From f8c67905cc8f8db19d148cf2457a75c2394136cb Mon Sep 17 00:00:00 2001 From: 6870d61c58e6946ec72c57da6f214d2e <6870d61c58e6946ec72c57da6f214d2e@app-learninglab.inria.fr> Date: Sun, 17 Jan 2021 17:05:53 +0000 Subject: [PATCH] =?UTF-8?q?Notebook=20ex=C3=A9cut=C3=A9=20pas=20=C3=A0=20p?= =?UTF-8?q?as,=20deux=20typos=20corrig=C3=A9es?= MIME-Version: 1.0 Content-Type: text/plain; charset=UTF-8 Content-Transfer-Encoding: 8bit --- module2/exo4/exercice.ipynb | 23 +- module3/exo1/analyse-syndrome-grippal.ipynb | 2210 ++++++++++++++++++- 2 files changed, 2193 insertions(+), 40 deletions(-) diff --git a/module2/exo4/exercice.ipynb b/module2/exo4/exercice.ipynb index 458afe6..703c7db 100644 --- a/module2/exo4/exercice.ipynb +++ b/module2/exo4/exercice.ipynb @@ -13,6 +13,13 @@ "source": [ "## 16/01/2021\n", "\n", + ":markdown:equation:" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ "Pour ajouter des équations dans des cellules Markdown, mettre les éléments entre des `$ $`.\\\n", "Par exemple:\\\n", "`$\\pi$` → $\\pi$\\\n", @@ -26,6 +33,14 @@ "metadata": {}, "source": [ "## 17/01/2021\n", + "\n", + ":python:matplotlib:" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ "Pour la fonction histogramme plt.hist(), bins = permet de fixer le nombre de barres, pas la largeur de l'histogramme.\\\n", "Une façon de contourner ça:\\\n", "`\n", @@ -66,11 +81,11 @@ ] }, { - "cell_type": "code", - "execution_count": null, + "cell_type": "markdown", "metadata": {}, - "outputs": [], - "source": [] + "source": [ + "Mettre des tags entre :: dans le journal pour faciliter la recherche des infos." + ] } ], "metadata": { diff --git a/module3/exo1/analyse-syndrome-grippal.ipynb b/module3/exo1/analyse-syndrome-grippal.ipynb index 59d72b5..24a6fb4 100644 --- a/module3/exo1/analyse-syndrome-grippal.ipynb +++ b/module3/exo1/analyse-syndrome-grippal.ipynb @@ -9,7 +9,7 @@ }, { "cell_type": "code", - "execution_count": null, + "execution_count": 1, "metadata": {}, "outputs": [], "source": [ @@ -28,10 +28,8 @@ }, { "cell_type": "code", - "execution_count": null, - "metadata": { - "collapsed": true - }, + "execution_count": 2, + "metadata": {}, "outputs": [], "source": [ "data_url = \"http://www.sentiweb.fr/datasets/incidence-PAY-3.csv\"" @@ -61,9 +59,976 @@ }, { "cell_type": "code", - "execution_count": null, + "execution_count": 3, "metadata": {}, - "outputs": [], + "outputs": [ + { + "data": { + "text/html": [ + "
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weekindicatorincinc_lowinc_upinc100inc100_lowinc100_upgeo_inseegeo_name
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.................................
