diff --git a/module3/exo1/analyse-syndrome-grippal.ipynb b/module3/exo1/analyse-syndrome-grippal.ipynb index 59d72b5b58a3ae26346460dd39e62a39c55243d7..e43b508a4ea4e4d74bf816a4c819e4ec90a27cbf 100644 --- a/module3/exo1/analyse-syndrome-grippal.ipynb +++ b/module3/exo1/analyse-syndrome-grippal.ipynb @@ -9,14 +9,16 @@ }, { "cell_type": "code", - "execution_count": null, + "execution_count": 1, "metadata": {}, "outputs": [], "source": [ "%matplotlib inline\n", "import matplotlib.pyplot as plt\n", "import pandas as pd\n", - "import isoweek" + "import isoweek\n", + "import os\n", + "import urllib.request" ] }, { @@ -28,10 +30,8 @@ }, { "cell_type": "code", - "execution_count": null, - "metadata": { - "collapsed": true - }, + "execution_count": 18, + "metadata": {}, "outputs": [], "source": [ "data_url = \"http://www.sentiweb.fr/datasets/incidence-PAY-3.csv\"" @@ -61,11 +61,981 @@ }, { "cell_type": "code", - "execution_count": null, + "execution_count": 17, "metadata": {}, - "outputs": [], + "outputs": [ + { + "data": { + "text/html": [ + "
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weekindicatorincinc_lowinc_upinc100inc100_lowinc100_upgeo_inseegeo_name
02022123185228171272.0199184.0279258.0300.0FRFrance
12022113122475112852.0132098.0185170.0200.0FRFrance
220221038790479741.096067.0133121.0145.0FRFrance
320220935018243958.056406.07667.085.0FRFrance
420220833096325942.035984.04739.055.0FRFrance
520220733488229446.040318.05345.061.0FRFrance
620220634662340398.052848.07061.079.0FRFrance
720220536297056043.069897.09585.0105.0FRFrance
820220437220964804.079614.010998.0120.0FRFrance
920220337461367144.082082.0113102.0124.0FRFrance
1020220235592049511.062329.08474.094.0FRFrance
1120220135762950699.064559.08777.097.0FRFrance
1220215235434947029.061669.08271.093.0FRFrance
1320215134169835359.048037.06353.073.0FRFrance
1420215033811732497.043737.05849.067.0FRFrance
1520214934016834716.045620.06153.069.0FRFrance
1620214834184236364.047320.06355.071.0FRFrance
1720214733659831338.041858.05547.063.0FRFrance
1820214633005925302.034816.04639.053.0FRFrance
1920214532036416564.024164.03125.037.0FRFrance
2020214431899915042.022956.02923.035.0FRFrance
2120214332704021935.032145.04133.049.0FRFrance
2220214232834323382.033304.04335.051.0FRFrance
2320214132504320586.029500.03831.045.0FRFrance
2420214032628621842.030730.04033.047.0FRFrance
2520213932215518014.026296.03428.040.0FRFrance
2620213831561412310.018918.02419.029.0FRFrance
2720213731367310404.016942.02116.026.0FRFrance
282021363102897505.013073.01612.020.0FRFrance
292021353126099282.015936.01914.024.0FRFrance
.................................
