diff --git a/module3/exo1/influenza-like-illness-analysis.ipynb b/module3/exo1/influenza-like-illness-analysis.ipynb index 87092fc69cd90ff457ea56284b789cb0de199a41..e0289892dac8f0d4756c23f38c11c694bf332578 100644 --- a/module3/exo1/influenza-like-illness-analysis.ipynb +++ b/module3/exo1/influenza-like-illness-analysis.ipynb @@ -9,10 +9,47 @@ }, { "cell_type": "code", - "execution_count": null, - "metadata": { - "collapsed": true - }, + "execution_count": 1, + "metadata": {}, + "outputs": [ + { + "data": { + "text/plain": [ + "'/home/jovyan/work/module3/exo1'" + ] + }, + "execution_count": 1, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "%pwd" + ] + }, + { + "cell_type": "code", + "execution_count": 2, + "metadata": {}, + "outputs": [ + { + "name": "stdout", + "output_type": "stream", + "text": [ + "analyse-syndrome-grippal.ipynb influenza-like-illness-analysis.ipynb\r\n", + "analyse-syndrome-grippal.org influenza-like-illness-analysis.org\r\n", + "analyse-syndrome-grippal.Rmd influenza-like-illness-analysis.Rmd\r\n" + ] + } + ], + "source": [ + "%ls\n" + ] + }, + { + "cell_type": "code", + "execution_count": 3, + "metadata": {}, "outputs": [], "source": [ "%matplotlib inline\n", @@ -30,13 +67,31 @@ }, { "cell_type": "code", - "execution_count": null, - "metadata": { - "collapsed": true - }, - "outputs": [], + "execution_count": 6, + "metadata": {}, + "outputs": [ + { + "data": { + "text/plain": [ + "True" + ] + }, + "execution_count": 6, + "metadata": {}, + "output_type": "execute_result" + } + ], "source": [ - "data_url = \"http://www.sentiweb.fr/datasets/incidence-PAY-3.csv\"" + "data_url = \"http://www.sentiweb.fr/datasets/incidence-PAY-3.csv\"\n", + "data_file = \"syndrome-grippal.csv\"\n", + "\n", + "import os\n", + "import urllib.request\n", + "if not os.path.exists(data_file):\n", + " print('file does not exist')\n", + " urllib.request.urlretrieve(data_url, data_file)\n", + "\n", + "os.path.exists(data_file)" ] }, { @@ -63,11 +118,978 @@ }, { "cell_type": "code", - "execution_count": null, + "execution_count": 8, "metadata": {}, - "outputs": [], + "outputs": [ + { + "data": { + "text/html": [ + "
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weekindicatorincinc_lowinc_upinc100inc100_lowinc100_upgeo_inseegeo_name
020223632300117464.028538.03527.043.0FRFrance
12022353132479926.016568.02015.025.0FRFrance
22022343107087334.014082.01611.021.0FRFrance
32022333129268869.016983.01913.025.0FRFrance
420223232225716158.028356.03425.043.0FRFrance
520223132182816268.027388.03325.041.0FRFrance
620223031966314779.024547.03023.037.0FRFrance
720222932426818906.029630.03729.045.0FRFrance
820222832484519214.030476.03729.045.0FRFrance
920222734074533994.047496.06151.071.0FRFrance
1020222633401028521.039499.05143.059.0FRFrance
1120222532337719042.027712.03528.042.0FRFrance
1220222432632821829.030827.04033.047.0FRFrance
1320222332343018950.027910.03528.042.0FRFrance
1420222231895115099.022803.02923.035.0FRFrance
1520222131363210251.017013.02116.026.0FRFrance
1620222031978715756.023818.03024.036.0FRFrance
1720221931788414079.021689.02721.033.0FRFrance
1820221833035325089.035617.04638.054.0FRFrance
1920221733600630373.041639.05446.062.0FRFrance
2020221634994942836.057062.07564.086.0FRFrance
21202215310080690824.0110788.0152137.0167.0FRFrance
222022143155441143891.0166991.0234217.0251.0FRFrance
232022133191914179558.0204270.0289270.0308.0FRFrance
242022123166224155035.0177413.0251234.0268.0FRFrance
252022113122849113306.0132392.0185171.0199.0FRFrance
2620221038790479741.096067.0133121.0145.0FRFrance
2720220935018243958.056406.07667.085.0FRFrance
2820220833096325942.035984.04739.055.0FRFrance
2920220733488229446.040318.05345.061.0FRFrance
.................................
194619852132609619621.032571.04735.059.0FRFrance
194719852032789620885.034907.05138.064.0FRFrance
194819851934315432821.053487.07859.097.0FRFrance
194919851834055529935.051175.07455.093.0FRFrance
195019851733405324366.043740.06244.080.0FRFrance
195119851635036236451.064273.09166.0116.0FRFrance
195219851536388145538.082224.011683.0149.0FRFrance
19531985143134545114400.0154690.0244207.0281.0FRFrance
19541985133197206176080.0218332.0357319.0395.0FRFrance
19551985123245240223304.0267176.0445405.0485.0FRFrance
19561985113276205252399.0300011.0501458.0544.0FRFrance
19571985103353231326279.0380183.0640591.0689.0FRFrance
19581985093369895341109.0398681.0670618.0722.0FRFrance
19591985083389886359529.0420243.0707652.0762.0FRFrance
19601985073471852432599.0511105.0855784.0926.0FRFrance
19611985063565825518011.0613639.01026939.01113.0FRFrance
19621985053637302592795.0681809.011551074.01236.0FRFrance
19631985043424937390794.0459080.0770708.0832.0FRFrance
19641985033213901174689.0253113.0388317.0459.0FRFrance
196519850239758680949.0114223.0177147.0207.0FRFrance
196619850138548965918.0105060.0155120.0190.0FRFrance
196719845238483060602.0109058.0154110.0198.0FRFrance
1968198451310172680242.0123210.0185146.0224.0FRFrance
19691984503123680101401.0145959.0225184.0266.0FRFrance
1970198449310107381684.0120462.0184149.0219.0FRFrance
197119844837862060634.096606.0143110.0176.0FRFrance
197219844737202954274.089784.013199.0163.0FRFrance
197319844638733067686.0106974.0159123.0195.0FRFrance
19741984453135223101414.0169032.0246184.0308.0FRFrance
197519844436842220056.0116788.012537.0213.0FRFrance
\n", + "

1976 rows × 10 columns

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25089.0 35617.0 46 38.0 \n", + "19 202217 3 36006 30373.0 41639.0 54 46.0 \n", + "20 202216 3 49949 42836.0 57062.0 75 64.0 \n", + "21 202215 3 100806 90824.0 110788.0 152 137.0 \n", + "22 202214 3 155441 143891.0 166991.0 234 217.0 \n", + "23 202213 3 191914 179558.0 204270.0 289 270.0 \n", + "24 202212 3 166224 155035.0 177413.0 251 234.0 \n", + "25 202211 3 122849 113306.0 132392.0 185 171.0 \n", + "26 202210 3 87904 79741.0 96067.0 133 121.0 \n", + "27 202209 3 50182 43958.0 56406.0 76 67.0 \n", + "28 202208 3 30963 25942.0 35984.0 47 39.0 \n", + "29 202207 3 34882 29446.0 40318.0 53 45.0 \n", + "... ... ... ... ... ... ... ... \n", + "1946 198521 3 26096 19621.0 32571.0 47 35.0 \n", + "1947 198520 3 27896 20885.0 34907.0 51 38.0 \n", + "1948 198519 3 43154 32821.0 53487.0 78 59.0 \n", + "1949 198518 3 40555 29935.0 51175.0 74 55.0 \n", + "1950 198517 3 34053 24366.0 43740.0 62 44.0 \n", + "1951 198516 3 50362 36451.0 64273.0 91 66.0 \n", + "1952 198515 3 63881 45538.0 82224.0 116 83.0 \n", + "1953 198514 3 134545 114400.0 154690.0 244 207.0 \n", + "1954 198513 3 197206 176080.0 218332.0 357 319.0 \n", + "1955 198512 3 245240 223304.0 267176.0 445 405.0 \n", + "1956 198511 3 276205 252399.0 300011.0 501 458.0 \n", + "1957 198510 3 353231 326279.0 380183.0 640 591.0 \n", + "1958 198509 3 369895 341109.0 398681.0 670 618.0 \n", + "1959 198508 3 389886 359529.0 420243.0 707 652.0 \n", + "1960 198507 3 471852 432599.0 511105.0 855 784.0 \n", + "1961 198506 3 565825 518011.0 613639.0 1026 939.0 \n", + "1962 198505 3 637302 592795.0 681809.0 1155 1074.0 \n", + "1963 198504 3 424937 390794.0 459080.0 770 708.0 \n", + "1964 198503 3 213901 174689.0 253113.0 388 317.0 \n", + "1965 198502 3 97586 80949.0 114223.0 177 147.0 \n", + "1966 198501 3 85489 65918.0 105060.0 155 120.0 \n", + "1967 198452 3 84830 60602.0 109058.0 154 110.0 \n", + "1968 198451 3 101726 80242.0 123210.0 185 146.0 \n", + "1969 198450 3 123680 101401.0 145959.0 225 184.0 \n", + "1970 198449 3 101073 81684.0 120462.0 184 149.0 \n", + "1971 198448 3 78620 60634.0 96606.0 143 110.0 \n", + "1972 198447 3 72029 54274.0 89784.0 131 99.0 \n", + "1973 198446 3 87330 67686.0 106974.0 159 123.0 \n", + "1974 198445 3 135223 101414.0 169032.0 246 184.0 \n", + "1975 198444 3 68422 20056.0 116788.0 125 37.0 \n", + "\n", + " inc100_up geo_insee geo_name \n", + "0 43.0 FR France \n", + "1 25.0 FR France \n", + "2 21.0 FR France \n", + "3 25.0 FR France \n", + "4 43.0 FR France \n", + "5 41.0 FR France \n", + "6 37.0 FR France \n", + "7 45.0 FR France \n", + "8 45.0 FR France \n", + "9 71.0 FR France \n", + "10 59.0 FR France \n", + "11 42.0 FR France \n", + "12 47.0 FR France \n", + "13 42.0 FR France \n", + "14 35.0 FR France \n", + "15 26.0 FR France \n", + "16 36.0 FR France \n", + "17 33.0 FR France \n", + "18 54.0 FR France \n", + "19 62.0 FR France \n", + "20 86.0 FR France \n", + "21 167.0 FR France \n", + "22 251.0 FR France \n", + "23 308.0 FR France \n", + "24 268.0 FR France \n", + "25 199.0 FR France \n", + "26 145.0 FR France \n", + "27 85.0 FR France \n", + "28 55.0 FR France \n", + "29 61.0 FR France \n", + "... ... ... ... \n", + "1946 59.0 FR France \n", + "1947 64.0 FR France \n", + "1948 97.0 FR France \n", + "1949 93.0 FR France \n", + "1950 80.0 FR France \n", + "1951 116.0 FR France \n", + "1952 149.0 FR France \n", + "1953 281.0 FR France \n", + "1954 395.0 FR France \n", + "1955 485.0 FR France \n", + "1956 544.0 FR France \n", + "1957 689.0 FR France \n", + "1958 722.0 FR France \n", + "1959 762.0 FR France \n", + "1960 926.0 FR France \n", + "1961 1113.0 FR France \n", + "1962 1236.0 FR France \n", + "1963 832.0 FR France \n", + "1964 459.0 FR France \n", + "1965 207.0 FR France \n", + "1966 190.0 FR France \n", + "1967 198.0 FR France \n", + "1968 224.0 FR France \n", + "1969 266.0 FR France \n", + "1970 219.0 FR France \n", + "1971 176.0 FR France \n", + "1972 163.0 FR France \n", + "1973 195.0 FR France \n", + "1974 308.0 FR France \n", + "1975 213.0 FR France \n", + "\n", + "[1976 rows x 10 columns]" + ] + }, + "execution_count": 8, + "metadata": {}, + "output_type": "execute_result" + } + ], "source": [ - "raw_data = pd.read_csv(data_url, skiprows=1)\n", + "raw_data = pd.read_csv(data_file, skiprows=1)\n", "raw_data" ] }, @@ -80,9 +1102,73 @@ }, { "cell_type": "code", - "execution_count": null, + "execution_count": 9, "metadata": {}, - "outputs": [], + "outputs": [ + { + "data": { + "text/html": [ + "
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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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12022353132479926.016568.02015.025.0FRFrance
22022343107087334.014082.01611.021.0FRFrance
32022333129268869.016983.01913.025.0FRFrance
420223232225716158.028356.03425.043.0FRFrance
520223132182816268.027388.03325.041.0FRFrance
620223031966314779.024547.03023.037.0FRFrance
720222932426818906.029630.03729.045.0FRFrance
820222832484519214.030476.03729.045.0FRFrance
920222734074533994.047496.06151.071.0FRFrance
1020222633401028521.039499.05143.059.0FRFrance
1120222532337719042.027712.03528.042.0FRFrance
1220222432632821829.030827.04033.047.0FRFrance
1320222332343018950.027910.03528.042.0FRFrance
1420222231895115099.022803.02923.035.0FRFrance
1520222131363210251.017013.02116.026.0FRFrance
1620222031978715756.023818.03024.036.0FRFrance
1720221931788414079.021689.02721.033.0FRFrance
1820221833035325089.035617.04638.054.0FRFrance
1920221733600630373.041639.05446.062.0FRFrance
2020221634994942836.057062.07564.086.0FRFrance
21202215310080690824.0110788.0152137.0167.0FRFrance
222022143155441143891.0166991.0234217.0251.0FRFrance
232022133191914179558.0204270.0289270.0308.0FRFrance
242022123166224155035.0177413.0251234.0268.0FRFrance
252022113122849113306.0132392.0185171.0199.0FRFrance
2620221038790479741.096067.0133121.0145.0FRFrance
2720220935018243958.056406.07667.085.0FRFrance
2820220833096325942.035984.04739.055.0FRFrance
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.................................