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1889 rows × 10 columns

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weekindicatorincinc_lowinc_upinc100inc100_lowinc100_upgeo_inseegeo_name
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1888 rows × 10 columns

\n", + "
" + ], + "text/plain": [ + " week indicator inc inc_low inc_up inc100 inc100_low \\\n", + "0 202101 3 30168 24407.0 35929.0 46 37.0 \n", + "1 202053 3 21449 16669.0 26229.0 33 26.0 \n", + "2 202052 3 16428 12285.0 20571.0 25 19.0 \n", + "3 202051 3 21619 17370.0 25868.0 33 27.0 \n", + "4 202050 3 16845 13220.0 20470.0 26 20.0 \n", + "5 202049 3 12939 9923.0 15955.0 20 15.0 \n", + "6 202048 3 13804 10641.0 16967.0 21 16.0 \n", + "7 202047 3 19085 15285.0 22885.0 29 23.0 \n", + "8 202046 3 24801 20503.0 29099.0 38 31.0 \n", + "9 202045 3 42516 36857.0 48175.0 65 56.0 \n", + "10 202044 3 44567 38521.0 50613.0 68 59.0 \n", + "11 202043 3 43737 37523.0 49951.0 66 57.0 \n", + "12 202042 3 35145 29812.0 40478.0 53 45.0 \n", + "13 202041 3 27877 23206.0 32548.0 42 35.0 \n", + "14 202040 3 20443 16381.0 24505.0 31 25.0 \n", + "15 202039 3 19810 15900.0 23720.0 30 24.0 \n", + "16 202038 3 25562 21142.0 29982.0 39 32.0 \n", + "17 202037 3 18485 14649.0 22321.0 28 22.0 \n", + "18 202036 3 10390 7646.0 13134.0 16 12.0 \n", + "19 202035 3 9918 6842.0 12994.0 15 10.0 \n", + "20 202034 3 6084 3090.0 9078.0 9 4.0 \n", + "21 202033 3 6106 3411.0 8801.0 9 5.0 \n", + "22 202032 3 5918 3330.0 8506.0 9 5.0 \n", + "23 202031 3 4351 2269.0 6433.0 7 4.0 \n", + "24 202030 3 8179 5442.0 10916.0 12 8.0 \n", + "25 202029 3 8687 5860.0 11514.0 13 9.0 \n", + "26 202028 3 8340 5701.0 10979.0 13 9.0 \n", + "27 202027 3 4066 2406.0 5726.0 6 3.0 \n", + "28 202026 3 4039 2389.0 5689.0 6 3.0 \n", + "29 202025 3 2853 1488.0 4218.0 4 2.0 \n", + "... ... ... ... ... ... ... ... \n", + "1859 198521 3 26096 19621.0 32571.0 47 35.0 \n", + "1860 198520 3 27896 20885.0 34907.0 51 38.0 \n", + "1861 198519 3 43154 32821.0 53487.0 78 59.0 \n", + "1862 198518 3 40555 29935.0 51175.0 74 55.0 \n", + "1863 198517 3 34053 24366.0 43740.0 62 44.0 \n", + "1864 198516 3 50362 36451.0 64273.0 91 66.0 \n", + "1865 198515 3 63881 45538.0 82224.0 116 83.0 \n", + "1866 198514 3 134545 114400.0 154690.0 244 207.0 \n", + "1867 198513 3 197206 176080.0 218332.0 357 319.0 \n", + "1868 198512 3 245240 223304.0 267176.0 445 405.0 \n", + "1869 198511 3 276205 252399.0 300011.0 501 458.0 \n", + "1870 198510 3 353231 326279.0 380183.0 640 591.0 \n", + "1871 198509 3 369895 341109.0 398681.0 670 618.0 \n", + "1872 198508 3 389886 359529.0 420243.0 707 652.0 \n", + "1873 198507 3 471852 432599.0 511105.0 855 784.0 \n", + "1874 198506 3 565825 518011.0 613639.0 1026 939.0 \n", + "1875 198505 