192219852132609619621.032571.04735.059.0FRFrance
192319852032789620885.034907.05138.064.0FRFrance
192419851934315432821.053487.07859.097.0FRFrance
192519851834055529935.051175.07455.093.0FRFrance
192619851733405324366.043740.06244.080.0FRFrance
192719851635036236451.064273.09166.0116.0FRFrance
192819851536388145538.082224.011683.0149.0FRFrance
19291985143134545114400.0154690.0244207.0281.0FRFrance
19301985133197206176080.0218332.0357319.0395.0FRFrance
19311985123245240223304.0267176.0445405.0485.0FRFrance
19321985113276205252399.0300011.0501458.0544.0FRFrance
19331985103353231326279.0380183.0640591.0689.0FRFrance
19341985093369895341109.0398681.0670618.0722.0FRFrance
19351985083389886359529.0420243.0707652.0762.0FRFrance
19361985073471852432599.0511105.0855784.0926.0FRFrance
19371985063565825518011.0613639.01026939.01113.0FRFrance
19381985053637302592795.0681809.011551074.01236.0FRFrance
19391985043424937390794.0459080.0770708.0832.0FRFrance
19401985033213901174689.0253113.0388317.0459.0FRFrance
194119850239758680949.0114223.0177147.0207.0FRFrance
194219850138548965918.0105060.0155120.0190.0FRFrance
194319845238483060602.0109058.0154110.0198.0FRFrance
1944198451310172680242.0123210.0185146.0224.0FRFrance
19451984503123680101401.0145959.0225184.0266.0FRFrance
1946198449310107381684.0120462.0184149.0219.0FRFrance
194719844837862060634.096606.0143110.0176.0FRFrance
194819844737202954274.089784.013199.0163.0FRFrance
194919844638733067686.0106974.0159123.0195.0FRFrance
19501984453135223101414.0169032.0246184.0308.0FRFrance
195119844436842220056.0116788.012537.0213.0FRFrance
\n", + "

1952 rows × 10 columns

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" + ], + "text/plain": [ + " week indicator inc inc_low inc_up inc100 inc100_low \\\n", + "0 202212 3 185228 171272.0 199184.0 279 258.0 \n", + "1 202211 3 122475 112852.0 132098.0 185 170.0 \n", + "2 202210 3 87904 79741.0 96067.0 133 121.0 \n", + "3 202209 3 50182 43958.0 56406.0 76 67.0 \n", + "4 202208 3 30963 25942.0 35984.0 47 39.0 \n", + "5 202207 3 34882 29446.0 40318.0 53 45.0 \n", + "6 202206 3 46623 40398.0 52848.0 70 61.0 \n", + "7 202205 3 62970 56043.0 69897.0 95 85.0 \n", + "8 202204 3 72209 64804.0 79614.0 109 98.0 \n", + "9 202203 3 74613 67144.0 82082.0 113 102.0 \n", + "10 202202 3 55920 49511.0 62329.0 84 74.0 \n", + "11 202201 3 57629 50699.0 64559.0 87 77.0 \n", + "12 202152 3 54349 47029.0 61669.0 82 71.0 \n", + "13 202151 3 41698 35359.0 48037.0 63 53.0 \n", + "14 202150 3 38117 32497.0 43737.0 58 49.0 \n", + "15 202149 3 40168 34716.0 45620.0 61 53.0 \n", + "16 202148 3 41842 36364.0 47320.0 63 55.0 \n", + "17 202147 3 36598 31338.0 41858.0 55 47.0 \n", + "18 202146 3 30059 25302.0 34816.0 46 39.0 \n", + "19 202145 3 20364 16564.0 24164.0 31 25.0 \n", + "20 202144 3 18999 15042.0 22956.0 29 23.0 \n", + "21 202143 3 27040 21935.0 32145.0 41 33.0 \n", + "22 202142 3 28343 23382.0 33304.0 43 35.0 \n", + "23 202141 3 25043 20586.0 29500.0 38 31.0 \n", + "24 202140 3 26286 21842.0 30730.0 40 33.0 \n", + "25 202139 3 22155 18014.0 26296.0 34 28.0 \n", + "26 202138 3 15614 12310.0 18918.0 24 19.0 \n", + "27 202137 3 13673 10404.0 16942.0 21 16.0 \n", + "28 202136 3 10289 7505.0 13073.0 16 12.0 \n", + "29 202135 3 12609 9282.0 15936.0 19 14.0 \n", + "... ... ... ... ... ... ... ... \n", + "1922 198521 3 26096 19621.0 32571.0 47 35.0 \n", + "1923 198520 3 27896 20885.0 34907.0 