194619852132609619621.032571.04735.059.0FRFrance
194719852032789620885.034907.05138.064.0FRFrance
194819851934315432821.053487.07859.097.0FRFrance
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195019851733405324366.043740.06244.080.0FRFrance
195119851635036236451.064273.09166.0116.0FRFrance
195219851536388145538.082224.011683.0149.0FRFrance
19531985143134545114400.0154690.0244207.0281.0FRFrance
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197119844837862060634.096606.0143110.0176.0FRFrance
197219844737202954274.089784.013199.0163.0FRFrance
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1975 rows × 10 columns

\n", + "
" + ], + "text/plain": [ + " week indicator inc inc_low inc_up inc100 inc100_low \\\n", + "0 202236 3 23001 17464.0 28538.0 35 27.0 \n", + "1 202235 3 13247 9926.0 16568.0 20 15.0 \n", + "2 202234 3 10708 7334.0 14082.0 16 11.0 \n", + "3 202233 3 12926 8869.0 16983.0 19 13.0 \n", + "4 202232 3 22257 16158.0 28356.0 34 25.0 \n", + "5 202231 3 21828 16268.0 27388.0 33 25.0 \n", + "6 202230 3 19663 14779.0 24547.0 30 23.0 \n", + "7 202229 3 24268 18906.0 29630.0 37 29.0 \n", + "8 202228 3 24845 19214.0 30476.0 37 29.0 \n", + "9 202227 3 40745 33994.0 47496.0 61 51.0 \n", + "10 202226 3 34010 28521.0 39499.0 51 43.0 \n", + "11 202225 3 23377 19042.0 27712.0 35 28.0 \n", + "12 202224 3 26328 21829.0 30827.0 40 33.0 \n", + "13 202223 3 23430 18950.0 27910.0 35 28.0 \n", + "14 202222 3 18951 15099.0 22803.0 29 23.0 \n", + "15 202221 3 13632 10251.0 17013.0 21 16.0 \n", + "16 202220 3 19787 15756.0 23818.0 30 24.0 \n", + "17 202219 3 17884 14079.0 21689.0 27 21.0 \n", + "18 202218 3 30353 25089.0 35617.0 46 38.0 \n", + "19 202217 3 36006 30373.0 41639.0 54 46.0 \n", + "20 202216 3 49949 42836.0 57062.0 75 64.0 \n", + "21 202215 3 100806 90824.0 110788.0 152 137.0 \n", + "22 202214 3 155441 143891.0 166991.0 234 217.0 \n", + "23 202213 3 191914 179558.0 204270.0 289 270.0 \n", + "24 202212 3 166224 155035.0 177413.0 251 234.0 \n", + "25 202211 3 122849 113306.0 132392.0 185 171.0 \n", + "26 202210 3 87904 79741.0 96067.0 133 121.0 \n", + "27 202209 3 50182 43958.0 56406.0 76 67.0 \n", + "28 202208 3 30963 25942.0 35984.0 47 39.0 \n", + "29 202207 3 34882 29446.0 40318.0 53 45.0 \n", + "... ... ... ... ... ... ... ... \n", + "1946 198521 3 26096 19621.0 32571.0 47 35.0 \n", + "1947 198520 3 27896 20885.0 34907.0 51 38.0 \n", + "1948 198519 3 43154 32821.0 53487.0 78 59.0 \n", + "1949 198518 3 40555 29935.0 51175.0 74 55.0 \n", + "1950 198517 3 34053 24366.0 43740.0 62 44.0 \n", + "1951 198516 3 50362 36451.0 64273.0 91 66.0 \n", + "1952 198515 3 63881 45538.0 82224.0 116 83.0 \n", + "1953 198514 3 134545 114400.0 154690.0 244 207.0 \n", + "1954 198513 3 197206 176080.0 218332.0 357 319.0 \n", + "1955 198512 3 245240 223304.0 267176.0 445 405.0 \n", + "1956 198511 3 276205 252399.0 300011.0 501 458.0 \n", + "1957 198510 3 353231 326279.0 380183.0 640 591.0 \n", + "1958 198509 3 369895 341109.0 398681.0 670 618.0 \n", + "1959 198508 3 389886 359529.0 420243.0 707 652.0 \n", + "1960 198507 3 471852 432599.0 511105.0 855 784.0 \n", + "1961 198506 3 565825 518011.0 613639.0 1026 939.0 \n", + "1962 198505 3 637302 592795.0 681809.0 1155 1074.0 \n", + "1963 198504 3 424937 390794.0 459080.0 770 708.0 \n", + "1964 198503 3 213901 174689.0 253113.0 388 317.0 \n", + "1965 198502 3 97586 80949.0 114223.0 177 147.0 \n", + "1966 198501 3 85489 65918.0 105060.0 155 120.0 \n", + "1967 198452 3 84830 60602.0 109058.0 154 110.0 \n", + "1968 198451 3 101726 80242.0 123210.0 185 146.0 \n", + "1969 198450 3 123680 101401.0 145959.0 225 184.0 \n", + "1970 198449 3 101073 81684.0 120462.0 184 149.0 \n", + "1971 198448 3 78620 60634.0 96606.0 143 110.0 \n", + "1972 198447 3 72029 54274.0 89784.0 131 99.0 \n", + "1973 198446 3 87330 67686.0 106974.0 159 123.0 \n", + "1974 198445 3 135223 101414.0 169032.0 246 184.0 \n", + "1975 198444 3 68422 20056.0 116788.0 125 37.0 \n", + "\n", + " inc100_up geo_insee geo_name \n", + "0 43.0 FR France \n", + "1 25.0 FR France \n", + "2 21.0 FR France \n", + "3 25.0 FR France \n", + "4 43.0 FR France \n", + "5 41.0 FR France \n", + "6 37.0 FR France \n", + "7 45.0 FR France \n", + "8 45.0 FR France \n", + "9 71.0 FR France \n", + "10 59.0 FR France \n", + "11 42.0 FR France \n", + "12 47.0 FR France \n", + "13 42.0 FR France \n", + "14 35.0 FR France \n", + "15 26.0 FR France \n", + "16 36.0 FR France \n", + "17 33.0 FR France \n", + "18 54.0 FR France \n", + "19 62.0 FR France \n", + "20 86.0 FR France \n", + "21 167.0 FR France \n", + "22 251.0 FR France \n", + "23 308.0 FR France \n", + "24 268.0 FR France \n", + "25 199.0 FR France \n", + "26 145.0 FR France \n", + "27 85.0 FR France \n", + "28 55.0 FR France \n", + "29 61.0 FR France \n", + "... ... ... ... \n", + "1946 59.0 FR France \n", + "1947 64.0 FR France \n", + "1948 97.0 FR France \n", + "1949 93.0 FR France \n", + "1950 80.0 FR France \n", + "1951 116.0 FR France \n", + "1952 149.0 FR France \n", + "1953 281.0 FR France \n", + "1954 395.0 FR France \n", + "1955 485.0 FR France \n", + "1956 544.0 FR France \n", + "1957 689.0 FR France \n", + "1958 722.0 FR France \n", + "1959 762.0 FR France \n", + "1960 926.0 FR France \n", + "1961 1113.0 FR France \n", + "1962 1236.0 FR France \n", + "1963 832.0 FR France \n", + "1964 459.0 FR France \n", + "1965 207.0 FR France \n", + "1966 190.0 FR France \n", + "1967 198.0 FR France \n", + "1968 224.0 FR France \n", + "1969 266.0 FR France \n", + "1970 219.0 FR France \n", + "1971 176.0 FR France \n", + "1972 163.0 FR France \n", + "1973 195.0 FR France \n", + "1974 308.0 FR France \n", + "1975 213.0 FR France \n", + "\n", + "[1975 rows x 10 columns]" + ] + }, + "execution_count": 10, + "metadata": {}, + "output_type": "execute_result" + } + ], "source": [ "data = raw_data.dropna().copy()\n", "data" @@ -123,10 +2176,8 @@ }, { "cell_type": "code", - "execution_count": null, - "metadata": { - "collapsed": true - }, + "execution_count": 11, + "metadata": {}, "outputs": [], "source": [ "def convert_week(year_and_week_int):\n", @@ -154,10 +2205,8 @@ }, { "cell_type": "code", - "execution_count": null, - "metadata": { - "collapsed": true - }, + "execution_count": 12, + "metadata": {}, "outputs": [], "source": [ "sorted_data = data.set_index('period').sort_index()" @@ -180,9 +2229,17 @@ }, { "cell_type": "code", - "execution_count": null, + "execution_count": 13, "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", @@ -200,9 +2257,32 @@ }, { "cell_type": "code", - "execution_count": null, + "execution_count": 14, "metadata": {}, - "outputs": [], + "outputs": [ + { + "data": { + "text/plain": [ + "" + ] + }, + "execution_count": 14, + "metadata": {}, + "output_type": "execute_result" + }, + { + "data": { + "image/png": 