6+xzFy8ad05MKfH+M+eglOKiIuuknEtK/10wCawPWCouWjKNS5dPxx+KpvwgtdWVc8tVy3htXx+/W38oG6c7KTYe7OexrR187Pz5tCQZv6uU4p4Pr+GFm9/KD95/2nF1F84Fl61owWW38Yn71rPhYD9fuXYljSluBuL51nWnsKy1hk/8Yj3/9dDW2ECjeB7adJQFzZUl6dpwO+zMjRsWtrKtlitWtPDDZ9rZ35O6+PP1A3188hevs2h6NU998QK+/95T+cQFC3Jx2nnn3IVN/OB9pxVdC55cIldmCnztnSfxlWtXTjjy87rVMzljbj3/89iOvPb50lrzzcd2UF/h5MPnzc3beWSS2nInb1ncTI8nyIfOncvbJ9GQsN5scfGeM2Zxz4v7eN9PXh4VpN/VMcT6/X2854zj77JcLNz6d8tx2Gz82x+3EBonRX7bkUE+ePerTK9xc8+Hz2B+cxVXnzKDcldhJW8I+UMEZQo0Vbn5wFlzJrxTUUrxuYsX0z0c4MGN6aWqpks0qvmPP23hn367cdwvADCyn275w2aeb+/msxcvorqsdDJxvnDpYj5xwQK+dNWySe9b6XbwtXeezNf//mTePDY0qhj1N68dxGlXvPO04mzDPhVaa8u5+cqlPN/ezVXfey6WMm2xp2uYG+5+hUq3g1989Myi7YYrZJfC9muUAOcubGRpSzV3PbeX61bPPO6MoUA4wqE+H/e+uI/7zDRfXzDC965fhcNuo2PQT225kzKnnVAkyhce2MhDG4/wmbcu5INF3HQuGctn1Bx3S5S/O2UG//3Idn758gHOWdBE55CfP7x+iEuXT08ZTytF/uGsObTUlPFff9nK+37yCpctn86cxgo8wQhPbu9Aa/jFR88smRRXIfOIoGQZpRQfPX8+//Tbjfx23SHebfw9eBQAAAjESURBVLpROof89HlCLGlJv5W7NxjmHT94MdZ65MPnzqO1tozbHtmO22Fj+YwavvrwdsqcNlbNqsMfirLhYD83X7n0hPFzT5Yyp513nTaTn7+4j/tfO8Adz+zGH4qesNfrkuXTOW9RE3c8s5t7X9rH33Z1UeFyMKuhgv9+x0oWTKG7rnDioIqpkWE6nH766XrdunX5Po1RBMNRbrz7VV7e28P71symezjAU292EtVw+/Wn8raT02v5/U+/3cjvXz/E/337chZNq+acBY3YbIrvP7mLb6/dCcAly6Yxs76CjYf66fUE+dj58/mHsyTNMRX7uj1c9t2/EYxEqSlz8LMPrWH1nMJMmxaEbKGUWq+1Pv24jiGCkhv8oQif/fUbPLG9g9baci5f0cLmw/28fqCfT1xgfOknm8PtDYb5xqNvsnZbB0cG/Hz2rQv5wmVLxmx35992c6Tfz7+9bRlOyUKZNAO+EH2eIA1VLmpKKM4kCOkigpKEQhUUi0hUx1o2DAfC/OvvNvHIlqPYlOLyFdO54ey5nDmvgX09Xl7b28tdz+9lZ+cQV65s4ewFTbz3jFmStigIQsbJhKAURQxFKXUF8D3ADvxUa/31PJ/SlInv/1PldvCD95/GwV4vv3h5P7957SCPbD5GpcuOx5z5Mb3GzT0fWsNbFksxlSAIhU3BWyhKKTuwE7gUOAS8BrxXa70t2faFbqGkwheM8NDGI7x+oI+TZtayZm4DC5qrCqLKXhCE0uZEsVDWAO1a6z0ASqnfANcASQWlmCl32Xn3GbNimWCCIAjFRDE449uA+IlVh8y1GEqpm5RS65RS67q6unJ6coIgCIJBMQhKMn/PKD+d1vpOrfXpWuvTm5sl1iAIgpAPikFQDgHxPqCZQGb7mAiCIAjHTTEIymvAIqXUPKWUC7geeDDP5yQIgiAkUPBBea11WCn1aeAxjLThu7XWW/N8WoIgCEICBS8oAFrrR4BH8n0egiAIwvgUg8tLEARBKAJEUARBEISMUPCV8pNFKTUE7Jjkbk1A94RbpUctMJChYxXD8TJ57aDwX++JdP0K/dpZFPI1zPTxsvX+awIqtdbHV3ehtS6pH2BdLvZJcaw7M/x6Cv14Gbt2RfJ6T5jrV+jXrhiuYRH8n6zL5DUUl1fmeegEO16mKfTXeyJdvxPt2lkU8usu6GtYii6vdXqSDc6mso9gINfu+JDrd/zINZw61rXL1DUsRQvlzhztIxjItTs+5PodP3INp86dCb+Pi5KzUARBEIT8UIoWiiAIgpAHSlJQlFKzlFJPK6W2K6W2KqU+Z643KKXWKqV2mb/rzfVLlVLrlVKbzd9vjTvWbUqpg0qp4Xy9nlySqWunlKpQSj2slHrTPE7RTtmcDBl+7/1VKbXRPM6PzGFzJU8mr2HcMR9USm3J9WvJNRl+/z2jlNqhlNpg/kyb8ASykcaX7x+gFTjNfFyNMfFxOfA/wM3m+s3AN8zHpwIzzMcrgcNxxzrLPN5wvl9XMV07oAK4yHzsAp4Drsz36yuW62f+u8b8rYDfA9fn+/UV2zU0194J/ArYku/XVkzXDngGOH1Sfz/fFyBHF/nPGCOEdwCtcRd+R5JtFdADuBPWTwhByca1M5/7HvCxfL+eYrx+gBMjXfQ9+X49xXYNgSrgefNLteQFJcPXbtKCUpIur3iUUnMxVPgVYLrW+iiA+TuZCff3wBta60CuzrFQydS1U0rVAVcDT2bzfAuNTFw/pdRjQCcwBPwuy6dccGTgGn4F+DbgzfrJFhgZ+vz+zHR3/YdSKtmww9HkW0GzrM5VwHrgnea/+xOe70v49wpgN7AgybFOKAslU9cOo6P1o8Dn8/2aivH6mc+VYbi8Ls336yqmawisAh4yH8/lBLJQMvH+A9rM39XA48ANE/3dkrVQlFJOjA/hL7XWfzCXO5RSrebzrRh3ftb2M4E/Yly03bk+30Iiw9fuTmCX1vp/s3/mhUGm33taaz/GULlrsn3uhUKGruHZwGql1D4Mt9dipdQzuXkF+SNT7z+t9WHz9xBGDGrNRH+7JAXFNM3uArZrrb8T99SDwI3m4xsx/IuWS+Zh4Bat9Qu5PNdCI5PXTin1VYxmdp/P9nkXCpm6fkqpqrgvAAdwFfBm9l9B/snUNdRa36G1nqG1ngucB+zUWl+Y/VeQPzL4/nMopZrMx07g7cDEWXL5Ns2yZO6dB2hgE7DB/LkKaMTw4+8yfzeY2/874InbdgMwzXzufzDm2kfN3/+Z79dXDNcOmGkeZ3vc+kfz/fqK6PpNxxh/vQnYCnwfcOT79RXTNUw45lxOAJdXBt9/lRguM+v99z3APtHfl0p5QRAEISOUpMtLEARByD0iKIIgCEJGEEERBEEQMoIIiiAIgpARRFAEQRCEjCCCIgg5Rin1CaXUDZPYfu6J0ClXKH4c+T4BQTiRUEo5tNY/yvd5CEI2EEERhEliNt37K0bTvVMxWoTfACwDvoPRR6kb+KDW+qjZ7uNF4FzgQaVUNUZvuG8ppVYBP8Jo978b+LDWuk8ptRq4G6Op4fO5e3WCMHXE5SUIU2MJcKfW+mRgEPgURjX7u7TWlhjcFrd9ndb6Aq31txOOcy/wr+ZxNgO3mus/Az6rtT47my9CEDKJWCiCMDUO6pHeR78AvoQxoGit2eXbDhyN2/7+xAMopWoxhOZZc+ke4LdJ1u8Drsz8SxCEzCKCIghTI7Fn0RCwNYVF4ZnEsVWS4wtCwSMuL0GYGrOVUpZ4vBd4GWi21pRSTqXUilQH0FoPAH1KqfPNpQ8Az2qt+4EBpdR55vr7M3/6gpB5xEIRhKmxHbhRKfVjjA6u3wceA243XVYO4H8xOrWm4kbgR0qpCmAP8CFz/UPA3Uopr3lcQSh4pNuwIEwSM8vrL1rrlXk+FUEoKMTlJQiCIGQEsVAEQRCEjCAWiiAIgpARRFAEQRCEjCCCIgiCIGQEERRBEAQhI4igCIIgCBlBBEUQBEHICP8fj+P+tgXt1t0AAAAASUVORK5CYII=\n",
-      "text/plain": [
-       "<Figure size 432x288 with 1 Axes>"
-      ]
-     },
-     "metadata": {
-      "needs_background": "light"
-     },
-     "output_type": "display_data"
-    }
-   ],
+   "outputs": [],
    "source": [
     "sorted_data['inc'][-200:].plot()"
    ]
@@ -3319,7 +3280,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 18,
+   "execution_count": null,
    "metadata": {},
    "outputs": [],
    "source": [
@@ -3339,7 +3300,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 19,