51 38.0 \n", + "1924 198519 3 43154 32821.0 53487.0 78 59.0 \n", + "1925 198518 3 40555 29935.0 51175.0 74 55.0 \n", + "1926 198517 3 34053 24366.0 43740.0 62 44.0 \n", + "1927 198516 3 50362 36451.0 64273.0 91 66.0 \n", + "1928 198515 3 63881 45538.0 82224.0 116 83.0 \n", + "1929 198514 3 134545 114400.0 154690.0 244 207.0 \n", + "1930 198513 3 197206 176080.0 218332.0 357 319.0 \n", + "1931 198512 3 245240 223304.0 267176.0 445 405.0 \n", + "1932 198511 3 276205 252399.0 300011.0 501 458.0 \n", + "1933 198510 3 353231 326279.0 380183.0 640 591.0 \n", + "1934 198509 3 369895 341109.0 398681.0 670 618.0 \n", + "1935 198508 3 389886 359529.0 420243.0 707 652.0 \n", + "1936 198507 3 471852 432599.0 511105.0 855 784.0 \n", + "1937 198506 3 565825 518011.0 613639.0 1026 939.0 \n", + "1938 198505 3 637302 592795.0 681809.0 1155 1074.0 \n", + "1939 198504 3 424937 390794.0 459080.0 770 708.0 \n", + "1940 198503 3 213901 174689.0 253113.0 388 317.0 \n", + "1941 198502 3 97586 80949.0 114223.0 177 147.0 \n", + "1942 198501 3 85489 65918.0 105060.0 155 120.0 \n", + "1943 198452 3 84830 60602.0 109058.0 154 110.0 \n", + "1944 198451 3 101726 80242.0 123210.0 185 146.0 \n", + "1945 198450 3 123680 101401.0 145959.0 225 184.0 \n", + "1946 198449 3 101073 81684.0 120462.0 184 149.0 \n", + "1947 198448 3 78620 60634.0 96606.0 143 110.0 \n", + "1948 198447 3 72029 54274.0 89784.0 131 99.0 \n", + "1949 198446 3 87330 67686.0 106974.0 159 123.0 \n", + "1950 198445 3 135223 101414.0 169032.0 246 184.0 \n", + "1951 198444 3 68422 20056.0 116788.0 125 37.0 \n", + "\n", + " inc100_up geo_insee geo_name \n", + "0 300.0 FR France \n", + "1 200.0 FR France \n", + "2 145.0 FR France \n", + "3 85.0 FR France \n", + "4 55.0 FR France \n", + "5 61.0 FR France \n", + "6 79.0 FR France \n", + "7 105.0 FR France \n", + "8 120.0 FR France \n", + "9 124.0 FR France \n", + "10 94.0 FR France \n", + "11 97.0 FR France \n", + "12 93.0 FR France \n", + "13 73.0 FR France \n", + "14 67.0 FR France \n", + "15 69.0 FR France \n", + "16 71.0 FR France \n", + "17 63.0 FR France \n", + "18 53.0 FR France \n", + "19 37.0 FR France \n", + "20 35.0 FR France \n", + "21 49.0 FR France \n", + "22 51.0 FR France \n", + "23 45.0 FR France \n", + "24 47.0 FR France \n", + "25 40.0 FR France \n", + "26 29.0 FR France \n", + "27 26.0 FR France \n", + "28 20.0 FR France \n", + "29 24.0 FR France \n", + "... ... ... ... \n", + "1922 59.0 FR France \n", + "1923 64.0 FR France \n", + "1924 97.0 FR France \n", + "1925 93.0 FR France \n", + "1926 80.0 FR France \n", + "1927 116.0 FR France \n", + "1928 149.0 FR France \n", + "1929 281.0 FR France \n", + "1930 395.0 FR France \n", + "1931 485.0 FR France \n", + "1932 544.0 FR France \n", + "1933 689.0 FR France \n", + "1934 722.0 FR France \n", + "1935 762.0 FR France \n", + "1936 926.0 FR France \n", + "1937 1113.0 FR France \n", + "1938 1236.0 FR France \n", + "1939 832.0 FR France \n", + "1940 459.0 FR France \n", + "1941 207.0 FR France \n", + "1942 190.0 FR France \n", + "1943 198.0 FR France \n", + "1944 224.0 FR France \n", + "1945 266.0 FR France \n", + "1946 219.0 FR France \n", + "1947 176.0 FR France \n", + "1948 163.0 FR France \n", + "1949 195.0 FR France \n", + "1950 308.0 FR France \n", + "1951 213.0 FR France \n", + "\n", + "[1952 rows x 10 columns]" + ] + }, + "execution_count": 17, + "metadata": {}, + "output_type": "execute_result" + } + ], "source": [ - "raw_data = pd.read_csv(data_url, skiprows=1)\n", + "if not os.path.exists(\"incidence-PAY-3.csv\"):\n", + " urllib.request.urlretrieve(data_url, 'incidence-PAY-3.csv')\n", + "\n", + "raw_data = pd.read_csv(\"incidence-PAY-3.csv\", skiprows=1)\n", "raw_data" ] }, @@ -78,9 +1048,73 @@ }, { "cell_type": "code", - "execution_count": null, + "execution_count": 4, "metadata": {}, - "outputs": [], + "outputs": [ + { + "data": { + "text/html": [ + "