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iUM+ROI0+IFU7iKt3MIvewWx1LxIBshem1rYeQeTyhVpXITa/fdba2Hz1rt4a12R8wiavCORrqqHUedhwnQu0U7/+MABgy3XvqXFN3DSCD2U41/gCpa3JGvIGR/OGM5kosIYSgUIdaii1jvKyqfZK+TFwFdVSA62Ray4U40FDaWmyXhI7OMICpRqwQIlALQcc8yaKNXqnvDLZRMxfaznoJFuDgbNgB7HVr0SptfZbCZKyo9bSyjCeYYESgdqavAzHx6Ya+uvHrEA9DKe5GBOGR9ftjSSQErZArvUvqKd+axaecbrRQt3AAiUChTrU/Gv9TnlFPQ+IYclG9BU8/cp+fOKWZ/Cdh9eXn5nUK5wjXTo0r+zrx/LN0d70UOs1TpVkHN1KXcFO+QjUVEMxriivkclLXT+yzat+VK9sxBnDgYFRAMDm7v6y89oaSpX71ju+Yy1KjBKUMB7GYNZQqgtrKBHQOeX3HhrGdx9eVxOnvbK919opH9eHYnrgx2I8yOaj3UVCSoUoLpiEWodSx6N2PdTtjqe34t3f/2vk/PVwD+MZ1lAioHPKf/7uVfjrhm689bhpOP2oSdW5eJ0ubLQX5sWsQD04paNGMyVts1X0NuABL5iv/v6lWleBCYA1lAjoTF7DWSsUsZrhlcYorwbfbbia5YcVdlE1FLUdTxSBovLU+vcLop7qFvUZY5NXdWGBEgGdSava+1mFgWe4eoaz4QahqFqWGqyihJWrS9baZBmIoW5bugcwMDI2+3zFXWRZT8JxPMECJQI6DUVNfqq515dp+/qaR+JUay+vCswswzrbow7qSkOJ8hOoLLXcJ85EUM1y+QLe9u2/4LO/fq6qdVDBC71DUbfPYRWlmrBAiYBuBpqIu7qvAtR6OIo789OaJCpwYyLkpDbqPdiL5qJIJCVIav0DBhAk6/bK97ms2HqgqnU4sqsVALC1eyBWOXUstxsaFigR0E10E7I1q2m2MA12tdoWJnbYcJnXiULY2X/UdUZ2lFeERmgMDUVft1FpgsqkqjukNKetrVOidnP2oVQXFigR0A0YiQpE+ZjQm7xq778B6nvmF7ZqUX8/+/cfAx9KLUybQZcsBhWMDfUseA9nWKBEwGTSqOf3pVT9+lHzmXZRrsBQFfZ3idqGcSyeoswBuRa/c9Al1bGxqlfcZ4zFUXVggRIBXWceCy1BV/ZYBAQEETcowF7YqDtegdsKbfKqxey/zGvX24A41hpTZKFf2WowHligRECnodQ8wqoOiNoC9m67GiN3JVo27M8TVaDE+fntvFWuYxyC+nfxkahuvahSZmV+VqsCC5QIGG3k1XTKa7Uj67PWtuXorwCuvhkxvIYSr/woEws7R8gpdG0EivnY2Jm8ouVjp3x1YYESAZ1TvuhYraJTXpM+VlFWZqpTgUrcV9gyomqa8bZcKS9v7X9nN2PllI9r2q23dhtvsECJgNbkJR+nWq52btTnZSw2G666f6IClQw7ga43DSWOdhatLuyUr0dYoERA9zCPhYaiexIqZluOTLzdco1RXBW4r9A+lIgzgjgTiXJvrxaTlqDfaKzWZcZ91XUxeKQy9WHcxBYoRJQkoueI6I/y/y4iWkREG+TnJMe5VxHRRiJaR0TnO9JPJ6IX5bEbSY6ORJQhot/I9GVENNeRZ6G8xgYiWhj3PspBty/dWM/S/Kj1gxI9bLg65Tqptg8lTmizyqsLSvASO2w2ip+nrnwo8S5Ua1/jeKUSGsq/AFjj+P9KAEuEEPMBLJH/g4hOBHAJgJMAXADgx0SUlHl+AuByAPPl3wUy/TIAB4QQxwK4AcD1sqwuAFcDeAOAMwFc7RRc1UYf5WV91mKlfNGH0qBO+SqV66TaiwZV+VFyF98pH46w28iYrlcpxmqzxdgaSp28N2i8EkugENFsAO8B8HNH8oUAbpPfbwNwkSP9TiHEiBBiM4CNAM4kohkAOoQQS4X1JN/uyaPKugfAuVJ7OR/AIiFEjxDiAIBFKAqhqmOa3UTayykk5s0hq3bpQIqL+qrjLFVtHidKp+oaSgXegxL2/moxQw/KYQvTRvGhsIZSFeJqKN8D8AUAzvnSdCHEbgCQn9Nk+iwA2x3n7ZBps+R3b7orjxAiB6AXwOSAssYEvVPeojbqtDUSfWfRevu9LLUgrg9FN6COZZRXTdahlCmI4zZHtC329XnGLsornq+wXsLrxyuRBQoRvRfAXiHEyrBZfNJEQHrUPO6LEl1ORCuIaMW+fftCVdSEtjOOgR05TNmLXt5TvQposE1uEfOPhQ8l7Kw0skCJ40Mp0+QV34cSIU+Y8sbKh1JnJr+w5AsC31+8Ab2DUbffr2/iaChvAvA+ItoC4E4A7yCiXwLYI81YkJ975fk7AMxx5J8NYJdMn+2T7spDRCkAnQB6AsoqQQhxkxBigRBiwdSpU6PdqQdz2PDhO/uJvPWKMmlphlR7r6sYTRvehxKx/EK8/GVdqxYmr0Cn/Fj7UBrTKf/o2r24YfF6/NcfVtfk+tUmskARQlwlhJgthJgLy9n+iBDiYwDuB6CirhYCuE9+vx/AJTJyax4s5/tyaRbrI6KzpH/kUk8eVdYH5TUEgIcAnEdEk6Qz/jyZNiboBIpKrq5TvvwjjUA9DcKR/UCRcsm8to8onI4St72iDahBJi/TGZUl7l5etZrzZWWI6OBo7czS1SRVhTKvA3AXEV0GYBuAiwFACLGaiO4C8DKAHIArhBCqVT8D4FYALQAekH8A8AsAdxDRRliaySWyrB4iugbAM/K8rwsheqpwL77o16FUX0PRzQSdyVEc1/0jOSxZswcXvm7MXFEubBunpu5juvVKRHNKvJXyY3ctK79/+uBoDsPZArramkqOhdFQqq2pVGoT1Fq9N6ixp31mKiJQhBB/AfAX+X0/gHM1510L4Fqf9BUATvZJH4YUSD7HbgZwc9Q6x0G3DsU2I9diFXPM/F/9/Uv43XM7MW9KG06ZPTF6PSJHSIU7HifKq76d8hbhfSjRrwXoB9T33PgENncPYMt17yk5FirKK161QhN9YWN9hA2P1z3FeKV8GahOYN7Lq3p1qFbRe/uGAQCHhnKR8scOGzbkq4xTPtx5ccOGIxmTytVQYnYyndDcHPHVupXwcZVDo/pQxjssUMqgKWk114gmLLeWYcNxtaK0vLesTv0KXY/q5KvMwsaQPpTIUV7RsQVqyJlrfB9K+XkCTV7259j0/ejRhNGFfiUY73KMBUoZtDZZC/uHdA4124dSvToYIpYjk0pYXWG0VgLFeHwMfShRo7zsSLXyGWsfSrQt9oOc8mM0UqqX2MXdzaBGI7tpvVWjwwKlDJIJqxcMaATK2PhQQjjlIwxpTSkrTy4fre7qmpHv3GAyGcutV6IOjnH8COXmidscldZQigN1tPqUS/QNPKsfOHM4wwKlDFQf1K1EV8erufWKjkppKPFNXvHMRbpZsGmdSqhrhA4brm75msxlXbxe16FUu+cXo7yi5S+apStRG8YLC5QyUH2wlu9D0c/giweiqNNK+4orDKMPxuGOxzF9VXtzyLFYdFm8VrzfKdLWKyG2rx+zlfIxF9DWWkOJMzGqZ1iglIHqjDnDbsO13nguyuWLUVrRoJh7rxS3/vc/XokWDe9DiaplRa+lyhu2hLiTlkhbrwQ65YXrs1rE3QS1+IxWpj6MGxYoZVDUUPzNQsWw4er11mqVbPtA4jp7q7TKfCyjvCIvbFT5KmxO8r1WnYXNxt1bq+zrRfZzSQ2lVgsbx7kgY4FSBqozaDUU+Vkbk1fxe6zFf9GzxsKk3VVi5lv1hY2Rcrnzht7AMvbmiBUWKGO0DiW2D8We9FWkOtEZnxYvFijlIAyzm2rZZ8MMMnEH3LgmK7sekZ2lwRnHdh1KvPIjRXmNuYZSfp5w61DGhriReLX2oYxXWKCUgeqCZh9K9GsMZ/M4ODjqW65Vh+BrA9EmP0V5UhunvL31v+5wGTPg7y/egHtX7ihJr7aGEqfpyvWhxF/YWGmnvHB9VguKuQ5lrOp5uFKNzSHHL7IPGqO8YujTH/35MqzcesB3L6XAqsV8PhL2gxotf9xdXIsmH8PxEGXdsHg9AOADp892pY/VwsZINIAPJdQ6lIj1KZdGDRse72KMNZQyKDrlg7WEOJ115dYD2us6r1F6TmVMXnE7fPRXAAdHCVVC+wubtybb16vP0HWMR6QorxDlBZW7t28YZ1y7GItjvAAu7m7D9bKwcZy6UFiglIMa9Gr5CuBqPwaRNZSYGo5pQKpEWOpYaSjRQnLLy1RtDcWvPmFeARzE1v2D2Nc3gp8+tslcQV297OtFzB9Ck1r08h4s+O/FGMmNz3eWVBMWKGVg8qEoU5fuwesdzOKlnb3lXzeMUz6mpIm7W7Bdjyrlq8TCuXpe2FjmQvn44d2G7H6TpqAsYQSKMqvqnp8wxPWBFELkv+aPL6O7fwR7ekfKKns4m8eFP3oSz24rtTIoxrvvhgVKGai+oNNQ1Lb2uu3tP3Hrcrz3B0+EWqWsN6sFa0dA1LDheBpGsSIxH3Ttcfd5ca5hPC/igFd862KEvGWeX+2FjdX0McT7DeOVYZulA8Kuo06uNuzpx6rtB3H1ffrX+9obiI7T3SFZoJSB6mC6wV5trKh7GFfvOgQAOOCJ4vLDuadWqG4dcwBIhPShLHp5j3YvszjVCG/yik7oNR6RTV7qOuXnNa3DKblW7C1ygvP7DdjBTnlzfdQ5pg1If/fcDvQOZX2PxTZ52dsjVV7rD/O++5hb5dU9LFDKwKShmBx+bRkrqK5/2PwSq3K3ka/cOhR9OS/sOIh/vH0F/usPL+vrEXtmq5Uoscuv9m7DccwZ5f5+sd/YaNRQyvShhOiuSggGaejr9/ThX3+zCp+/a5Xv8bhrvVQ9g+5fPQrlmubCbAtTqxX6YwULlAjkNE9P3vah+OdTHVVnEnOV5ZjFudah6MbbCvXToGL6pCDcuj/aW/0Cr2tyEns+dQQNVnEXNgoh8Kk7VuCpTd2a8kMVH3jNsfOhmDSU0rSgtg1TG9Xv1+3p056j3jW059Cw/3ViTixsTTdEAeXuvK22LwrqZ3HemdMIsEApA9VNdBp72H2CwsxSnEInzOw1rjyhED6UMCGbsbevDxjMAXPbbdrXrz0WV0MZGM3jodV78MnbVvjXMVzx/nnLjvKKcbEQ+f2ER9BEqFImJJNrIe5eXGF8MMq/UbZACSElwkwmGxkWKOVgm7yCNRRTXw+jSmu3dwk1bJU//ymq63Ft8xHzmXwoBnOj4rwbHg+4hvD9XnKeJt1kFTStpQlClHwJJn5oukEj9Ck/sO1DVKecOpvWI1VzLy91734C5YUdB7Fkjf86mjA+lPFu8uKV8mWgOrnOqVgUKP7HVYcLFeXlGvxC1C3mABNm072gtSaxtxU3rDNR9Yozwyt42lQ3o9T9fgWDwKhM2HBIs1z0SwEI40MpTYtrTgzT702actyFiWF8MHn7nNJj7/vhkwDgu5NFGC1flTlOg7xYQymH4uwmWKCYBvd4YcOauhlLDEYJi2BTQHAd4tTDND6YIuzC4FQsvfcpQghwld802EUhlFnTUb7uWhv39mP55p4QZQUf9zV5BQoU4yUrYvIqlhXV5KWe0YBzlOO+zL4WZnPQWrzNdSxhDaUMVFfQmaxM61CUHhBmll2u892ZHmX2E0ZdD9pAMq7JTOWKa/IKwqWhaMoH9ANJ3jBgxBkqwjibndXStfM7v/sYAP8ZtLusypq8wgjEcn47s4YSuih3uZ5y/Ahjui4UBBIJ94NmslCYjo0HWEMpA9PWK2pmY/LlhXLKl/nExNZQ7AgV/TlFh2a8ay28eTl++MgGV1rYKKd4WkDp9fzK1d2f/ZsYBrsoVQyTxTnIm9ZymMsKPu7XBsEDpfmabpNjsAauFdoGK4G5Dub8uRCWBr9JoZ0U+AyxQGEktoai86EYIlDULD6MU17nQ9HmrFBHDTNzC3Roh6jGY+v34dsPr/fkCx6MTcI8DC6zlqclncXW1IcSUkMx9SFjGLbJLOtzPOiaYTRTdxuHv667jJgaShiTl+Yazr4XFAUXZmHjOHWhsEAph7A+FN1DYecvM8prTMKGlckroG5q/Y3fGbZDMvJuw8Ec0yq7AAAgAElEQVTHVbXi7APlNhl5j5lnz6Z1RmEGq2Wv7MfDq1/1y63PZJ9RPMcU0po1aDB+R52/vV8/CDR5lamh6NdyyT6me4bs68XrZ0HdSPccO9vcry3C+FDivIStEWAfSgT8BjXTw2jK78XZmcPYzuMSJsoryLZcXDAW7fqmKK9KvGvGG+XlKj/M7NmoFZjr8OGbngZQ6uMIE+XlLH80FyxQcoUCmgLmi36TIme/9LuXuFFeLrOipvomc3Fck1eYhY0Fu5+7zxlxtHnQGBDs8LcOsoZymOOKsPHpTM4OptNQ7LDhMA+f48Fym2p09XNcx1h6QN0CNRSzXSbqcG+yP9tO+RgC1SWYS0xeZo0w7AaWUQhzW85zTJMSo4bic9jZBn7tHDfKy5nftNuEjnLe3OlHcesVcz/3Ch2nEPcbA4outnjt1MiwQAmJ6WF2PYwVWCkfFJHkW78KKdGBjsiCfkANs+1E4HU9n7rjcTSUoNDgME55k0M3zm8QRsNzXtdk8soZjps0FL/jcXdICKehBLdD3MCQMD6Yoi/Une5sc78xwNbgA5qenfIMAPdAZ4rR1y5slJ+hTF5O84Ozgxpm8CYeeHE3Xu0t3ScpzIOq6u13f7EXNtrKj2awFu46RKEQ8BuFccqr30SnARqCwAIJpaE4vptNXoaZvk+aq8+V6ZQP54NylqXRUAyBD2HXeumwJyYhTF5eLc30jJcjVMerphJZoBDRHCJ6lIjWENFqIvoXmd5FRIuIaIP8nOTIcxURbSSidUR0viP9dCJ6UR67keQqOyLKENFvZPoyIprryLNQXmMDES2Meh9hcXYW0z5HldBQyt7LK6TJ4TO/ehYfvmmpNn+QSanoMC09ZvtgIj4p9sJFbXZ5PGT5fmtx3CYvT+kB2ksxf1hzTJjfy32OSUPz5jGZtEwajGmdiV/2oN82VASXQ4jo+pmp/6j7irtSPih7XvM7OgWqr4YSIsqrXl5BXC3iaCg5AJ8XQpwA4CwAVxDRiQCuBLBECDEfwBL5P+SxSwCcBOACAD8moqQs6ycALgcwX/5dINMvA3BACHEsgBsAXC/L6gJwNYA3ADgTwNVOwVUNTBpKwfAwOil3Ly9n39M7rc2oWeGOA0Ol1wvR0U3vezEdC8TWkHQDTfBxL+lEadd2zaIL3mPOawXPjnUUtSxz/bxFlZvHbPIKV1dXHseAbzKJeQmjoTurrH2nkMHkVdSS/Y+v39OHuVf+Cc9vP+h73OTUF0JoI8GcAjEoCi5QWBn6caEg8KNHN6J30P99MPVOZIEihNgthHhWfu8DsAbALAAXArhNnnYbgIvk9wsB3CmEGBFCbAawEcCZRDQDQIcQYqmwpgS3e/Kosu4BcK7UXs4HsEgI0SOEOABgEYpCqCoU37Tmr66HMnmFWI1uKk+X1Tmb0r0NzmSyAUxhw/oZuLpmVKe5aRdZex+1kBLLR554Irk8GkIIH4rdfpr2LWf26RUIoZzN5QgUwwtK/O4xaGsawBQ2bNbQnQOyaT88HSYN5bF1+wAAf1y1y/e46Tfa1zdScq7CpKGYhJV1jurn/sef2rQf//PQOnzlvpe0ZdQzFfGhSFPU6wEsAzBdCLEbsIQOgGnytFkAtjuy7ZBps+R3b7orjxAiB6AXwOSAsvzqdjkRrSCiFfv27Yt2gyh2lnQygYIoHVRNi5505+rQmWfiKMrKTOI3HhY3zdPnD7OwLaptO294GO2HNaRAmd7RXJLmXgchPMf8z9Pl961jyPP8rh/mrtxOedPAa9JQ/DQQ5ww8+PpenPJNd1qYSZep7ZQg0p2WSgZvPV/8jfzzD2edWpr/tYFgP2rQHZgEmvoNDoZ4q2s9ElugENEEAPcC+JwQ4lDQqT5pIiA9ah53ohA3CSEWCCEWTJ06NaB6wdgCRe7f4+1Q7nUjGg1FVjuUyUujlYTbsdWfooZSeoYqNqj8fF7vQwk7mOoEgslZqZJNGtCMzmZtHQsB7Rhma3ujbyyMliHxRmEVrxkgtB3f45q8/G7FNOAHmrxC9H/TDN+ZrruSGnB110gnrSEtq+1n1qfuN+4bKZqavH3VtTQgINIz6LcxmbxSUrWOu4nk7Uu3YOmm/bHKiEIsgUJEaVjC5FdCiN/K5D3SjAX5uVem7wAwx5F9NoBdMn22T7orDxGlAHQC6Akoq2qoDpCSHTYoAkS7U3AZi/N0ETemGbx1HX/sGaifhhJiwVfxYQ9S97XZAZidsUaBY9onLWAGGLRSO8hh782vNRkK10cgXg2ifA3FsFLe+E5e/Qzbey07LazJK4T2of2dA8yqQgi73fQCRWoomig4k2nR+Xpu7zVcQQUBAmUkq29708QpKSescfdq+9p9q/GR//d0rDKiECfKiwD8AsAaIcR3HYfuB7BQfl8I4D5H+iUycmseLOf7cmkW6yOis2SZl3ryqLI+COAR6Wd5CMB5RDRJOuPPk2lVQ3UENQPydqhCCIejouy9vJzpBmEVWGaAD0UVG8bx6j/7D37QvWXo0rX57fqF8w2YtISS3y+E0FZjuEnghDN5eTUU96cfzmPGsOGx1lCcEyBN1cJoKIEasqt+/ucUX8Pgf9zk5+gfcQoU9zGTyUsljQYIe1MfsQWKcUJQn8TZeuVNAD4O4EUiel6mfQnAdQDuIqLLAGwDcDEACCFWE9FdAF6GFSF2hRAiL/N9BsCtAFoAPCD/AEtg3UFEG2FpJpfIsnqI6BoAz8jzvi6EML8EIgbq51czIO8DUY7JK9Q2FZoorzDvSdHNoHOBPhQY6xa0DiXMgBhUvmnmpo6bt+YI0FACBrQwg5U5bDjceUDpgC88n/7lBw9o7vJLG8oUGp0ztIG7TwpXcILLnGjQQgHzxMLv6LBDiMZ9H4qu+dwCRd9HgnYSCLNFTZT7bwQiCxQhxBPQj13navJcC+Ban/QVAE72SR+GFEg+x24GcHPY+sZFzbqUhuJV2avplA8zew7TAdWAkfCNUrKOBc1sw3T2qPeukvUCJ/h4mPOCfChhFuaZ9mGyrx1icqmL8grCeYbJl+TnQxCaPmWX6RQoPvm9e305u9HGvX2BZXvzawdUe2ZSemxoNG9/j+piKE58/AtwmiKDfSilP7LzvkdyeWRSyZJzbC1XU/9cwFqvRoBXyoek6EPRaCiu2Yt/GWW9Atj58LrSzXXVla4eAl+Tlyz3Qd+dcC1sDcV3sApW5Yt1CJ6ZmQRmWIHlO8N2+lDy+t9Puy2ISUMpY16pi/IK+2oA4wakPh1FZ0a1j5tm4AETm8Vr9haPGfwjQDST13DWKVCqo6G41poI7zGnQNGXDbiFnxPTc2IKSqh3WKCERP3AaU0Uhml2pztXh27GHLQgy1S+6qx+6yjUYNg3nEPvkP+iKvWw+YWkRvVdFPMHmwJMx73n6Zy6unqEW5hnECghtSjAx6keYgRxlmvy2fr/RsFamO4dPHZ+zSSn9Dr+6aa9wgCDycshUPQvuVP5dc9J8PWD6uj2AfloKI6koay/QDGGDcd0xgPxI8TiwAIlJLZTPuUfNlwIMaBH3stL+Kc7caZm0v4/q+1D8TnmLFY3S1b19nuY7Ag2k4ZiGEi0TSPc5+koDhilx4IGBN3rApw4F7f6XztcGwB+PhTzzNR5zLhew+83Ev7fFeU45QPXpOh+4wAN0VsHvz7o3D4+jEDwo9hP/Y8H7WdmivJy3t+gRkOxw4Z1gQsmm1gITBGA1YQFSkhsk5dBQ0knqSJ7eZW9DkUAsye1BJZpP2wBTnnXeR7ychDwm/2GnZ2bd5k1aChGH4p+UHdGRgVpKGE2N/S/tvsziBKTVxgNpQwt2G/ANgoMUxSTZpITdJ7r+vng6welA573kWgEUs4QilfUpM0agrcNTD4gZ5m1NHmxQGkE5C+sorx0CxvTyYRx0Ct7YSOcD7JeQ9HNnO06BvhQnNfQPqwFJVD8NBQL062Z3mZpMnmZBtKg85zhnCUr5Z0rvTVl68wY3muHcbCXLmx0fwaVDwRowfLH9fuNTFv4mI6bXsDlV44Tl4ZiMMv6HVUTAiKzWVdbN4Ovzh0A4z5mCrxxNrlWQzEKlPjCwLRLQjVhgRIS1X9UlFfpgFQUKPrFeerT/IPrtrLQD8iiGL2lKb4YNuzjQ3Hk0c1w1EPkJ3BsDSWidlZ80PzzqfLNA4b7fCdBr3A1bYwIAJ/99XMA/HcaAJyOdf+6iYABNcweaGH8PKoP+L+zx/ndR0MxlB8m2tB7HSfuATm4j/kVryYEremkUSDpMG0uGdQGWdPWK47zn99+wLd8lU035qtrxLB4Gd+FU01YoIRge88glqzdA8CxUl6jDjel9BqKOieUU17TsXV9RaA4mJjeJRG0l1dQ/XK2U16/xsFs2w+um97k5fge0H5BJq+gV7gGzUy96B2+wW3gbFdvG5azD5S3LCdyXZzvoGJyqht9BC4fVPH7Zbday8Ga08HbhpiipLx19KJWv7c0pUJdI+h4mN/Ie4qpfZx995Ynt/iWb9Jii/0gukQJWlhZbfid8iG44HuPY0CqsCnNXl7qQWhKJmJHKgH6EM+gAdv06l87ysu3bs7z/Duk0kxyBVGysE1lN5q8TG0ToIHZZQiBhOZug8JC3T4U74BeWoYOtZq5tI4qv38+V1CAZ4oaLlDD8V1zujWpENGivFxtUFp2TiMQl6y1QoYzqSSGs4VQe6HpNJSg7X3UQNnSlNC2l6qXrjVN6zxyAX4e02u+nff31tf47xtoMrmpiUA8DSVG5piwhhKCAYc9VAmUklW0oqihmN6nUfY6FOGf7kQI2JJC+7DIh8lvYaMzi84G655hu88Jq6EYV8oHaGB+9SgtR3+d0QCnbhinvCIZcfv6oCiz4kCiv7Z7N2CdhqLfusOZxT/KK3gluvOaflu/ZFKJkuu4yw+hoQT0A3XN1nQq8jNm0oSDXgJm8qGopCkTmlwr7t3nqPr5Hq6IyYud8g2Ebi8vV5SXbtBUPogQAkW3+23QXl5GDSVg65Uw5pSgAVEdMT0I+ge9tB7l1s+0Xmc0X0BTSrMXmzOv4XlMGDQU3fTYGeXkFcjhXrrm+K5pJxU0stvnNc+m7WVMM/CcQaDo2tbv+tpXAAcIhFHb5JXU5s/aWnSwBhRGi/Q2QdgouNamlGvNjJNiVLBB4PlXLxS1NHmxQCkTtVLe+8Bt6xkEYKn92hj7kLN4wDNjdqTrFzY6fCjGGaLvdsM2Jqe8dY5nQDao8gpn27gEgCG/8/nV72bruI5mQGptSvoeNzmknXXVmbyKDledQC74fgfKN4Pqo7ysuu11vChK4fxd/UxK5hm4Q6AE+GjCRHmZfBh+v9+Icso3JfWTnrx+8S1QFOpB17etECV9RO+Dc5bZlklpIwJNmrzaJXo0FxxRGASbvBoINZh4Zxhfu281AMsxqZshlGXy0pgnglYI23XTlBn4gixn2LDBKQ/47EWl6mG4tazGsWmO8ioVPl5UeU3JBIQoPS+bL6AlnSy5trdMv9KdbaIzeak6holAKtFQZHtu2NPvm9dbZ5Mm59yG3e/6flV0lu+ngZiOq6CHIJNfk4qSNJhV/XwstsmrSR/lpZ49XaST6RXD+YIo7tfnOSdony+g2IfbmpLadSjqHL1AtNI37RvAroOlr+oOA5u8GoiiU97/eGtTSvuwlOOU10V5Bc3gdTNnhRIIviYvx/2E0VBK7lGocoLvLauJtDK9DyWUUHX4sbzlA9aA1KLRUEw+FOcAqjN52TsJGAYz6xx/DenVQ6WmKkUYs59qv77h0u1zXIO0wansNylyHh/xESjKzKPrAoWCMJvFAoTyaIgoL3WOKZowSOjprBC6KDeFOt3SUPz7gMqm93MWD/zuuZ3+Jxlgk1cDoQsbVrRl9PZdk4aie0lRmME0L4RWe1KoQcxvPHRqKGF8KHoNJVig6FYbmxza4Xwo1mfxFQPuOo44TF4lUV4ycypBxgixlEagOLUs37DbvHNA8jrlQ2itDg1Md7qqg9+A75ph++Q3+UiCwp6BYvBKkA9FOe61ZsG8/hmxBUpaH0lpCxTftVLC1pCDTF7pZAIJKn2OnBOFoN2a2zJJrQ/FuFI+b+5nJtjk1UCkNVFeigmZFLJ54dsZbRt7CKel24cSPBAAnoWNGux1KAGvALbqaq6fbvt1k0Bxzp7yPgJUf3/F7wc1m1caNZR8Aa3plO8xdW+pJBnXsGgHo7y+faxrFtO8JhHnMd3Ls4qLZ0mrySmh4VeGzn+lcA6Cvvk1AmfKhAwA4KNvOFJbNmC1sUlDUe3gpwFk8wUkE2St9dLkH7E1FH+TnKpa0KQpmSAkqLQfOF8J4PeM2D6UppTe5KUmlQEakpoYRjVdscmrgehoSQPQd8jWJv8BSzeQOnFHmPhrKEH+g7A+lKAXbAH6DplzzbDdV1H/mqx5rkgZl01apgWYs9T9bZcBEH7nAI7dDDwPvdPkpY/SS4RYw+J7eePWIs60A4Nuoeisz+Cof8iprUVp1jrlC8JO9zN7uHcDKC1/yCBQCqIoEJzHu9rSOP+k6Xj3a2eU3Iu3/iaBkg3SUPIFpJOEVEK/DkUJFD+nvBrkE6R/TW++UEBKChRvE5p8WMUor6R5t2FNH8rlhe3nM72VUwcLlAaiUwoUZ4c67isP2N/VTr9+g5lC/zD5D1qmcE5VZtHk5V/3IN9NvlCwHab62Z9+wAnzTnrAfY9+DvqgvcqmtVsz4UM+/gGg+JDajl/PU+uK8vJGqTmEka8PJW/de2dLOtTCPb93mjuveWBg1HXMOQDqBpKcS+j5z+AVfgOma8LiU/7QaB5E1oRD50OxBzvPvmiWmSj49bt5h1PeFKWVL5Rq+aM5q48mE/oNWG2nvM+IrQb5Sa1NGNZEUeUKlqafTlKJLyybL9hmKD+BpszOzUECxRA2nCsUkEoSMqmEr9kyDLyXVwNxwowOAG6B4vzhp0r1P+sdzAL2kVIcdMxa3Vt9m/MKoY8+UqgBR7ePkxKGfm/7A6wN73SvQFZFmjQU56DnbKIwUV5KmB8a8p/BqzZv1kRy7e0b0R6zTV4Jf5PXcFbZ75PGLfidddEd7xkc1R7TDSRKIDWn/QWKs4/5CQSno95vQBsazaMlnURT0j9S0SVQPBMka1Zv/R/kn9CZIxXOvuetw0iugKZUEskEaf2UKtzWzySlBvmJrWlk88L3WcpLp3wqmSiZ6efyDh+QT96CsLSflnQSo7lCYOi1rp9n8wKpRAJNsQQKaygNwcWnz0ZHszJ5lR5/7ykzbHOLd4Z61zPb7e86obDjQDFMsKB5sIJi/ItRXsEDnt/l8wVhD7a6KKXB0bw9qJfsluu5ho6sxjGtBrigNSZFgaJ7AZiV109LVGYyFTmjW4dibe5ZWra9MWFT0mWq87u+99oKp5Dp8WgozrbQDSRqoGhO+6/DUH0unSSM+MyQ/+HWFfZ3v2YezObR2pREUyqhdcork6F314GU1BwAQ9iwyYfi6FdeP8RoroBMyqChBER5qfImtjYBgK/jXGn66WQCoz6ReBnNhASwntkEkS10fcs39POcNOtlUvrlB0HsPTSM25ZuLTtfpWCBUgbHz+iAfB2Kdvahe0Xwtx9eb3/XPQyX31584HUvIwryMejCWe1ybLOS/7GMYfY4OJqzfUjezh5+YaNmHYrJ5CUss0prU1L7Rkk14KoH2nkfXjOZN8pL1T+VJP99pORA1dmaxlA2r9kLy6GhBITdTmxN41XPSnZnXUc05piiQPH38yhhPSGTMg5GvlrYaB7N6aQ1mGkEipp0jLhMXpYpSC2qDAppNpm8nBMOr9lI7XSQCmPy8rl/p8kL0EXCFZBOJNCUJB8NpRD4jCg/nxK6fmYv9Szr+vlwroBmpSVG0FCuf3AdVm0/WKyTyWRQYVighOAtcqO3T7xxbskszNkx/vziq0UNRfNAT+/IaO23fY79f3KeB1ah36UVSBr28irOmPwHw6KG4l/AwEhRQ3HOvoQQxgVjiqzrvkoFSlD0TSpJ6GhOo89n0Z6z3kWzVqnw+p8PnlJybcAcNvy8fEi7WpuQKwjfwShoJwFn/Y6ZOgE7Dw659nvK54VtMtJpKGqAaU5pNBTZthOarUhD72Cy4KhJ9ne/Vh4clRqKZjDLC2H7oLIek1cyQRXRUJz9w/tOkdFc3vahFIT/YDkawik/qbW0Dxevb9UxnfIxeck+mCDNwsYCXBqKX6SXqp9unB9SQl2azcqld8hjSjU9kBWGBUoIvvn+1+Kx/3gbEgmy39ioOpvz4b/57xcUfQyeDj1vShv+9tSZ2HNoBE9u3F/S2fbJrTLeeMxkTGpNu8pVD0drUzIwAigp66brQuoB0oWEqu3H/d+XLTCUzePIrlYAwNb9g6689nlGp7y/tqW+mmzL7c0prVNe1UPdh/Naygcyo7MFCZ8XNDnfZ+M3e7zugbUAgK42a3brt/mf8+ENChueI9+sOegoI1so4ORZnQD0EUhZh8DURUEBVtiq83/F5AlNmDvZ+v38fqehrPShaOz3+QICnfKq7+ucwgVR9LXoBIrzufAzeSkNRV3Xi/qdA53ybXqT12jOMjml/XwoBasP6qLM8oWC5UNp0pu8lPYZFPjSnE6gKZnQaqpBeIsNs4i6krBACcGsiS04anIbAMucAFizdcDdad5x/PQSgaMYGMmhVT6MANDd795r6YxrFwOw/ASZVNI1qCjhNGVCpiTcVGGFdOofNKuu+tlbvlBAJqXXUAblfb5mejsA99YeYbYEUbg0FJ91G0ELvtJJQkdLOkCgFGfw3nqp36k5nUDKx+ms2iyT0oekAsXBaMBHoOjuzXsNZTZ0zsDzheLs32TyyqSCo7zam1OyHPc9DmULdli7XzMPZfNoaUpiQnNKu9Je50NJJsg2BwUFFSTlpEw3c1ZCDSjVUJT2oDRQP5OSEvR+7a/6QFHLLq2nElrpZAKjOY8PRUZ5JRL+/XQ0X0AmnSxqKL4CJbif24ERGrOjiUfkqwTsOrNAqW8myIe1f8R64PYcsgTD379xLgA4TF7FH1IIgYNDWUyUqjbgjuhy8r5TZyKTTrjMYmqAOf6IdmzY01cy4AghIARsgeAXsgoUO7jvGoV8sIbSLTWo6R3NSCXI9bC4IrcM/Ve3Ul6VMZzN42M/X4YLvvd4Sb5UMoGO5pQ2yksNIspx6qyXGkwyqaSl6Y2421A96G0Z/dY5QHH2/+BLr5Yc6x/OoV1OOPyivHbKoAs14A9IbXMkl0c2LzCxRW/bB4oDbFsmFbg9f1tGCRT3PQ5Lkxbgb8NfvrkHmVQSnS1pXz+VCvtNJcg1kVI+FNX/dAPhcC6PTCqJdJK05wyN5jF5QpO8X/fvrMKG2+1nsLQfqImOn4Y4aJu8VDv7aCj5AtJJfx9KVgYfpBIJ3z4yIoMGdAJRnQPoTcNOLbESW6iwhlLnKC3juW2WTf1nj20CAOyUG7kpDcY5ix4czWM0V0BXWxPu+fTZANxhox/66VL7u3KKKg0lly/g3+5aBQA46+jJyBWEKxoMAB7f0C3z6gXCXc9sxz0rdwBwL4BT5ArCntn7aTB7bYGSQUs66ZrduaObgh8C5yCh6pkvCBSEtaleNi/wxMZurH21z5XPcpZaGorf7FmdA/i/OXA4VzzW1pQq0TBUe7dlUoFhl0qQflOawOzys3m80j2ALjkY+gn1r/z+JQCwtV0lYLr7rb4wp8syhekEyvUPrrXr6FdF24ci+6B30B7K5jGhOQWi0msoH9Fj6/dh54EhPLvtYKlAyhZsDabf5e/zaigaH+FwDu3NKbQ0+W9NotpQDbZek1f/SA7N