3 637302 592795.0 681809.0 1155 1074.0 \n", + "1876 198504 3 424937 390794.0 459080.0 770 708.0 \n", + "1877 198503 3 213901 174689.0 253113.0 388 317.0 \n", + "1878 198502 3 97586 80949.0 114223.0 177 147.0 \n", + "1879 198501 3 85489 65918.0 105060.0 155 120.0 \n", + "1880 198452 3 84830 60602.0 109058.0 154 110.0 \n", + "1881 198451 3 101726 80242.0 123210.0 185 146.0 \n", + "1882 198450 3 123680 101401.0 145959.0 225 184.0 \n", + "1883 198449 3 101073 81684.0 120462.0 184 149.0 \n", + "1884 198448 3 78620 60634.0 96606.0 143 110.0 \n", + "1885 198447 3 72029 54274.0 89784.0 131 99.0 \n", + "1886 198446 3 87330 67686.0 106974.0 159 123.0 \n", + "1887 198445 3 135223 101414.0 169032.0 246 184.0 \n", + "1888 198444 3 68422 20056.0 116788.0 125 37.0 \n", + "\n", + " inc100_up geo_insee geo_name \n", + "0 55.0 FR France \n", + "1 40.0 FR France \n", + "2 31.0 FR France \n", + "3 39.0 FR France \n", + "4 32.0 FR France \n", + "5 25.0 FR France \n", + "6 26.0 FR France \n", + "7 35.0 FR France \n", + "8 45.0 FR France \n", + "9 74.0 FR France \n", + "10 77.0 FR France \n", + "11 75.0 FR France \n", + "12 61.0 FR France \n", + "13 49.0 FR France \n", + "14 37.0 FR France \n", + "15 36.0 FR France \n", + "16 46.0 FR France \n", + "17 34.0 FR France \n", + "18 20.0 FR France \n", + "19 20.0 FR France \n", + "20 14.0 FR France \n", + "21 13.0 FR France \n", + "22 13.0 FR France \n", + "23 10.0 FR France \n", + "24 16.0 FR France \n", + "25 17.0 FR France \n", + "26 17.0 FR France \n", + "27 9.0 FR France \n", + "28 9.0 FR France \n", + "29 6.0 FR France \n", + "... ... ... ... \n", + "1859 59.0 FR France \n", + "1860 64.0 FR France \n", + "1861 97.0 FR France \n", + "1862 93.0 FR France \n", + "1863 80.0 FR France \n", + "1864 116.0 FR France \n", + "1865 149.0 FR France \n", + "1866 281.0 FR France \n", + "1867 395.0 FR France \n", + "1868 485.0 FR France \n", + "1869 544.0 FR France \n", + "1870 689.0 FR France \n", + "1871 722.0 FR France \n", + "1872 762.0 FR France \n", + "1873 926.0 FR France \n", + "1874 1113.0 FR France \n", + "1875 1236.0 FR France \n", + "1876 832.0 FR France \n", + "1877 459.0 FR France \n", + "1878 207.0 FR France \n", + "1879 190.0 FR France \n", + "1880 198.0 FR France \n", + "1881 224.0 FR France \n", + "1882 266.0 FR France \n", + "1883 219.0 FR France \n", + "1884 176.0 FR France \n", + "1885 163.0 FR France \n", + "1886 195.0 FR France \n", + "1887 308.0 FR France \n", + "1888 213.0 FR France \n", + "\n", + "[1888 rows x 10 columns]" + ] + }, + "execution_count": 5, + "metadata": {}, + "output_type": "execute_result" + } + ], "source": [ "data = raw_data.dropna().copy()\n", "data" @@ -122,7 +2118,7 @@ }, { "cell_type": "code", - "execution_count": null, + "execution_count": 6, "metadata": {}, "outputs": [], "source": [ @@ -143,7 +2139,7 @@ "Il restent deux petites modifications à faire.