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weekindicatorincinc_lowinc_upinc100inc100_lowinc100_upgeo_inseegeo_name
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" + ], + "text/plain": [ + " week indicator inc inc_low inc_up inc100 inc100_low inc100_up \\\n", + "1715 198919 3 0 NaN NaN 0 NaN NaN \n", + "\n", + " geo_insee geo_name \n", + "1715 FR France " + ] + }, + "execution_count": 4, + "metadata": {}, + "output_type": "execute_result" + } + ], "source": [ "raw_data[raw_data.isnull().any(axis=1)]" ] @@ -94,9 +1128,976 @@ }, { "cell_type": "code", - "execution_count": null, + "execution_count": 5, "metadata": {}, - "outputs": [], + "outputs": [ + { + "data": { + "text/html": [ + "
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weekindicatorincinc_lowinc_upinc100inc100_lowinc100_upgeo_inseegeo_name
02022123185228171272.0199184.0279258.0300.0FRFrance
12022113122475112852.0132098.0185170.0200.0FRFrance
220221038790479741.096067.0133121.0145.0FRFrance
320220935018243958.056406.07667.085.0FRFrance
420220833096325942.035984.04739.055.0FRFrance
520220733488229446.040318.05345.061.0FRFrance
620220634662340398.052848.07061.079.0FRFrance
720220536297056043.069897.09585.0105.0FRFrance
820220437220964804.079614.010998.0120.0FRFrance
920220337461367144.082082.0113102.0124.0FRFrance
1020220235592049511.062329.08474.094.0FRFrance
1120220135762950699.064559.08777.097.0FRFrance
1220215235434947029.061669.08271.093.0FRFrance
1320215134169835359.048037.06353.073.0FRFrance
1420215033811732497.043737.05849.067.0FRFrance
1520214934016834716.045620.06153.069.0FRFrance
1620214834184236364.047320.06355.071.0FRFrance
1720214733659831338.041858.05547.063.0FRFrance
1820214633005925302.034816.04639.053.0FRFrance
1920214532036416564.024164.03125.037.0FRFrance
2020214431899915042.022956.02923.035.0FRFrance
2120214332704021935.032145.04133.049.0FRFrance
2220214232834323382.033304.04335.051.0FRFrance
2320214132504320586.029500.03831.045.0FRFrance
2420214032628621842.030730.04033.047.0FRFrance
2520213932215518014.026296.03428.040.0FRFrance
2620213831561412310.018918.02419.029.0FRFrance
2720213731367310404.016942.02116.026.0FRFrance
282021363102897505.013073.01612.020.0FRFrance
292021353126099282.015936.01914.024.0FRFrance
.................................
192219852132609619621.032571.04735.059.0FRFrance
192319852032789620885.034907.05138.064.0FRFrance
192419851934315432821.053487.07859.097.0FRFrance
192519851834055529935.051175.07455.093.0FRFrance
192619851733405324366.043740.06244.080.0FRFrance
192719851635036236451.064273.09166.0116.0FRFrance
192819851536388145538.082224.011683.0149.0FRFrance
19291985143134545114400.0154690.0244207.0281.0FRFrance
19301985133197206176080.0218332.0357319.0395.0FRFrance
19311985123245240223304.0267176.0445405.0485.0FRFrance
19321985113276205252399.0300011.0501458.0544.0FRFrance
19331985103353231326279.0380183.0640591.0689.0FRFrance