6QQmZNKyPHc/GMnl7UHYbyAdLPGh+GsoGamhlL5V0xKcSU1ouRIorbYVw0fgjRQnEbrdCvyc8nsPDeP7izdoV+ADarcM7z37T76qBQuUMlGRVA+89Cp6B7P4rQxD/ffzjgNQHBTW7D5k53lxZy8Ay1yiTCYHpUDZ2zeM5Vt67HMzqYRl8pIP5e2OEEDlv3CGzQohsPDm5QCKC/q84Y4A8KO/bHT9731YBkdy9szP72FU9zO9oxmZdNKjoRTP171YSLHOISjUdVRdpsqFi35YoakkfSj+11ADhBpQc74mryQmZFIl9RzJWWtsmnycsX/dsM/+/um3Hu17beVjUTPk/Z6wYKcTd9ZEq4+o4ALlP5s7pU2mlwpM50CSTvqvw7jtKauvBAmUtqYU2jOpksCGbsd291ukf8y78/HAaA5tTUl0NKft+xvNFZCT5jrlcPcbqNV9dbSk0Zz2X/j3l3VWO6vJmXeGv3X/AI6a3FbUUDz3oP5vbUr6rqXa0j2A9kzK7md+wTHbegYxtb1Z70NJknYdzKhcJ6Pa39vHeoeyrqAB/w02C9Ip7xYoP3v8FdyweD0efrlUM1Z8b/GGEgvBV3//Er75wBptnkrDAiUGv1xWHOznycHgqMltmNzWZA+cI7k8LrnpaQBAR3PaVrfVOoQ9vW5fSiadQHO66BRV9nYAtsnM2VGdpjNljvPTEuZPa3f971WnDw5lMXlCxtqWwudBe2TtXszpasGxUyegpSnhmmE6BZAupBcAXu0dxuI1RRuvGjBGwwiUQkGavNI4NJQtmd31j+Twz79+DgAca2UcobjK5JVOoC2TtM1N9vGc5UNqSiZKNLQfPFIUxhNbm/DhBXNwREez65yNe63Bd1pHM4jcghMA+h3XU2uZ1IClBMrxR1iLZrv73MIIcGu8bRlLw/K2wf2rdgEotmOJD0VGEHW2lpq0VLj7mXO7cMxUqy9718kOjuTRmknhmKltWC/vT83CJ2RS6GhOo6M5hY173feu7nU4W0B7JiU13NI+piZZX3r38db1HOcMjOQwMJrHEZ3Ndj/v8wzYSkhObEn7PgO7Dg5hTler7QfyrtXJ5gvoH8lhZmcz0qnSdSgjWec6mJLiMZzNI5NKaAXK0k37ARQ1aK9Q398/ghWVfjUAABohSURBVJ0Hh5CxnfIODUX2Ee/6JSfKAuFk8Zq9+Nljr2jzVBoWKDFwDlhqdgYAc7pasf2ANctb4hhAj5rcis6WNIiKezld++eXXWVmUkmpoaiZjPX51y+8vfggOTrinr7iegY1kPqZbPYPuAXXotV77O93PL0Vg6N5TGpNo6stU9Jpf/n0Vjy2fh9OmtGJRMIKi3TOmNX1JvkMVIr+kRy+u2idK+2AHECUeWhae3NJPsVormjyysmIMyeLX95jBzqohWvOdlA74bY2pdCWSaHf4UNZtf0gVu/qRUZGEJlWGrf6CKSOFuu3OXbaBMzsbMHW/QOu470Owe/9nX70qCWwZk1swcTWdEnABlA0SQHFDUiL9njhmgScKHdz8NNQWpqKQtl1TLbPf114Ev7zfScBcGsIAyM5jOYL6GhO44jOFrv/qrpPaE4jkSAcO20C7nt+V0n9VZ9VJi8/082Vv30RAPC246bJOhXbWAndqRMy6PB5DgDYZtLZk1p9w4r39o1ganvGdup7NSn1m7U0JS0fiqf9BrM5tDalkCQqWccEAIeGrXVa6jktMavK3+iT5xwt6+/+Db71oPV8vLijt8Qpr9qrdyiLbL6Aj/9iGZ7a2G0f7x3KYufBIRx/hHviONawQInA9z78OgCWucqPOV2t2N5jqe3bHBsZnjCjA8kEobMljdU7e7FiSw+efqXHlbcplUAmVdQAlBo/sTVdnPk4HqS9h4qDj3Lq9gyUDupqpbgqY+2rlglrYCSHr0rbfmdrE6ZMaMI+zwxZ2f6ntFvlr9/TjwdXF1VvNbjO6GzBcLbgq+HcsXQr7lphzaCu/BtrBqq0K+XfmNbh1lDUA5UvCPSN5NDZkrbNHbq1KABwtJxhH5Qx+cte2Y//XbYNTakE2posk4QzZPfCHz2Jp1/p0a4/8M70CwWBvuGcbQb83uL1+POLVnv890UnY96UNttspFCC9r2nzEBnq1ocag14anCf2p7BER3NePjlV13axx1Pb8Wn7lgJAPjsufNLBtR7n92J477yIADgzfOn2ALLK/RUBFFnS7pkx+Y+h6ahIsGcAkXNkKe1ZzC9I4Pu/hH0DIzi509sBmD51gDg2W0HMTiaL5mUqMGzvdnf5JX3MQk6r79PCtkp7Rnbh+I1ed29wtqN4sx5XQDcgRGbuwew/cAgprVn7PbxTn4+9DPLkjAwkpcr5T0CZdSKgtOFVR8ayqKzJY3WdBJEpfXbL31lR8nQbW8fVub0ixfMdl2ju38Ei9dYE8BntvRg/pcfwF83dOOy24oLob8l/WvD2Tzu/6c34foPvNZV9v8u2+aa1FQLFigRePvx1gzqV8u2+R6fM6kFOw8OIZcvYIfUVF76r/Pt412tTViydi8++NOl+LvXzwIATJa+FbXSdl/fiDVwjeRABGn7th4Ep0N/j+OFTMdOnwAA+Oljm7B8syWoRnJ5LPjvxejuH8WX3n08Vn71nQCKZhfVyQHrxcBT2zP2wwu4Z3knzuj0vV8Vqjh3ivWgOIWcYr+jzE+eM8+6Dzno/Faq6nOls1qh2s4ycVmah6r3lu6iBrD30DA+95vn7f+PmWK1w53Lt2NoNI8P3/Q0tvUMYkpbE4jINhl52d07jNZ0Ev0ec5LXNPL6I60Fgr9/bifuemY7vrd4g32ssyWNY6dNwLpX+1wzzO88bM0+P/3WY2xflxJcE1vTeOMxk5FMEAZGc9hzaAT3Plt8uZIS+ADw2Xcc64g0tO7hjqeLptevvvdEHCkHrM2yjYQQOOlrD9oRRLMnuTWobL6AL9zzAgAlUGSU0ohz4mL1s2kdGbxuzkQAwKZ9RR/LKbMmutpI/XaA1YculX6+9mbL5OV8AZUQAsd86c/2/22ZFDKphD0r39I9gItl4MrMzmbHpKI4QHb3j2CJ7Iez5Dofdf+5fAFv//ZfcHAwi2kdGUxqbQKR28/15MZuuz8mE9bz0evxVR4czKJdto9fBNehoSw6mlNIJAgTMqkSgfXc9oNIUNEX6hXqew8N46jJrfj4WUehq7UJ3f0jyOUL+OOqosb35Mb99ne1Y8PtS7fYY9FIroBTZk/Eha+b5Sr7S797scRKUQ0aWqAQ0QVEtI6INhLRlWN13c6WtEu1/OsX3u46PndyG/IFgbtX7sD2niGcPKvD1gyAovoOWI70yW1NdqhnkgjvOH4a9vaN4PkdB9E3nEVbk9VJ1YN03QNrcd0DazGczdszxyevfAdOO7K4EvqFHZaJZNPeAduEcs6xU+3Qzu8ssraCcdrm//bUmZgyIePaHl69QfD9p83CJWfMAQB8eMEc+3ihIGxV/ZxjrR0FHltfdGL3DIziTdc9gp8/sRmtTUmsveYC+yVl31+yAX3DWbsunS1pnH7UJHvxnVo8uVtuUzKpLW2vg/nwTU/bwu5dNxRDjFddfZ5tflq2uQf/cc8q+1i7FEZ+TnnF9I5mDGcL+Mljm7B6lxVM4TUdXfT6WZjT1YKXdx/CF+59oaSM04+ahKFsHid+7UFs6R7A67/+MB6VDuf50yfY/oqs3EDw2W0H7Z2Uh0ata/373atKygWsreu9UU5Oof+a6e2YNbEFzekENu8bsNtPmfymdzZjzqRWdPeP2prktX8qOm0nNKfs0OgBx6C5UQqPae3NdpTaii0HAACnzploa113fcqKYnRq5su39Ni/ZXtzWppMi+3/W4fw/Jdz5wOAa9C+e2VxH7wZE1vQ2pREKkH45gNr8Uk5S/+s9J8BlpbmrN9ex/M2uS2DZIIwsSWNHscA+9GfLyt+f8NRmNLehJ6BUbttv/HnNegZGMUpsyeWTEhGcnlc8atnsX9g1A4ZntnZgl2e7XU2d/djTlerLfC3eV7DsGpHLxYc1QUiwmtnd2IkV8D6Pf1oSiWhY8mavfbrxwHgW3IniOZ0aR61KLeaNKxAIaIkgB8B+BsAJwL4CBGdOFbXv++f3mR/Vyq64rWzrZn8Vb99EY+t31eybuI1DmH0mxXbcfTUNrxBquntzSmcdfRkAMD7f/wUbnlyi+3Ec+7V9dPHNuGErz2Ie1buQFtT0q6DeqC39wzirxv2YYtjJnriTMu2PlvO4H759FZbw7n3M29EZ0saR3Q2o2dg1HbwKdv9R8480r6+imT7+h9edoX3fviMOZjWnsETG7pxaDiL4WweG/b02VE7//au15R09NW7itFwx89ox72feSPukqHVL+7sxXA2j3ff+Ffr/olwnKPt1AzZORPsaE7Ze0oBwB9f2G1/V5rlhEwKfSM5ZPMF3L50i6s+yszxrQfX4T03PoHhbB5D2Txmdjbj+a+9yz5vwVFdePqV/a68amuT6dJhnysIfPHeF1yLUTMpazBMJwm/XLbVjiBTeZxRZO/74RN4YkPRTv6hBbMBADM6rXPVQKxMe59/12sAAESE4WwBP39iMwoFYUdPAcAHTpttO+3/uGo38gVh/9bvPGEa0smELZC3dA8gmy/g+e0H8eXfWVrStPaM3ddUGPMax294yuxONCUTtk9r2Sv7XRGPkyc04Zhpbdi0b8Due07zaVGgWEI/ly/Y5kTA+u2IyI6WXLxmD1ZtP4inpMP7zsvPwszOFqSThJd29mIkl8evlxctCe89xXpny5QJGXs/tfsdGsAvFi7ApLYmTG7LIF+w1o8Njubw//5qmfbedtxUtDen8NSm/fak5OlXevCnF61+pjYmnTyhyfWKgkfX7sVLOw/h/JOOwPT2ZjSnEy4t+z/vX43u/hF7oqq0wFuf2oxvPWS18/tPs7SOBz/3ZnzrA5bg+KRj/79bP3EG3jx/qv3/379xrm3+A4pWiWqSMp9St5wJYKMQ4hUAIKI7AVwI4OXAXBUik0pi7uRWbNk/WLIpo5pFK5STVPGTj56G9/7gCXvmdNLMTlz17uPxqbcejckTSiOduh1mqeVfPhdnXrsEgLU4anO32/l75rwuZFIJ3LZ0K25buhWnHWl1zBf/8zz7nG/83Wtx6c3Lbd8IUFTDL3/z0bjp8Vfw73evcs2SVQcHgK42q443P7kZNz9pPWiL/+2tSCYIc7pa8eDqV12DBAD845vn4eNnH2X/f/0HXosv3vsi/lHOMO/59Nl2lNO09macPKsD3120Hr9yRNJdcPIRAKzFn/ev2uXSTABrsCDNFv7f/dCpeP9p1oA8b0obhADmf/kB1znnnzQdF71+Fv7noWLwwPFftXwTl5wxx3b2AyiJBvubk4/Ade+3HnJnBNiyzUUf2dprLgBgDfjN6ST2HBrB39/yDIDifnGXnTMP/y01hhd29OJjv7Bmzt/78OtwkTSPqv5161NbcOtTWwAAC88+Cv8sB2MnJ3ztQVtzfe2sTjSnk7ZA+fzdq/B5+RvPndyKny88A4BlWkwnCT98dCN++Ggxwm1qe8YeyJ087tDQm9NJnDFvEn7//C783uOcP2PuJMyd3IaLT5+DHz26CW/4xhLX8X940zz7WWrLJPG753a63qu++Zvvtr8f1dVqa/oX/uhJANbveubcLiQShGxe4M5ntuNOxy7fy790LqbJ32ZbzyA27O3Hl373Ih6WffWhz73FnrDMlELztGsW2fm72powo7MZ5590BP6ybh8u/OETOGpym2t1+sKz5wKwJj8rth7AO7/7GP72lJm4YbGlhZ9z7BQkEoSjutrwiyc247jp7WhKJezf8RypXR3Z1Yp0kmy/47wpbfjOxafiG3/3WjSnk3jNtHaXdnzakRPxpmOnuNpTBVc8v/0g9h4aNm4eWwkaVkMBMAvAdsf/O2TamLHo396KFxwDtSKZIDzxxeJD9vWLTnIdn9bRjD999s0ArJnS5945H5lUEsc6Qnuf+fI77e+/v6KoDU1rb8bmb74b/3H+cXbaV95zgqv8Ux2D/7PbDuLIrlbb3ANYg9f3L3md/X97JoUpckHepLYm/Juc6SpOmNFh7wAAWIOnFxVqesXbjyk5BgCfP+8429wGAO85ZSYmtabRN5LD5LYmW3tSvO/UmQCKOxH85d/fZue//gOnlITt3nn5WfjBR15v///dD51qv5IWKAojwDJJeVn9X+fjZx9fgFkTW3Cfo70VJ81y+4/+j6NsALjmopNts8+Rk1tts4vi1k+c4dLOvuD4/YCiQCciLP/SuXZ7Kt554nT7uzOi0L6nuV2u/z9yplW/kVwBS1/ZjxNndNj35ZwcKLwRdp9407ySc5Ze+Q77+9prLsDbjpuKn37sdBzR6c7704+dXpL3U285Gnd/+o1oSiUwd0obZnry/Os7X4MvO/qxivRSXP+B17omCyfPKvXnPfS5t9iD5tlSy1d87KwjbWECAFfJwJD/XbYN3f2jOHFGh0v7PfuYyTjJ0yef/OI7QET4kDT5bto3YAuTWRNb8PRVRYGlhP7Gvf24YfF6ZFIJ3PDhU+1+obTlL9z7gu3/++M/n2O/b4mIcNk5RW31Ox861Z6IAJa1YuVX3omzj56MR//9bfjt/32T6xl18ro5E3HeSaXPbDUg0xv26hUiuhjA+UKIT8r/Pw7gTCHEP3vOuxzA5QBw5JFHnr5169i9K2DZK5ZafO4J032PD47m7IiaKKzY0oMZE1tKTG5Do3nc8tRmEAh/WLUL3/rgKb4P4P7+Edy1YgcufN1Me0amyOWtdR8jcrsMP3b3DoFAmN6RcT3s+YLA/zy0DjsPDuEt86fgb0+d6WvTHc7mccuTW3D+SdNx9NQJrmNCCKzb04c7l2/HiTM68KEz5riOd/ePYMeBISx+eQ/OPWGa7Sj38ui6vThuenvJ/Y3InWv/uqEbZx8z2fdhfHbbAXz4Z0vxg4+8Hu868QjH+2aK9f/2Q+twzLQJ9gDupHcoi0fW7kGCCO87daarjYQQ2NYziE37+rHn0IhvfsBq49FcwfZbKLL5AgZH8rh75XbMn96Ot75makne/pEc3nPjX7Hr4BAe+4+3u9qgdyiL1Tt78Y0H1qC1KYXvXHwq5kihpnh49avYsn8Apx81CdPam0uOB9EzMIpdB4ewZvchdPeP4tNvPdp1/yO5PLr7R/GbZ7bjg6fNtv0KzuMb9/aDQOhoSWH2JPfxgZEcntq0H7l8Ab1DWZx7wnTXOiYhBA4N5zA4msPQaB4zJ7aU9MHRXAGb9vXjjy/swrknTHf5IBU7Dw7hsXX78Pbjp2JGZ7H9/vTCbjz9yn4c2dWKC04+ApPamlx+0kJB4PqH1uI109rRlknh2GkTcOy0Yh/P5gu4Z+UOrN19CNM6mnHG3C6XecpZR78JxFhDRCuFEAuM5zWwQDkbwH8KIc6X/18FAEKIb+ryLFiwQKxYsUJ3mGEYhvEhrECpveiLzjMA5hPRPCJqAnAJgPtrXCeGYZjDloZ1ygshckT0TwAeApAEcLMQYrUhG8MwDFMlGlagAIAQ4s8A/mw8kWEYhqk6jWzyYhiGYeoIFigMwzBMRWCBwjAMw1QEFigMwzBMRWCBwjAMw1SEhl3YGAUiGgIQFFrcCaA34PiRAPz3rA+Xv9rHgfqvI9eP6xe3j9d7Hcdj/Y4TQpjf3iWEOGz+AOwzHL+pyvmrerwR6sj14/rFOd4IdRyP9QOwwvS7CCEOO5PXQcPxP1Q5f7WPA/VfR65fvOOHe/0qUcbh3oaV+A18OdxMXitEiP1oqpV/LKj3OnL94sH1i0+917Ee6xe2ToebhnJTjfOPBfVeR65fPLh+8an3OtZj/ULV6bDSUBiGYZjqcbhpKAzDMEyVOOwFChHdTER7ieglR9qpRLSUiF4koj8QUYdMTxPRbTJ9jXoHizz2FyJaR0TPy79pftercv2aiOgWmb6KiN7myHO6TN9IRDeS7l25tatftdpvDhE9Kn+v1UT0LzK9i4gWEdEG+TnJkecq2U7riOh8R3rF27DC9at4G5ZbPyKaLM/vJ6IfesqqVh+sZB3roQ3fRUQrZVutJKJ3OMqqShtWjDChYOP5D8BbAJwG4CVH2jMA3iq//wOAa+T3/wPgTvm9FcAWAHPl/38BsKDG9bsCwC3y+zQAKwEk5P/LAZwNgAA8AOBv6qx+1Wq/GQBOk9/bAawHcCKAbwG4UqZfCeB6+f1EAKsAZADMA7AJQLJabVjh+lW8DSPUrw3AOQA+DeCHnrKq1QcrWcd6aMPXA5gpv58MYGe127BSf4e9hiKEeBxAjyf5OACPy++LAHxAnQ6gjYhSAFoAjAI4VEf1OxHAEplvL6zwwwVENANAhxBiqbB65e0ALqqX+lWiHgH12y2EeFZ+7wOwBsAsABcCuE2edhuK7XEhrEnDiBBiM4CNAM6sVhtWqn5x61Gp+gkhBoQQTwAYdpZT5T5YkTpWiwj1e04IsUumrwbQTESZarZhpTjsBYqGlwC8T36/GIB6ofk9AAYA7Ia1kvXbQgjnYHqLVJO/WmVVVFe/VQAuJKIUEc0DcLo8NgvADkf+HTKtXuqnqGr7EdFcWLO/ZQCmCyF2A9YDD0tjAqx22e7Iptqq6m0Ys36KqrVhyPrpGJM+GLOOinpqww8AeE4IMYKxf47LhgWKP/8A4AoiWglLRR2V6WcCyAOYCcvc8HkiOloe+6gQ4rUA3iz/Pl6D+t0Mq5OtAPA9AE8ByMFSj71UM7yv3PoBVW4/IpoA4F4AnxNCBGmVuraqahtWoH5AFduwjPppi/BJq2gfrEAdgTpqQyI6CcD1AD6lknxOq6swXRYoPggh1gohzhNCnA7g17Ds1IDlQ3lQCJGVJpsnIU02Qoid8rMPwP+iumYI3/oJIXJCiH8VQrxOCHEhgIkANsAaxGc7ipgNYJe33BrWr6rtR0RpWA/yr4QQv5XJe6QJQZlj9sr0HXBrTaqtqtaGFapf1dqwzPrpqGofrFAd66YNiWg2gN8BuFQIocafMX2Oo8ACxQcV2UFECQBfAfBTeWgbgHeQRRuAswCslSacKTJPGsB7YZl9xrR+RNQq6wUieheAnBDiZalO9xHRWVKFvxTAffVSv2q2n7zfXwBYI4T4ruPQ/QAWyu8LUWyP+wFcIm3W8wDMB7C8Wm1YqfpVqw0j1M+XavbBStWxXtqQiCYC+BOAq4QQT6qTx/o5jkSlvfyN9gdrBr0bQBbWDOAyAP8CKxJjPYDrUFwAOgHA3bAcZS8D+A+Z3gYrYukFeez7kJE3Y1y/uQDWwXL6LQZwlKOcBbAejk0Afqjy1EP9qtx+58AyC7wA4Hn5924Ak2EFCGyQn12OPF+W7bQOjiiaarRhpepXrTaMWL8tsAI1+mWfOLHKfbAidayXNoQ1CRtwnPs8gGnVbMNK/fFKeYZhGKYisMmLYRiGqQgsUBiGYZiKwAKFYRiGqQgsUBiGYZiKwAKFYRiGqQgsUBimTiCiTxPRpWWcP5ccuzwzTK1J1boCDMNYi+qEED81n8kw9QsLFIapEHLjvwdhbfz3elgLOy8FcAKA78JaGNsN4O+FELuJ6C+w9jN7E4D7iagdQL8Q4ttE9DpYOwy0wlrE9g9CiANEdDqsPdEGATwxdnfHMGbY5MUwleU4ADcJIU6B9WqDKwD8AMAHhbW32c0ArnWcP1EI8VYhxHc85dwO4IuynBcBXC3TbwHwWSHE2dW8CYaJAmsoDFNZtovi/ku/BPAlWC9JWiR3Qk/C2qpG8RtvAUTUCUvQPCaTbgNwt0/6HQD+pvK3wDDRYIHCMJXFu5dRH4DVARrFQBllk0/5DFM3sMmLYSrLkUSkhMdHADwNYKpKI6K0fM+FFiFEL4ADRPRmmfRxAI8JIQ4C6CWic2T6RytffYaJDmsoDFNZ1gBYSEQ/g7WL7A8APATgRmmySsF6udhqQzkLAfyUiFoBvALgEzL9EwBuJqJBWS7D1A282zDDVAgZ5fVHIcTJNa4Kw9QENnkxDMMwFYE1FIZhGKYisIbCMAzDVAQWKAzDMExFYIHCMAzDVAQWKAzDMExFYIHCMAzDVAQWKAzDMExF+P+Q+CWh15XMVgAAAABJRU5ErkJggg==\n", 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E2IrT8+oGt+cUwPXA74BsnF5TT7rl9wEPiEgZToax2D1WtYj8AHjN3e4WVa3u30c9tgKhMNnp/k5l3oJMwbCS5o+2lzHGDC+9Bg1VfYnobQtPxNhnGbAsSnkpMCdKeStwVQ/HWg4s7+08h1ogGGZUdnqnMm9KkUAoTFa6RQ1jzPBnI8ITpC0YIiu9e/UUYNOjG2NShgWNBGltD5OZFr16yrrdGmNShQWNBGkLhjot9QpHq6ds/iljTKqwoJEgbcHu7RbeYD8LGsaYVGFBI0Fa26NlGlY9ZYxJLRY0EkBVaQuGuwWNNJ9VTxljUosFjQRoDymqkNl1nIYbRGwqEWNMqrCgkQCtQWfsYtdMw5uLKmjVU8aYFGFBIwHa2p1Molum4beGcGNMarGgkQBtPWQakSPCjTEmFVjQSIA2d8R31y63NiLcGJNqLGgkQGt7T5mGdbk1xqQWCxoJ4GUaPVVPBcOWaRhjUoMFjQToaAjvYe6pgFVPGWNShAWNBPC63PY4y61VTxljUoQFjQToOdOwEeH9sa+62ZbINSZJxbPc6xQReU5EtonIFhH5mls+RkRWichO97kwYp+bRKRMRHaIyKKI8rkissl970532VfcpWEfdsvXicjUiH2WuL9jp4gsIQl1dLntmmnYhIV9tuNQA++9/Tle2VU11KdijIkinkwjCHxLVU8BzgFuEJFZwHeB1ao6E1jt/oz73mJgNnAJcJeIeLfgdwNLcdYNn+m+D3AdUKOqM4A7gNvcY40BbgYWAPOBmyODU7I4mmlEHxFu1VPx27S/DoDthxqG+EyMMdH0GjRU9aCqvuG+bgC2AZOAy4EV7mYrgCvc15cDD6lqm6ruAcqA+SJSAhSo6lp16h7u77KPd6xHgYvdLGQRsEpVq1W1BljF0UCTNNo62jRsRPhAlVU0Ak4VlTEm+fSpTcOtNjoTWAeMV9WD4AQWYJy72SRgX8Ru5W7ZJPd11/JO+6hqEKgDimIcK6n01OXW7xNELGj0RVmFk2HstaBhTFKKO2iISB7wZ+Drqlofa9MoZRqjvL/7RJ7bUhEpFZHSysrKGKd2bBwNGv5u76X7fTaNSB94mYYFDWOSU1xBQ0TScQLGH1T1L27xYbfKCfe5wi0vB6ZE7D4ZOOCWT45S3mkfEUkDRgHVMY7Viareo6rzVHVecXFxPB8poVrbQ/jkaG+pSBl+n81yG6fW9hB7q5vx+8R6UBmTpOLpPSXAfcA2Vf1ZxFsrAa830xLgsYjyxW6PqBNwGrzXu1VYDSJyjnvMa7vs4x3rSuBZt93jaWChiBS6DeAL3bKk4izA5MftDNZJul+seipOuyubCCvMPb6QtmCYyoa2oT4lY0wX8WQa5wHXABeJyAb3cRlwK/BBEdkJfND9GVXdAjwCbAWeAm5Q1ZB7rOuBe3Eax3cBT7rl9wFFIlIGfBO3J5aqVgM/AF5zH7e4ZUmlrT3UrbutJ93vs6ARp7JKp2rq4pOd5jGrojLJbtnjW3li08GhPo1BldbbBqr6EtHbFgAu7mGfZcCyKOWlwJwo5a3AVT0cazmwvLfzHEqt7d2XevWk+30EglbNEo+yww34BN53YjE/enI7e6ubmTd1zFCfljFRhcPKirXvcqi+jctOLRnq0xk0NiI8AdqCoW7dbT1WPRW/sspGjhuTwwljcxGBfdUtQ31KxvSoqilAIBimqnFkVaNa0EgAp02j50zDZrmNz5GGAOMLsshK9zOhIMuqp0xSO1Dr3NRUNwWG+EwGlwWNBGhtD0XtbgtWPdUXTYEguZlOjemUMTk2wM8ktf1u0DjSaEHD9FHMTCPNGsLj1RwIkZPhBN+Jo7I4WG/VUyZ5eZlGTXOAcHjk3Bha0EiAtmC45zYNn7VpxKs5ECQ3w8k0RudkUNvUPsRnZEzPvEwjFFbqW0fO36oFjQRoC4ZitmlY0IhPc1uInEwn+I7JzaChLWjXziSt/TVHM+GRVEVlQSMBWtvDPY/TSPPZLLdxUFWnTcPNNApz0gEn9TcmGR2oa+m4WRxJjeEWNBKgLRgiq4eG8AzrchuXtmCYsNKRaRTmZgBQ2zxy0n4zvByobWXWxAIAqptGTrdbCxoJ0BYr0/D7bI3wODS1BQE6Mo0xOU7QGEl3cGb4aA4EqW4KcNqkUYBVT5k+itXlNjPN1zELrulZc8CZacbrPTU6x8s0Rs5/RjN8HKhtBWC2GzRG0s2NBY0EiNXlNivdT2t7KOp75qimgJtpuOM0xuR6mYZVT5nk43W3nVqUS0FW2ogaFW5BY4BU1QkaPXS5zUr302JBo1dNbc41yu7INKwh3CQvL2hMHJ1FUV4mVZZpmHj1tGqfJyvd37GGuOlZi1s95bVpZKX7ycnwUzOC/jOa4cMLEmPzMinKzbDqKRO/3oOGs3JfaASNGO0Pr3rKa9MAKMzJoNoyDZOEapsDZKf7yUr3MyY3gyprCDfxags6d8g9jQj3yr3tTHTNXdo0AApz063LrUlKtc3tHVWoRXkZVj1l4udVPfWYabjlXvWLic5r08jtmmmMoP+MZviobWlnVLYbNHIzR9T8U/Es97pcRCpEZHNE2fdFZH+Xlfy8924SkTIR2SEiiyLK54rIJve9O90lX3GXhX3YLV8nIlMj9lkiIjvdh7ccbFLxMoieGsK9ht1W63Ybk5dp5ERmGjkZ1uXWJKW6iExjTG4GobBS1zIysuJ4Mo3fAZdEKb9DVc9wH08AiMgsYDEw293nLhHxvk3vBpbirBk+M+KY1wE1qjoDuAO4zT3WGOBmYAEwH7jZXSc8qbT2lmm4wcS63cbW0XsqIviOGWENjGb4qG0JMDrb6RbudQ8fKT39eg0aqvoCEO+63JcDD6lqm6ruwVkLfL6IlAAFqrpWVRW4H7giYp8V7utHgYvdLGQRsEpVq1W1BlhF9OA1pLyG8J7aNLxBfxY0YmsOBMlO9+P3HV1ZeHROOvWtQYI2DYtJMpFtGvlZTnbc0BocylMaNANp07hRRDa61VdeBjAJ2BexTblbNsl93bW80z6qGgTqgKIYx0oqbW4wiNV7Cixo9KY5ECI3s3Pg9e7gakdI2m+GB1V12jQ6gobzbEEjtruB6cAZwEHgp265RNlWY5T3d59ORGSpiJSKSGllZWWs8064eMZpwNFqLBOdswBTWqeyQncqERurYZJJa3uYQDDcUT2Vl+llGiPj5qZfQUNVD6tqSFXDwG9w2hzAyQamRGw6GTjglk+OUt5pHxFJA0bhVIf1dKxo53OPqs5T1XnFxcX9+Uj91tqRafTQEG5tGnFpagt2GqMBEUHDut2aJFLb4tzEdKuearNMo0duG4XnY4DXs2olsNjtEXUCToP3elU9CDSIyDlue8W1wGMR+3g9o64EnnXbPZ4GFopIoVv9tdAtSypdJ9rryjKN+EQu9eopzHX+U1pjuEkmXi+p0W6X24IRVj2V1tsGIvIgcCEwVkTKcXo0XSgiZ+BUF70DfAlAVbeIyCPAViAI3KCq3i329Tg9sbKBJ90HwH3AAyJShpNhLHaPVS0iPwBec7e7RVXjbZAfNN68Uj0HDWvTiEdTINiR5nuKcjMBqBpBaxWY5OcNOPXaNPKyRlb1VK9BQ1WvjlJ8X4ztlwHLopSXAnOilLcCV/VwrOXA8t7OcSh5g/aye8k0bNLC2JrbQozLz+xUVpTnVE8dabBMwyQPL2h4bRp+n5CT4R8xmYaNCB+go9VT0eOvjdOIT+RSr550v4/CnHSOjKBpp03yq3PbNLxMA5x2jUYLGiYeze1BMtJ8ncYXRPKqp2whpthaAqGOpV4jjc3LpLLBgoZJHkczjcigkU5D28ionrKgMUAtURpwI2X4fYhYptGbaJkGQHF+pmUaJqnUtrST7pdO/+/zs9KsesrEpzkQ6jT1RVciQlaa3yYsjCEUVlrbw1Gr+MbmZVJpQcMkkdrmdkZlZ+BOnwc4mUa9BQ0Tj5ZAqMdGcE92hp9Wmxq9R0enRe9+HYvzrXrKJJe6lkDHGA1PfmbaiOk9ZUFjgJoD3QeldZWV5rNxGjHE6kwwNi+T5kCIphEycMokv9rm9k7tGWAN4aYPmgMhctJj91zOSvdbm0YMXkCIFnyL3W641q5hkkXkZIUea9MwcWtt7716KtOCRkyxRtWP9cZqWNAwSaKuxWnTiJSflU5Le4j2ETAjswWNAYo2/UVX2elWPRVLrOopL9Owdg2TLGqaAx2r9nm82QxGQhWVBY0Bao6jIdyqp2Krd+fyKciOEjTy3KDRaKPCzdBrCYRoDoQ6ZivweJMWNo6AtjcLGgPU0t57ppGVbr2nYqlt6TwtQ6QxuRmIWKZhkoNXTerdzHi8NTXqR0APKgsaA+T0nuqtIdxn4zRi8NYBH9WlcREgze+jKDfDgoZJClXujMtdM42CEbR6nwWNAQi7g9JiDe4DyErzW5tGDPUt7fjE6esezdi8o6PCQ2G17rdmyFS5f4dFXTKNPAsaJh7ezLW9tmlk+Gmz6qke1ba0U5Cdjq+H+bsiB/j9+OkdXPDj56izhZnMEKhy29bGdmvTcLLkxhEw/5QFjQHobQEmj2UasUUbLBWpOC+T8ppmmtqCPPTaXo40Brj7+V2DeIbGOLwpbby1Xjz5IyjT6HU9DdOzjrU0equeSvfZehox1La0MyqneyO450OnlfCXN/ez9IFSapvbOXF8Hr99eQ9j8zIYnZPBlXMn97ivMYlU1RggN8PfrXZhJAWNXjMNEVkuIhUisjmibIyIrBKRne5zYcR7N4lImYjsEJFFEeVzRWST+96d7rKvuEvDPuyWrxORqRH7LHF/x04R8ZaETRpHV+3rfUR4KKwjYuBPf9S1xM40Ljp5HAtOGMPLZVVMLszmviVnA/DDx7fxb396yzoZmEFT1dTG2C6LhQFkpvnJSPNZ7ynX74BLupR9F1itqjOB1e7PiMgsnOVaZ7v73CUiXki+G1iKs274zIhjXgfUqOoM4A7gNvdYY3CWll0AzAdujgxOycCbaK/3wX22