\n", "\n", "Premièrement, nous définissons les périodes d'observation\n", - "comme nouvel index de notre jeux de données. Ceci en fait\n", + "comme nouvel index de notre jeu de données. Ceci en fait\n", "une suite chronologique, ce qui sera pratique par la suite.\n", "\n", "Deuxièmement, nous trions les points par période, dans\n", @@ -152,10 +2148,8 @@ }, { "cell_type": "code", - "execution_count": null, - "metadata": { - "collapsed": true - }, + "execution_count": 7, + "metadata": {}, "outputs": [], "source": [ "sorted_data = data.set_index('period').sort_index()" @@ -179,9 +2173,17 @@ }, { "cell_type": "code", - "execution_count": null, + "execution_count": 8, "metadata": {}, - "outputs": [], + "outputs": [ + { + "name": "stdout", + "output_type": "stream", + "text": [ + "1989-05-01/1989-05-07 1989-05-15/1989-05-21\n" + ] + } + ], "source": [ "periods = sorted_data.index\n", "for p1, p2 in zip(periods[:-1], periods[1:]):\n", @@ -199,9 +2201,32 @@ }, { "cell_type": "code", - "execution_count": null, + "execution_count": 9, "metadata": {}, - "outputs": [], + "outputs": [ + { + "data": { + "text/plain": [ + "" + ] + }, + "execution_count": 9, + "metadata": {}, + "output_type": "execute_result" + }, + { + "data": { + "image/png": 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\n", 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\n", + "text/plain": [ + "
" + ] + }, + "metadata": { + "needs_background": "light" + }, + "output_type": "display_data" + } + ], "source": [ "sorted_data['inc'][-200:].plot()" ] @@ -246,16 +2294,14 @@ "Comme l'incidence de syndrome grippal est très faible en été, cette\n", "modification ne risque pas de fausser nos conclusions.\n", "\n", - "Encore un petit détail: les données commencent an octobre 1984, ce qui\n", + "Encore un petit détail: les données commencent en octobre 1984, ce qui\n", "rend la première année incomplète. Nous commençons donc l'analyse en 1985." ] }, { "cell_type": "code", - "execution_count": null, - "metadata": { - "collapsed": true - }, + "execution_count": 12, + "metadata": {}, "outputs": [], "source": [ "first_august_week = [pd.Period(pd.Timestamp(y, 8, 1), 'W')\n", @@ -274,7 +2320,7 @@ }, { "cell_type": "code", - "execution_count": null, + "execution_count": 13, "metadata": {}, "outputs": [], "source": [ @@ -298,9 +2344,32 @@ }, { "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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\n", 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" + ] + }, + "metadata": { + "needs_background": "light" + }, + "output_type": "display_data" + } + ], "source": [ "yearly_incidence.plot(style='*')" ] @@ -314,9 +2383,55 @@ }, { "cell_type": "code", - "execution_count": null, + "execution_count": 15, "metadata": {}, - "outputs": [], + "outputs": [ + { + "data": { + "text/plain": [ + "2014 1600941\n", + "1991 1659249\n", + "1995 1840410\n", + "2020 2042389\n", + "2012 2175217\n", + "2003 2234584\n", + "2019 2254386\n", + "2006 2307352\n", + "2017 2321583\n", + "2001 2529279\n", + "1992 2574578\n", + "1993 2703886\n", + "2018 2705325\n", + "1988 2765617\n", + "2007 2780164\n", + "1987 2855570\n", + "2016 2856393\n", + "2011 2857040\n", + "2008 2973918\n", + "1998 3034904\n", + "2002 3125418\n", + "2009 3444020\n", + "1994 3514763\n", + "1996 3539413\n", + "2004 3567744\n", + "1997 3620066\n", + "2015 3654892\n", + "2000 3826372\n", + "2005 3835025\n", + "1999 3908112\n", + "2010 4111392\n", + "2013 4182691\n", + "1986 5115251\n", + "1990 5235827\n", + "1989 5466192\n", + "dtype: int64" + ] + }, + "execution_count": 15, + "metadata": {}, + "output_type": "execute_result" + } + ], "source": [ "yearly_incidence.sort_values()" ] @@ -331,9 +2446,32 @@ }, { "cell_type": "code", - "execution_count": null, + "execution_count": 16, "metadata": {}, - "outputs": [], + "outputs": [ + { + "data": { + "text/plain": [ + "" + ] + }, + "execution_count": 16, + "metadata": {}, + "output_type": "execute_result" + }, + { + "data": { + "image/png": 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2Pmerrsn5nK26fuQr0xVzB/C0tvuHAnfWG8fMzLpVprBfDxwu6RmS9gZeB/xjb2KZmVlVHXfFRMQeSe8EvgIsAT4TETd3Me8Fu2v6qMnZoNn5nK26JudztuoWPV/HB0/NzOyJwVeempllxoXdzCwzLuxmZpl5QhZ2Saslre53jtlIeqak90g6od9ZZmpyNmh2Pmerrsn5mpwNqud7QhV2SUOSrgauAD4u6SX9ztRO0n8Evkb6Lp23SXp7nyP9QpOzQbPzOVt1Tc7X5GzQZb6IaPQfsG/b7dcCnyhuvxn4B2BNcV99yHYC8Izp+QMfAE4r7r8I+BIw3I98Tc7W9HzOlme+JmerO18jt9glHSDpryTdCnxC0mHFoN8BflTcHgN+CJwx/bRFzHeUpO8B/w34rKQTIrX2UcAhABFxHfBN4C2Lma/J2Zqez9nyzNfkbL3K18jCDpwI7EtasEeAD0haTtoteTVARDwMXAy8pLj/WK/CSDpU0gFtD50CXBIRLyV9wLxB0uHAhdP5CpcBR0vap1f5mpyt6fmcLc98Tc62WPn6VtiVLJX0Vklfl3SWpGcVg58NPBIRe4A/A34KnAZ8FXiKpF8rxrsV+LGk43qU8UhJXwa+AXxY0vTXFP8/YL/i9heBu4B1pE/UJ7ftYdxH+nbL5/0qZWt6PmfLM1+Tsy12vr4V9mJX4zeBNwEfA/YB/qYYfBdwd/HJ9GPSwjyL1ADf5/GvBV4G3Fs8XgtJK9ruPh+4IyKGgCuBTxSP3wc8LGn/iLgP+FfgqUWObwLvLcbbG/g5sD33bE3P52x55mtytn7mW7TCLuk4SR+VdHpxX8CRwBUR8aWI+BhwmKQXAztIn2BHFk/fBgwUj/0F8CpJryZ9KAwC3+0y25MknS/pemCjpIOKfGuAayUpIv4RuF/SOtKewv7FcIr7BwOPkfYwDpb0N8BFwJ6IuDvHbE3P52zVNTlfk7M1Jd+iFHZJzwH+EngA+D1J7y3mvRp4oFhogPOBN5AK9R7gxcXjN5COGD8UEdcAG4DTgeOB/x4Rj7VNo4qXFvN7FemgxNnAAaQvOzuk2LsAuKDI9+1iWV4JEBHfKqaxNCK2AWcCNwP/MyLeQneanK3p+Zwtz3xNztaMfHOdLlP1j7RlfQZpt2Np8difAmcVt1vAJ4GTgZcDX2l77tNIuyqQCvmNpF9hOgb438BT2sYtfTpS0bBnAleTunNWFY9/EXh3cfsZwMZi+LGk/rAlbcv2k2I6q0l7Eu8EPgt8CljRRbs1NlvT8zmbX1e33b//q3WLXdLzSQc4fxv4IPC+YtAO0m+mQvrkuRb4XeCfgUMkPVfSskj96TskvSQiriR93eVHgUuBiyLi36bnFUXLlHQS8BrgQ8BxpL59SGfbTO8d/Bj4OvDKiLie9Ik7UsxzCrgOODYidgBvJHUF3QW8LyIeLBuobU/j1U3LNoPbrprGtRu47brJ9kRouzI/jfdLJL0QOBz4akT8hLQ1fmtEnC7pBcA5klrAOPCfJO0XEQ9J+i7we6RzNC8E/gD4pKTdwCRwezGLvwIujIhdJTIpIkLSsaTdnK8DWyKdHvnrwG0RcaWk20lXr74C2Ar8jqRVEXGPpH8FHpT0dODPgdMkHUz61ah7SbtORMQEMFGh3VqkvZoHgI8DdwPP7Hc2t121bE+EdnPb5dd28ym1xa5kmaQ3SbqR1LF/IDBdeH8ObC+2vm8g7VocBzzE46fwADxK2gU5hLRVfhOpf/1q4J6IuAPSVnnFov5S4DOko8ovBz5SjPIYcKuk5RFxe5HvuaQX607S+aTTy7GE1D6XFBlPBdYCm6PiOa6SVkr6bDHN24FzI+JuSXuRPsn7mW1J0Xa/SdoVbEzbFevdgKTzaVjbFfMMScM0c53bR9KKhrbdAQ1vuwFJ+0q6gIa13YI66a8BVgAvLm4fWAT75CzjnUW6DHZ1cf9kUn/6YaSvALi6eHxfUjfMqrbnHgPs3UmeGfPcD3gbj2/5LwP+CHhHMfxJwPeK6Z9C6u8aKoadVCzLquL2JLCS1L//5fY8wF5dZLuIdMXYAKlr6cy2caaPQ7wT+B+Lla3tdT2DtLKtJx3gaUrbTWe7tFivDmpY2+0PbCH9khjAe5rQbjPyfRn46+L+x4C39bvtSO+JN5Pe/5c0re3a8l0J/H3xWGPWu07/Ftxil3Q2cBuwRdJgRNxP6he6s+gbf40ev0DoW6QDoNMXGl1LOoj6UERcAPxU0udIB0VvAX7RhxQRN0bEIwvlmZHtEOByYBj4HOkAxWtJewl7iun+lHTg9d2kvq+Defw0ymtI59I/EhGXA58mXc16HumI9aNt+Up9qs7I9nfA24tstwJHSNpYbEX9vtIFV1eQ9mB6nq3It4L05jqBdP3AK0jHPY4lbSn1s+3as20mnS3wWtI1DL/R77YrLCdde/EsSatI6/ySYpp9abdZ8u1NWteeSuriOFrSR/rVdpKWkY6xnQx8PCJ+txh0TNs0+9Z2M/J9LCKmt7gngaP62XaldfAJNkzavfhb4D3FY8eSitYdRfALgU3FsHOAD7c9/3rgmOL2PqRTgI6t41OJtPK+qO3+6aQtkzcD3257/KnAncXtd5Au231S8fwvAU9vG3dVj7K9iXSk+9eBvy/+Xg/8L9K5/IuWrW16B7bd/s+kN9Op/W67WbL9MemUsWc2qO3eTOprfT/wVtKBtOv73W6z5HsfaY9nVRPajrQHduqMx04BrmtC282R7+lFhr6vdx0vRwcLOn1qzinAeHF7GWlramVx/zDS1vqxpF3Ai0lbWv9E+qTapyfhUx+X4Be/3foCHu/uuZd0zuj0uF+jKLSk3aevFuP8ySJlOwb4xvSK2zbeMtLB5ROK++f0OtuMnAeQjm/sBD5c3L8XGOxX282S7a5ivisouvn61XZtr+dbSN1srwW+UDx2T7/bbY58Y8Vj7acL92W9I3VR3ApsKub/gaJ+3Acc3IB1rj3fVaQv5jq03+td6eUoscBPJl0o9Jzi/tIZw88HTp5egUhdD2fSo6I+x8p8AY+fL/854KPF7V8j7XE8ve2FOZq2rwRepGzvaH+suH1I0XbPXexsbRn+kHS+7WZSv/Y3izec+tl2M7KdRzqt7NlNaDvSV0YvIfWhXk3aMr4JeH+/17lZ8v0z6QyzFzSk7b5C2gN7Gmkr+CzShmFT1rn2fF8gXfp/eBPartO/6aLTEUmfAn4WERuK+3uRzrt8B/Ac4JQo2U9eF0mHkvq03hURtyp9odhokWs18J2o56qybrK9PSJuKx47htQtta7I9of9yNZO6TqEM0lvsiNJK+uh9LHt2rIdTXqz/TnpLKuT6FPbSRogdXPsQ2qn3yBdeHI2aUv5cPrYbrPkO5x0fOK3SMe8XkZqv76sdypOey5uP4/0Pr2WdEl939e5GfmOJl3pfi7pm2b7tt6VUfY89s3AucVBhiNJK/HxpBfl7H4V9cIxFOfASzqD1P9/NqkL6QeRTr/sd7YfFdluJ60ce0hb8Tf2MVu7e0kHAd8XEX8n6TTg5obku5/UT3wT6XVdRv/abg/p7IlHSVvqPyet/5PAexvQbnPle1jSa0gFv2/r3XTRLNxPOu70/oi4sAFtNzPfA6SN123Af6W/613Hym6xv450oPRh0jeOXRkRt/QoWymSriUdXNtOOof0QxHxvb6GKszIdhewoUHttpK0BfcG0vffbwbOi4hH533iIpgl26cjYlN/U/2y4sKT6b7su/qdZ6Yi38nAZyOdddLvPPuQfnPhjaQ96r8EPhXpa7r7bpZ8myPiz/qbqpyOC7uk55LO57yYdLCotq/K7VaxB/FB0pbw5yNdtdYITc4GIGkpqfvlYVK+Jr2ujc0G6aIu4LEos3W0iJqcT9KZpNNqP9e01xWan28hpbbYzcys+Zr603hmZlaRC7uZWWZc2M3MMuPCbmaWGRd2M7PMuLCbmWXGhd3MLDP/H+KofDj+oV4qAAAAAElFTkSuQmCC\n", + "text/plain": [ + "
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