19341985093369895341109.0398681.0670618.0722.0FRFrance
19351985083389886359529.0420243.0707652.0762.0FRFrance
19361985073471852432599.0511105.0855784.0926.0FRFrance
19371985063565825518011.0613639.01026939.01113.0FRFrance
19381985053637302592795.0681809.011551074.01236.0FRFrance
19391985043424937390794.0459080.0770708.0832.0FRFrance
19401985033213901174689.0253113.0388317.0459.0FRFrance
194119850239758680949.0114223.0177147.0207.0FRFrance
194219850138548965918.0105060.0155120.0190.0FRFrance
194319845238483060602.0109058.0154110.0198.0FRFrance
1944198451310172680242.0123210.0185146.0224.0FRFrance
19451984503123680101401.0145959.0225184.0266.0FRFrance
1946198449310107381684.0120462.0184149.0219.0FRFrance
194719844837862060634.096606.0143110.0176.0FRFrance
194819844737202954274.089784.013199.0163.0FRFrance
194919844638733067686.0106974.0159123.0195.0FRFrance
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1951 rows × 10 columns

\n", + "
" + ], + "text/plain": [ + " week indicator inc inc_low inc_up inc100 inc100_low \\\n", + "0 202212 3 185228 171272.0 199184.0 279 258.0 \n", + "1 202211 3 122475 112852.0 132098.0 185 170.0 \n", + "2 202210 3 87904 79741.0 96067.0 133 121.0 \n", + "3 202209 3 50182 43958.0 56406.0 76 67.0 \n", + "4 202208 3 30963 25942.0 35984.0 47 39.0 \n", + "5 202207 3 34882 29446.0 40318.0 53 45.0 \n", + "6 202206 3 46623 40398.0 52848.0 70 61.0 \n", + "7 202205 3 62970 56043.0 69897.0 95 85.0 \n", + "8 202204 3 72209 64804.0 79614.0 109 98.0 \n", + "9 202203 3 74613 67144.0 82082.0 113 102.0 \n", + "10 202202 3 55920 49511.0 62329.0 84 74.0 \n", + "11 202201 3 57629 50699.0 64559.0 87 77.0 \n", + "12 202152 3 54349 47029.0 61669.0 82 71.0 \n", + "13 202151 3 41698 35359.0 48037.0 63 53.0 \n", + "14 202150 3 38117 32497.0 43737.0 58 49.0 \n", + "15 202149 3 40168 34716.0 45620.0 61 53.0 \n", + "16 202148 3 41842 36364.0 47320.0 63 55.0 \n", + "17 202147 3 36598 31338.0 41858.0 55 47.0 \n", + "18 202146 3 30059 25302.0 34816.0 46 39.0 \n", + "19 202145 3 20364 16564.0 24164.0 31 25.0 \n", + "20 202144 3 18999 15042.0 22956.0 29 23.0 \n", + "21 202143 3 27040 21935.0 32145.0 41 33.0 \n", + "22 202142 3 28343 23382.0 33304.0 43 35.0 \n", + "23 202141 3 25043 20586.0 29500.0 38 31.0 \n", + "24 202140 3 26286 21842.0 30730.0 40 33.0 \n", + "25 202139 3 22155 18014.0 26296.0 34 28.0 \n", + "26 202138 3 15614 12310.0 18918.0 24 19.0 \n", + "27 202137 3 13673 10404.0 16942.0 21 16.0 \n", + "28 202136 3 10289 7505.0 13073.0 16 12.0 \n", + "29 202135 3 12609 9282.0 15936.0 19 14.0 \n", + "... ... ... ... ... ... ... ... \n", + "1922 198521 3 26096 19621.0 32571.0 47 35.0 \n", + "1923 198520 3 27896 20885.0 34907.0 51 38.0 \n", + "1924 198519 3 43154 32821.0 53487.0 78 59.0 \n", + "1925 198518 3 40555 29935.0 51175.0 74 55.0 \n", + "1926 198517 3 34053 24366.0 43740.0 62 44.0 \n", + "1927 198516 3 50362 36451.0 64273.0 91 66.0 \n", + "1928 198515 3 63881 45538.0 82224.0 116 83.0 \n", + "1929 198514 3 134545 114400.0 154690.0 244 207.0 \n", + "1930 198513 3 197206 176080.0 218332.0 357 319.0 \n", + "1931 198512 3 245240 223304.0 267176.0 445 405.0 \n", + "1932 198511 3 276205 252399.0 300011.0 501 458.0 \n", + "1933 198510 3 353231 326279.0 380183.0 640 591.0 \n", + "1934 198509 3 369895 341109.0 398681.0 670 618.0 \n", + "1935 198508 3 389886 359529.0 420243.0 707 652.0 \n", + "1936 198507 3 471852 432599.0 511105.0 855 784.0 \n", + "1937 198506 