EFMsdVEGS0USEf7zQ6cgAlfPP44pY3JY8+0LuenSkwFbDtYMniONbRTlRs+K8zNHxvxTvQYNVX0BZ+3uSJcDK9zXK4ArIsofUtU2Vd0DlAHzRaQEKFDVtaqqwP1d9vGO9ShwsZuFLAJWqWq1qtYAq+gevIZUb0u9eo6uE26ZRjS1Ld3n8unqtMmjWfWN97H0fdMAKBmVzfTiPACqm2zgnxkcVY2Bbj2nPCNl/qn+NoSPV9WDAO7zOLd8ErAvYrtyt2yS+7pread9VDUI1AFFMY6VNOJtCM+0TKNH4bD2Wj3lmTEun3T/0T/ZMW4PliobLW4GyZHGAGN7DBrpI2J69ET3norWZ1JjlPd3n86/VGSpiJSKSGllZWVcJ5oIze1x9p6yoNGjhrYgqsRsCO/JWLcHS5VlGmYQhMNKdVNbt+62Hss0YjvsVjnhPle45eXAlIjtJgMH3PLJUco77SMiacAonOqwno7Vjareo6rzVHVecXFxPz9S37W4bRrZvTSEH23TsOqprrzxFrHaNHpS1JFpWJuGOfZqmgOElR7bNPIyLWjEshLwejMtAR6LKF/s9og6AafBe71bhdUgIue47RXXdtnHO9aVwLNuu8fTwEIRKXQbwBe6ZUmjo3oqji63gM0/FUVti5MlxFM91VVOhp/MNJ9lGmZQeH9n0XpPgVM9NRImLOx1nIaIPAhcCIwVkXKcHk23Ao+IyHXAXuAqAFXdIiKPAFuBIHCDqnrflNfj9MTKBp50HwD3AQ+ISBlOhrHYPVa1iPwAeM3d7hZV7dogP6Sa424Id963rqHd1bqZRm8N4dGICGPzMq1NwwyKIz0M7PPkZ6WNiC63vQYNVb26h7cu7mH7ZcCyKOWlwJwo5a24QSfKe8uB5b2d41BpCYQQgcy02AlbVpq1afSkrqX/QQOcWXCty60ZDD1NIeIpyEqjsS1IOKw9TomTCmwakQFoaQ+Rk+7HHafYo6PVU9am0VVtx1oa/QsaRXkZ1uXWDAov04jVe0oVmgKpXUVlQWMAnAWYep+JxZvMbCR0x+urOm9a9P4GjVyrnjKDo6oxgE96/lvNGyELMVnQGICWQLDX7rYAhbnOH1mN3RF3U9vc7jadvM5EAAAgAElEQVRo934doynKc6qnnL4Txhw71c0BxuRm9Fj1NFLmn7KgMQDxrA8Ozrw0eZlp1ssningH9vWkKDeD1vZwR6cEY46V6kYnaPRkpNQoWNAYgJb23tcH9xTmplumEYW3lkZ/ef+JrYrKHGvVTQEKYwxC9TKNess0TE/izTQAxuRkUG0LB3VT19z7vFOxeI2S1oPKHGvVzYFuy7xG8laeTPVJCy1oDEBzIER2enxLkhTmZlimEcXhhlaK87P6vb9lGmawVDfFWz1lQcP0oKG1nbzMODONXOsa2lU4rByobWHS6Ox+H8O787Nra/qjpinA4nvW8tiG/TG3C4WVmuYAY+Konkr1Ng1bua+fQmHlUF0rJXF+4Y3JyaCm2b7YIlU0tNEeUiYXDiBouKNzj1j1lOmH0ndreHV3Na/urmbPkSa+/oETo25X19KOKjEzjZwMP36fWKZhoqtoaCUY1rjvkgtzM2gOhGxUeIT9tc0ATBpA0MjO8JOb4edIgwVk03c7KxoAZ3XIu9bs6jFLqHZvSsb0MLAPnGltnEkLUzvTsKDRT/trWoD4v/C8OxSrRjmq3L2GkwdQPQUwriCLiobWRJySGWHKDjdSMiqL6y+cTiAY5tntFVG3q25yAkGs6ilwZ7q1wX0mmv21ffvC87rqWdA4qryPgbcnxfmZVDRY9ZTpu7LKRmaMy2PucYWMy8/kyU2Hom7XkWnEqJ6CkbGmhgWNfvKCRrxfeF6DrbVrHLW/toUxuRnkxDEVSyzjC7KoqLdMw/RNOKyUVThBw+cTLp0zged2VNAUJVPwBubG6nILUDACVu+zoNFP+2taKMxJj/sLzzKN7sprBtZzyjPOzTRsKhHTFwfqWmgOhJg5Lh+AS08toS0Y5oW3u6/+6XWX721MkWUapkf7a1v6VK3ipbU2VuOo/TXNA+o55RmXn0lzIJTyE8WZxNpZ0QjAjHF5AJx1XCHpfmHj/rpu21Y1BcjPTOt1jrQ8d3r0VGZBo5/29/EueVR2OiLYqHCXqjqBNwGZxvgCZ3CgtWuYeARDYV7aeYStB+oBmOkGjYw0H9OL89h2sL7bPtVNAQp7ac+AkZFp2DiNfvC+8M6fOTbuffw+oTAno6NBbaSragrQ2h4ecCM4OJkGwOH6VqYX5w34eCZ1qSo3/WUTf3q9HHAWVIoMBrMmFvDSziPd9uttNLgn323TUNVe19kZrgaUaYjIOyKySUQ2iEipWzZGRFaJyE73uTBi+5tEpExEdojIoojyue5xykTkTncdcdy1xh92y9eJyNSBnG+i1LW00xwI9fkuuTAnnZomyzQgorttYc6AjzXOzTQqLdMwvfj5Mzv50+vlLD57CqdNHsVFJ4/r9P6skgIqGto6FlzyVDcFKIoz02gPKW0pvOBaIqqn3q+qZ6jqPPfn7wKrVXUmsNr9GRGZhbP+92zgEuAuEfEqCO8GlgIz3cclbvl1QI2qzgDuAG5LwPkO2NEvvL4FDZtK5Kh3q5qAvl/DaMYVHM00jOmJqvKHde/ygVPG8aOPn8rKG8/n9itP77TNrJICgG5VVPFXT6X+/FPHok3jcmCF+3oFcEVE+UOq2qaqe4AyYL6IlAAFqrpWne4v93fZxzvWo8DFkgQ5X0d329F9u0sutKlEOuw41ECaT5hWnDvgY+VnppGd7qei3jIN07PdR5o40hjg4lPG91h1dIobNLz2DnCCTdyZRmbqzz810KChwD9F5HURWeqWjVfVgwDus5f/TQL2Rexb7pZNcl93Le+0j6oGgTqgqOtJiMhSESkVkdLKyu7d5RJty4F6fAJTx/YtaBTnZ3KovtW6huLcyc0Yl9fvFfsiiQjjCjI5bNVTJob1e6oBmH/CmB63KczNoGRUVqdMo7opQFsw3FENGkux2752oDZ1s96BBo3zVPUs4FLgBhF5X4xto4V2jVEea5/OBar3qOo8VZ1XXFzc2zkP2Po9VcyeOKojFY3X9OI8apvbOWLTeLP9UAMnT8hP2PHG5WfaAD8T02t7qhmbl8G0sbGz21klBWyJyDR2VTpVqV7X3FjmTBoFwIZ9NQM40+Q2oKChqgfc5wrgr8B84LBb5YT77E3mUg5Midh9MnDALZ8cpbzTPiKSBowCqgdyzgPVFgzx5t7amHcrPTlxvPMl6U2SNlLVNgc4WNfaURWQCM78U8Mj06iob+XHT29nyfL1PPzaXss8B8m6PdWcPXVMr72azpgymp0VjR1jqsrc8RzT46hKHZWdzoxxeby5t3bgJ5yk+h00RCRXRPK918BCYDOwEljibrYEeMx9vRJY7PaIOgGnwXu9W4XVICLnuO0V13bZxzvWlcCzOsT/w97aV0dbMMyCfgUN505l5+HGRJ/WsLLtoBM0T05k0BhGmcZ3/7KJXz2/m7KKRr7z5018/eENQ31KKaf0nWrePnz05mx/bQv7a1viutk7d4bTlX7t7ioAdlU2kp3uZ+Ko+DptnDFlNG/uq03Zm4GBZBrjgZdE5C1gPfC4qj4F3Ap8UER2Ah90f0ZVtwCPAFuBp4AbVNWbJ/x64F6cxvFdwJNu+X1AkYiUAd/E7Yk1FFSVlkCIdburEIldL9qT4vxMCrLSOv0xj0ReffEpJYmrnhpfkEVTIJT0DZBVjW08/3YlX3zvNF789/fzqQXH8diGA0l/3sPJniNNXP2bV1n08xf49p/eoropwE//uQOAc6f3PrbqtMmjyM3w88ouZ7xGWUUj04pz8fni64Nz5nGjqW4KsK+6pV/n/8zWw1z3u9cIh5Mz6PR7cJ+q7gZOj1JeBVzcwz7LgGVRykuBOVHKW4Gr+nuOifTo6+V8588byc9K56Tx+YzuZYrkaESEE8fnj/hMY/uhesbmZTBuAMu8duXVU++saOSs4wp72XroPLHpIKGwcvkZE/H5hItOGscf1+1N+vMeTpY9vpUMv49PL5jCH9a9y+ObDtIcCPH1D8zkpDja0dL9PhZMK+KVXU6mUVbRyNzj4/+3OXOKs+2b+2o4rqhvnWXCYeXWp7ZTVtHIO1VNTEvCwao2jUicnt5yiDy3O90lcyb0+zgzx+fzdkVDyqau8dhyoJ6TJySuagqOdpXcfjC5s7jHNhzgpPH5HefrfYm9fSi5z3u4eGnnEZ7ZVsFXLp7J9z86m8duOJ+TJuRz9fwpfO3imXEf59zpReyubGLPkSb217bE1QjuOXF8HjkZ/n61azz/dmVHG0pkY3wysaARh2AozKu7q/nw6RN56+aFPS4JGY8Txzs9qCobh0ej7UDtq27m7jW7CLmp9r7qZrYcqOfcGd16Tg/IpNHZ5GWmsf1Qcv5HA2dAY+m7NXz0jIkdZZNGZ5OT4WfHCK+yTJQ7n93JxFFZfO68qYAzLchfv3weP/r4aX2a1sOrxvq/58oA+jQ9TZrfx/wTxvCPjQejTrMeyz0v7GZCQRbpfrGgMZy9VV5HY1uQ8+KoD+1NRw+qEVJFddeaMm57ajv3vrgbgL9vdDrGfeS0ibF26zOfTzh5Qn5SZxp/XLcXv0/4xFlHOwv6fOJknxY0Buz1d2tYv6ea6947bcDjf04pyefc6UU86s5R1ZdMA+CrF8/kSGMb9720J+59DtS2sHZ3Fde853hmjstny4Hus+0mAwsacXi57Agi8J7pA7879oLGxvLk/INIpLZgiMc3HiTNJ/z0n2+zeX8dKzcc4KzjRjNlzMDnnOrq5JJ8th2qT8qqv9b2EI+U7mPhrPFMGNW5Leek8XnsODS4NxHhsDNx31ObDw7q7z2WfvX8LkZlp7P47Cm9b9wLEeHOq89kfEEmPoHj+9g2cdZxhVwyewL3vLA77qmD1uxwBiYvnDWe2RML2HogOf+WLWjE4aWyI8yeWBDXLJe9Kc7P5NRJo3h6S/RlJVPJmh2V1LcG+fFVpzEqJ50r/u9lth9q4PIzJvW+cz+cPKGAhtYgB+qSr+vtE5sOUtPczmfOOb7beyeOz+dIYxtVg1hl+dc39/Pg+r184+G32FU5fLLe1vYQtz21ncc27CcQMSngkcY2Vm87zKcXHEduZmIm7x6bl8n9n1/AT646naz0vmcuN140g8a2YI/rjne1ZkcFk0ZnM2NcHrMnFlDVFOBwEk6NY0GjF1WNbbzxbg3nz0jcSPNL5kxgw75aDtb1r0vecPHYhv2MzcvgI6dN5PGvnM9V86YwrTiXD59Wckx+n9eFd3uU9RAG2ztHmjr9/MCr7zKtOJdzo2SrHY3hA6iyDIeVdburOn2R9qS1PcRP/7mDkyfkk5Xu42sPvUl7KHlnZW1tD/GzVW+zauthvvLgm9y9Zhdfe2gDH/3lSx1tZau3HSas8KEE/22dNCGfj581ufcNo5hVUsDonHTW76nqcZuWgPPZNpbX8nLZES48qRgRYbY7sjwZq6gsaPTibxsOEAwrHzszcXfHl7q9r57anLrZxrPbD/P0lsN85PSJpPl9jCvI4kcfP5Vnv3UhRXmZx+R3elV/0RbRGUzPbD3MhT9Zw+MbnaqfzfvreHNvLZ9ZcHzUxljvvDdHWTEuXnc/v4t/uedVvvHIBsJh7fgyjeZ3r7zDgbpW/t9HZvE/HzuVzfvreXD93n7/7mPtR09s487VO/ni/aWs2nqY739kFt//yCy2H2rghZ1Olc7TWw4zaXR2xyy1ycDnE86eOqZjzquuGlrbWfLb9dy5eiefuPsVmgIhLjzJmarvlJICROBHT27njlVvx/z39LS2h3rdJhEsaMSgqvypdB+nTR4VV//ueE0rzuOk8fk8uSk1g8br71bz5T+8waySAr75wf73NOur/Kx0Tp6Qz9/fOjikA6Pufclp9P/JP3fQHgrzh3XvkpXu4xNzo9+xjsvP5PQpo1n+8h5aAt3/46sq5TXNHT9XNbbx4s5K9lU7ZWt3VfHTf+5g2thcHt94kAt/soYTv/ckF/90DT96YlunkfI1TQH+77kyLjp5HOdOH8slcyZw7vQifrbqbeqScFXJf245xIq17/K586byq8/M5c6rz+Sz553ApxYcT2FOOo+WltPYFuSlsiMsmj0h6RY+WnDCGN6pau42bb+q8vWHNvDGuzX8vw/PomRUNplpvo5MNC8zjX9fdDJ5mWn8YvVOlr+0h8a2II+U7uP2p7azbnf37OVbj7zF4nvWHvPPZEGjB4fqWvnbhv1sP9TAVT38Zx+Ij54xkfXvVLNhX2rNUVNe08zS+1+nZFQ2v/vc2X2e1HGgrr9wOjsON/DUELUZbTtYz6u7qzl/xlj2HGni3x/dyN/ePMDlp09iVHb0ayEi/Odlp3CwrpXlL3fvbfOzVW/z3tuf45VdR3h6yyHm/89qrrlvPZ/89VrKa5r5xsMbmFqUy8qvnM+3F53E5MJsPn/eVCYX5nDvS3t47+3P8bc39wPwy+fKaGoL8p1LTu743f/14VnUt7Sz9IFSdiZRL65QWPnh49s4paSAmy49hUvmTOCjpzu97jLSfFx+xiRWbT3M3WvKCATDLJw9fojPuLsFJzhB4JVdR1i/p7rjZuZPpeWs3l7Bf1x2Cp8//wRW3ngeK288v1N7zPUXTuevXz6XD5wynp/8cweX/eJF/v3Rjdy1Zhf//fetnX5Pa3uINTsqOGHssR8MaEEjinW7q3jf7c/xjYffIifDz0dPT3zD7ZJzp1KUm8FtT25Pyh4S/VHZ0MYXVpQSCIW5d8m8Y1YNFcuHT5vI9OJcfv7M20MyNceKV94hK93HLz91JvOnjuGvb+5nUmE2X7pgWsz95p8whoWzxnP3ml2dVo3bfqieu9fsQhVufmwL3/vbZk4an89Prjqdw/WtXPaLF6lsbOPni88gLzONG94/gz9+8Rz+80OzWPH5+Tz7rQs4Y8povvWnt/jKg2+y/OU9XDV3SqfM+ZSSAm79+GlsO1jPZXe+yMq3DkQ7xQELhZWvPvgmd60pi2v7JzcfZG91M1+7eAYZad2/qq6aN5lAKMz/PbeLs44bzbw+jNoeLKeU5JOXmcZ3Ht3EJ3+9lt++8g6H61u55R9bOWfaGD577lQARudkRK3NEBH+52NzyM7wEworf/zCAm669GS2HqzvWMgMnGyzKRAalMBpQaOLPUea+NLvX2fKmGz++IUFrP7WBYzKSfzdcl5mGl+5aAZrd1fF3bsime050sTH736Zd6qauOvTZw3ZWt1+n/DtRSfz9uFGLvzxGlZtPTxov7upLcjKtw7w0dMnMjong/uvm8+G//dBnvnmBXFNB/HdS0+mtT3EL57ZCUAgGOY7j26kIDudWz9+KjsrGqluCnD7ladx5dzJfPnCGdS3Brnh/TM4bfLoqMc8viiX+z57NrMnFvD3tw5wzTnHc/NHZ3Xb7pNnT+G5f7uQM48r5GsPvckjpfuiHG1gfv/qu6x86wC3P7WDe17YFXNbVeVXz+9i2thcPjgr+gwMsyeO4n8+diq//ezZPPqv55LmT76vszS/j4tOHseonHROHJ/Hr57fxQ/+sZVAMMxtnzgtrvmsxhVk8cw3L2DVN9/HuTPGctmpTmP/kxFtov/cepjcDH/UjhaJlpi+aSkiGArztYfeRIDlnz2b44sGvqpcLJ9acDx/WLeXbz+6kb9/5fw+rzmeLFSV7/55Iw2tQR5e+h5OnxL9C2ywXDJnAitvPI/v/nkT33x4A6u+eUG3sRHHwhPuHEefnOeME8hK9/epq+a04jw+teA4/rBuL1ecOZGVGw7wVnkdd3/6LC6ZM4GtB+uZWpTbsWbD1z8wkwXTxvCeabG/KPIy03jwi+dwqL41ZjAvysvk/s/P57oVr/Fff9vMWccV9nlQWzTlNc28sbeWHz+9g/fOHEtBdjr/88R2zphSGHXizwO1LfznXzexeX89t33iVPwxvlg/teC4AZ/fsfazT56OiLB+TzVX/+ZV/rHxIP96wfQ+fb+Mjcjap4zJ4bTJo3hyk3OccFhZtfUwF540LiGLmvUm+ULzELrvpT1sLK/jlsvnHPOAAU697K+vmUt7MMyXf/960s5q2ZuXy6pYt6ear188c8gDhue0yaO5+zNn0R4O872/bR6UKsBHXy/nhLG5fZrcrquvXTyT/Kw0PnH3WlasfZcvnH8Cl55agohwy+Vz+Pz5J3Rsm+b38d6ZxXHdYedmpsWV/WWl+7njk2eQneHnqw++yf+u3tlj75947KtuZuEdL/DVB9/E7xN+eMUcfnLl6UwclcXNK7fwx3V7mb/sGS79xYvcuXon+6qb+cTdr7BuTzX/9eFZXDV34AP1hlqa34ffJ7xnehHnTi9iXH4mN7x/+oCOeemcEt4qr+OfWw5xz4u7OdLYNmhtOpIq9emeefPmaWlpaZ/3e7eqiYV3vMD7TizmnmvmDmovjL+8Uc43H3mLe66Zy8LZ/Z8McTA1tLaTl5lGMKxc+au1VNa38ty3LxyUO52++M0Lu1n2xDY+duYkln1sDjkZiU+uN++v45lth/n5Mzv59qKTuOH9MwZ0vIr6VlZtO0xFfRs3XjSD9CGodnlq80G++tAGAsEwPoFvLTyJzDQfkwuzuWRO7LEQzYEg3/vbZuYeX8hz2yt4ZVcVD1w3n1NKCjqu/+MbD3LDH98AYO7xhWT4fazdXUVGmo9Mv4+HvnQOsyeOOuafc7C1BEK0tIcGPFC4uinAZ+5dx1a3e/klsydw59VnRm37iZeIvK6q83rdzoKGoz0U5r6X9vCxMycxPo61gBMpGApzwY/XMHF0Fn/613MH9Xf3propwB9efZdgWPmXs6dQ3RTgNy/u5rENBzjzOCereHNvLT/75On9HgR1LIXDyi+fK+OOZ97mtMmj+cMXFnTMVhzL1gP1/PblPRysa6UoL4NzpxfxyXlTut1MbN5fxyfufoW2YJiTJ+Rz/3XzEzrl+1AKBMO0tIf41iNv8cy2o21DV8+fwnumj6VkVBbzji9ERFBV1u2pJj8rjTtX7+TpLUe3/4/LTmbp+zrfWasq3350I3mZafznh04h3e/j0dfLuWtNGT+8Yk5c616MdG3BEP+7uozczDS+9L5pca/30RMLGsPM8pf2cMs/tvLn688dUPVGoqgq9699l1uf3E5LewgR8P5UMtJ8fOKsyTy7/TBNbSFu/cSpfDjBExAm2lObD3HDH99g7vGF/PazZ8ecaqK2OcClv3iRxtYg04pzqWho42BdK7dcPpvLTi3hhbcraWkPEQiGuffFPYRV+dsN5w36zcZgCYWVDftqmDQ6h9++sodfP7+7473ji3L4+gdmsquiiV8+d7RX1H99eBZZ6T427qvjhx+bMyTZkumblAoaInIJ8AvAD9yrqrf2tO1wDRqNbUHed/tztIfC/Mdlp7Bw1viOLqvev9FgVZmVVTTw33/fyos7j3DBicV870OnkJHm44lNh5g4Oov3TCtiXEEWre0hWgIhChMwJ9dgeGzDfr7x8AZOmlDAVy6awYHaFs6ZVsTsic4o4jf21rCpvI7V2yt4dXcVf7n+PE6dPIpwWPni/aU8/3Yl6X4fLREjb/Oz0vj9dQuSpi1nMOyvbaElEGLz/jqWv7ynY/LNT86bzLypYwiFlcVnd8/KTHJLmaAhIn7gbZylY8uB14CrVXVrtO2Ha9AAZ76ib/3pLV5/twaA951YzEdOK+GuNbs4VNfKuIJMxudnUew+jyvIZPbEAs6dPpbG1iB7qpqoqG9l0/46wupMfXKgtpVdlY1kpfupamyjLRjmzONGU5SbSUiVcFiZVJhNTkYaf369nKe3HKL03Rpy0v3826KTuPY90ae+GK6ef7uSG//4Bg2tR9c5KMrNIM0vHZPDicB/fWhWp0bn+tZ2vvC7UkpGZ/HF906jOD+TDL+PnEx/0rXjDKZQWHmkdB+VDW3c+P4ZA64iMUMnlYLGe4Dvq+oi9+ebAFT1R9G2H85BA5z/hG/sreGVsirufWk3Da1BZozL44ITi6lsaONwfSuVDW0cqm+l2Z1yIj8zjYaIxV68LorR5qvxCUTrpOWVnzwhnw+cMp7PnTd1SAbnDYaK+lb21bQwcXQWz26vYPP+OpoDIc6bMZb3nzSO7Ax/XO0exqSSeIPGcPifMQmIHGlUDiyI3EBElgJLAY47Lvn7bcfidyc5O3vqGD59znFsKq/jvBljo/aKaGht58WdR1izo4Lji3I5aXw+Y/MzOXF8Hg2tQZ7YdJDji3I4bfJo2oJhCnPSEYS3ymtpDgTxiSAivHOkiYN1rXz4tJKOMQCpbFxBFuPc9odPL+g+VbkxpmfDIdO4Clikql9wf74GmK+qX4m2/XDPNIwxZijEm2kMhy4N5UDkCJ/JwLGZHMcYY0xMwyFovAbMFJETRCQDWAysHOJzMsaYESnp2zRUNSgiNwJP43S5Xa6qW4b4tIwxZkRK+qABoKpPAE8M9XkYY8xINxyqp4wxxiQJCxrGGGPiZkHDGGNM3CxoGGOMiVvSD+7rKxFpAHZEeWsUUJfAXzUWOJLA4yX6/JL9eHb9+s+u3cDY9etuLJCrqsW9Hk1VU+oBlPZQfs9g/J4BHC/R55fsx7PrZ9duqI5n128A12QkVU/9fahPoBeJPr9kP16iJfvnTebrl+yfNZmvHST/503o8VKxeqpU45g/Zbj8nlRl16//7NoNjF2/7vpyTVIx07gnxX5PqrLr13927QbGrl93cV+TlMs0jDHGHDupmGkYY4w5RixouERkiog8JyLbRGSLiHzNLR8jIqtEZKf7XOiWF7nbN4rIL7sc619EZKN7nNuH4vMMtn5cvw+KyOsissl9vijiWHPd8jIRuVNSab3ZKBJ87ZaJyD4RaRyqzzPYEnX9RCRHRB4Xke3ucW4dys+VtBLZtWs4P4AS4Cz3dT7OuuSzgNuB77rl3wVuc1/nAucD/wr8MuI4RcBeoNj9eQVw8VB/viS8fmcCE93Xc4D9EcdaD7wHEOBJ4NKh/nzD6Nqd4x6vcag/13C7fkAO8H73dQbwYqr/7fXreg/1CSTrA3gM+CDOQMESt6wE2NFlu892CRpnA89E/HwNcNdQf55kvX5uuQBVQKa7zfaI964Gfj3Un2c4XLsu5SMmaByL6+e+9wvgi0P9eZLtYdVTUYjIVJy7kXXAeFU9COA+j+tl9zLgZBGZKiJpwBV0Xnkw5fXj+n0CeFNV23DWhC+PeK/cLRsRBnjtRrxEXT8RGQ18BFh9LM93OBoW62kMJhHJA/4MfF1V6/tana6qNSJyPfAwEAZeAaYl/ESTVF+vn4jMBm4DFnpFUTYbEV38EnDtRrREXT/3Zu9B4E5V3X2MTnfYskwjgoik4/zR/UFV/+IWHxaREvf9EqCit+Oo6t9VdYGqvgcnRd55rM45mfT1+onIZOCvwLWqusstLsdZB94zItaET9C1G7ESfP3uAXaq6s+P/ZkPPxY0XG4PnfuAbar6s4i3VgJL3NdLcOpLezvWOPe5EPgycG9izzb59PX6uen/48BNqvqyt7FbjdAgIue4x7yWOK75cJaoazdSJfL6icgPcSb4+/qxPu9ha6gbVZLlgdMTSoGNwAb3cRlOb6jVONnCamBMxD7vANVAI84d8iy3/EFgq/tYPNSfLRmvH/A9oCli2w3AOPe9ecBmYBfwS9xBqKn6SPC1u939Wwy7z98f6s83XK4fTlarwLaI8i8M9edLtoeNCDfGGBM3q54yxhgTNwsaxhhj4mZBwxhjTNwsaBhjjImbBQ1jjDFxs6BhzCATkX8VkWv7sP1UEdl8LM/JmHjZNCLGDCIRSVPVXw31eRjTXxY0jOkjd1K8p3AmxTsTZyrua4FTgJ8BecAR4LOqelBE1uDMQXYesFJE8nFmof2JiJwB/ApnWu5dwOfVmb9sLrAcaAZeGrxPZ0xsVj1lTP+cBNyjqqcB9cANwP8CV6qq94W/LGL70ap6gar+tMtx7ge+4x5nE3CzW/5b4KvqzF9mTNKwTMOY/tmnR+ct+j3wHzgL+qxyZ1f1A/THot0AAADrSURBVAcjtn+46wFEZBROMHneLVoB/ClK+QPApYn/CMb0nQUNY/qn6/w7DcCWGJlBUx+OLVGOb0xSsOopY/rnOBHxAsTVwKtAsVcmIunueg09UtU6oEZE3usWXQM8r6q1QJ2InO+Wfzrxp29M/1imYUz/bAOWiMivcWZR/V/gaeBOt3opDfg5sKWX4ywBfiUiOcBu4HNu+eeA5SLS7B7XmKRgs9wa00du76l/qOqcIT4VYwadVU8ZY4yJm2Uaxhhj4maZhjHGmLhZ0DDGGBM3CxrGGGPiZkHDGGNM3CxoGGOMiZsFDWOMMXH7/9ERGSfUJwRvAAAAAElFTkSuQmCC\n", + "text/plain": [ + "
" + ] + }, + "metadata": { + "needs_background": "light" + }, + "output_type": "display_data" + } + ], "source": [ "sorted_data['inc'][-200:].plot()" ] @@ -251,10 +2354,8 @@ }, { "cell_type": "code", - "execution_count": null, - "metadata": { - "collapsed": true - }, + "execution_count": 16, + "metadata": {}, "outputs": [], "source": [ "first_august_week = [pd.Period(pd.Timestamp(y, 8, 1), 'W')\n", @@ -273,10 +2374,8 @@ }, { "cell_type": "code", - "execution_count": null, - "metadata": { - "collapsed": true - }, + "execution_count": 17, + "metadata": {}, "outputs": [], "source": [ "year = []\n", @@ -299,9 +2398,32 @@ }, { "cell_type": "code", - "execution_count": null, + "execution_count": 18, "metadata": {}, - "outputs": [], + "outputs": [ + { + "data": { + "text/plain": [ + "" + ] + }, + "execution_count": 18, + "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='*')" ] @@ -315,9 +2437,56 @@ }, { "cell_type": "code", - "execution_count": null, + "execution_count": 19, "metadata": {}, - "outputs": [], + "outputs": [ + { + "data": { + "text/plain": [ + "2021 938731\n", + "2014 1600941\n", + "1991 1659249\n", + "1995 1840410\n", + "2020 2053781\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": 19, + "metadata": {}, + "output_type": "execute_result" + } + ], "source": [ "yearly_incidence.sort_values()" ] @@ -332,9 +2501,32 @@ }, { "cell_type": "code", - "execution_count": null, + "execution_count": 20, "metadata": {}, - "outputs": [], + "outputs": [ + { + "data": { + "text/plain": [ + "" + ] + }, + "execution_count": 20, + "metadata": {}, + "output_type": "execute_result" + }, + { + "data": { + "image/png": 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\n", + "text/plain": [ + "
" + ] + }, + "metadata": { + "needs_background": "light" + }, + "output_type": "display_data" + } + ], "source": [ "yearly_incidence.hist(xrot=20)" ] @@ -365,7 +2557,7 @@ "name": "python", "nbconvert_exporter": "python", "pygments_lexer": "ipython3", - "version": "3.6.1" + "version": "3.6.4" } }, "nbformat": 4, diff --git a/module3/exo1/syndrome-grippal.csv b/module3/exo1/syndrome-grippal.csv new file mode 100644 index 0000000000000000000000000000000000000000..c5668a688173c1faf72393dba845f35d6a8f0277 --- /dev/null +++ b/module3/exo1/syndrome-grippal.csv @@ -0,0 +1,1978 @@ +# @source="réseau Sentinelles, INSERM, Sorbonne Université, http://www.sentiweb.fr", @meta={"period":[198444,202236],"geo":["PAY","1"],"geo_ref":"insee","indicator":"3","type":"all","conf_int":true,"compact":false}, @date=2022-09-16T14:58:39+02:00 +week,indicator,inc,inc_low,inc_up,inc100,inc100_low,inc100_up,geo_insee,geo_name +202236,3,23001,17464,28538,35,27,43,FR,France 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