+   "execution_count": null,
    "metadata": {},
    "outputs": [],
    "source": [
@@ -3363,32 +3324,9 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 20,
+   "execution_count": null,
    "metadata": {},
-   "outputs": [
-    {
-     "data": {
-      "text/plain": [
-       "<matplotlib.axes._subplots.AxesSubplot at 0x7fdba02295c0>"
-      ]
-     },
-     "execution_count": 20,
-     "metadata": {},
-     "output_type": "execute_result"
-    },
-    {
-     "data": {
-      "image/png": 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\n",
-      "text/plain": [
-       "<Figure size 432x288 with 1 Axes>"
-      ]
-     },
-     "metadata": {
-      "needs_background": "light"
-     },
-     "output_type": "display_data"
-    }
-   ],
+   "outputs": [],
    "source": [
     "yearly_incidence.plot(style='*')"
    ]
@@ -3402,58 +3340,9 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 21,
+   "execution_count": null,
    "metadata": {},
-   "outputs": [
-    {
-     "data": {
-      "text/plain": [
-       "2021     743449\n",
-       "2014    1600941\n",
-       "1991    1659249\n",
-       "1995    1840410\n",
-       "2020    2010315\n",
-       "2022    2060304\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",
-       "2023    2873501\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": 21,
-     "metadata": {},
-     "output_type": "execute_result"
-    }
-   ],
+   "outputs": [],
    "source": [
     "yearly_incidence.sort_values()"
    ]
@@ -3468,32 +3357,9 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 22,
+   "execution_count": null,
    "metadata": {},
-   "outputs": [
-    {
-     "data": {
-      "text/plain": [
-       "<matplotlib.axes._subplots.AxesSubplot at 0x7fdba0209be0>"
-      ]
-     },
-     "execution_count": 22,
-     "metadata": {},
-     "output_type": "execute_result"
-    },
-    {
-     "data": {
-      "image/png": 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\n",
-      "text/plain": [
-       "<Figure size 432x288 with 1 Axes>"
-      ]
-     },
-     "metadata": {
-      "needs_background": "light"
-     },
-     "output_type": "display_data"
-    }
-   ],
+   "outputs": [],
    "source": [
     "yearly_incidence.hist(xrot=20)"
    ]
-- 
2.18.1