Analyse de l'incidence de la varicelle (sept)

module3/exo2/exercice.ipynb

@@ -1105,7 +1105,7 @@
     {
      "data": {
       "text/plain": [
-       "<matplotlib.axes._subplots.AxesSubplot at 0x7f77a9a81710>"
+       "<matplotlib.axes._subplots.AxesSubplot at 0x7f9adc975668>"
       ]
      },
      "execution_count": 8,
@@ -1137,7 +1137,7 @@
     {
      "data": {
       "text/plain": [
-       "<matplotlib.axes._subplots.AxesSubplot at 0x7f77a79a0470>"
+       "<matplotlib.axes._subplots.AxesSubplot at 0x7f9ada88f4a8>"
       ]
      },
      "execution_count": 9,
@@ -1167,7 +1167,7 @@
    "metadata": {},
    "outputs": [],
    "source": [
-    "first_august_week = [pd.Period(pd.Timestamp(y, 8, 1), 'W')\n",
+    "first_august_week = [pd.Period(pd.Timestamp(y, 9, 1), 'W')\n",
     "                     for y in range(1991,\n",
     "                                    sorted_data.index[-1].year)]"
    ]
@@ -1197,7 +1197,7 @@
     {
      "data": {
       "text/plain": [
-       "<matplotlib.axes._subplots.AxesSubplot at 0x7f77a796f128>"
+       "<matplotlib.axes._subplots.AxesSubplot at 0x7f9ada80cd30>"
       ]
      },
      "execution_count": 12,
@@ -1206,7 +1206,7 @@
     },
     {
      "data": {
-      "image/png": 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\n",
+      "image/png": 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\n",
       "text/plain": [
        "<Figure size 432x288 with 1 Axes>"
       ]
@@ -1229,34 +1229,34 @@
     {
      "data": {
       "text/plain": [
-       "2002    502271\n",
-       "2018    543281\n",
-       "1996    553859\n",
-       "2017    557449\n",
-       "2019    584926\n",
-       "2000    605096\n",
-       "2015    613286\n",
-       "2012    620315\n",
-       "2011    645042\n",
-       "1995    648598\n",
-       "2001    650660\n",
-       "1993    653058\n",
-       "2005    654308\n",
-       "2006    657482\n",
-       "1998    660316\n",
-       "2014    673458\n",
-       "1997    679308\n",
-       "1994    682920\n",
-       "2007    701566\n",
-       "2013    708874\n",
-       "2004    736266\n",
-       "2008    745701\n",
-       "2003    770211\n",
-       "2016    780645\n",
-       "1999    784963\n",
-       "1992    821558\n",
-       "2009    822819\n",
-       "2010    848236\n",
+       "2002    516689\n",
+       "2018    542312\n",
+       "2017    551041\n",
+       "1996    564901\n",
+       "2019    584066\n",
+       "2015    604382\n",
+       "2000    617597\n",
+       "2001    619041\n",
+       "2012    624573\n",
+       "2005    628464\n",
+       "2006    632833\n",
+       "2011    642368\n",
+       "1993    643387\n",
+       "1995    652478\n",
+       "1994    661409\n",
+       "1998    677775\n",
+       "1997    683434\n",
+       "2014    685769\n",
+       "2013    698332\n",
+       "2007    717352\n",
+       "2008    749478\n",
+       "1999    756456\n",
+       "2003    758363\n",
+       "2004    777388\n",
+       "2016    782114\n",
+       "2010    829911\n",
+       "1992    832939\n",
+       "2009    842373\n",
        "dtype: int64"
       ]
      },
@@ -1277,7 +1277,7 @@
     {
      "data": {
       "text/plain": [
-       "<matplotlib.axes._subplots.AxesSubplot at 0x7f77a789df98>"
+       "<matplotlib.axes._subplots.AxesSubplot at 0x7f9ada789f60>"
       ]
      },
      "execution_count": 14,
@@ -1286,7 +1286,7 @@
     },
     {
      "data": {
-      "image/png": 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\n",
+      "image/png": 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\n",
       "text/plain": [
        "<Figure size 432x288 with 1 Axes>"
       ]