3 565825 518011.0 613639.0 1026 939.0 \n", + "1938 198505 3 637302 592795.0 681809.0 1155 1074.0 \n", + "1939 198504 3 424937 390794.0 459080.0 770 708.0 \n", + "1940 198503 3 213901 174689.0 253113.0 388 317.0 \n", + "1941 198502 3 97586 80949.0 114223.0 177 147.0 \n", + "1942 198501 3 85489 65918.0 105060.0 155 120.0 \n", + "1943 198452 3 84830 60602.0 109058.0 154 110.0 \n", + "1944 198451 3 101726 80242.0 123210.0 185 146.0 \n", + "1945 198450 3 123680 101401.0 145959.0 225 184.0 \n", + "1946 198449 3 101073 81684.0 120462.0 184 149.0 \n", + "1947 198448 3 78620 60634.0 96606.0 143 110.0 \n", + "1948 198447 3 72029 54274.0 89784.0 131 99.0 \n", + "1949 198446 3 87330 67686.0 106974.0 159 123.0 \n", + "1950 198445 3 135223 101414.0 169032.0 246 184.0 \n", + "1951 198444 3 68422 20056.0 116788.0 125 37.0 \n", + "\n", + " inc100_up geo_insee geo_name \n", + "0 300.0 FR France \n", + "1 200.0 FR France \n", + "2 145.0 FR France \n", + "3 85.0 FR France \n", + "4 55.0 FR France \n", + "5 61.0 FR France \n", + "6 79.0 FR France \n", + "7 105.0 FR France \n", + "8 120.0 FR France \n", + "9 124.0 FR France \n", + "10 94.0 FR France \n", + "11 97.0 FR France \n", + "12 93.0 FR France \n", + "13 73.0 FR France \n", + "14 67.0 FR France \n", + "15 69.0 FR France \n", + "16 71.0 FR France \n", + "17 63.0 FR France \n", + "18 53.0 FR France \n", + "19 37.0 FR France \n", + "20 35.0 FR France \n", + "21 49.0 FR France \n", + "22 51.0 FR France \n", + "23 45.0 FR France \n", + "24 47.0 FR France \n", + "25 40.0 FR France \n", + "26 29.0 FR France \n", + "27 26.0 FR France \n", + "28 20.0 FR France \n", + "29 24.0 FR France \n", + "... ... ... ... \n", + "1922 59.0 FR France \n", + "1923 64.0 FR France \n", + "1924 97.0 FR France \n", + "1925 93.0 FR France \n", + "1926 80.0 FR France \n", + "1927 116.0 FR France \n", + "1928 149.0 FR France \n", + "1929 281.0 FR France \n", + "1930 395.0 FR France \n", + "1931 485.0 FR France \n", + "1932 544.0 FR France \n", + "1933 689.0 FR France \n", + "1934 722.0 FR France \n", + "1935 762.0 FR France \n", + "1936 926.0 FR France \n", + "1937 1113.0 FR France \n", + "1938 1236.0 FR France \n", + "1939 832.0 FR France \n", + "1940 459.0 FR France \n", + "1941 207.0 FR France \n", + "1942 190.0 FR France \n", + "1943 198.0 FR France \n", + "1944 224.0 FR France \n", + "1945 266.0 FR France \n", + "1946 219.0 FR France \n", + "1947 176.0 FR France \n", + "1948 163.0 FR France \n", + "1949 195.0 FR France \n", + "1950 308.0 FR France \n", + "1951 213.0 FR France \n", + "\n", + "[1951 rows x 10 columns]" + ] + }, + "execution_count": 5, + "metadata": {}, + "output_type": "execute_result" + } + ], "source": [ "data = raw_data.dropna().copy()\n", "data" @@ -122,7 +2123,7 @@ }, { "cell_type": "code", - "execution_count": null, + "execution_count": 6, "metadata": {}, "outputs": [], "source": [ @@ -152,10 +2153,8 @@ }, { "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 +2178,17 @@ }, { "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 +2206,32 @@ }, { "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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nXBs9FWK1VdTfy2bSjH9jDig1VtQ51zxMhVjtFPX3spk049+YvwK4Dop0vynfw6l1FOn3spk089+Y11DsGF2Hjhz3Hk7+9Go2ckX8G/Maig2Lp0LMaquZ/8YcUFrQYIuB3hZpVlvN+jfmKa8W1Gr3ITKzkal2ysuL8i2kmRcD66Hr0BG+8+Qr3H/NBU0xPWGWNU95tRBfezAyzbjN0yxLHqG0kGZeDKwlj+zMquMRSotp1sXAWvLIzqw6HqG0GH8H+9B5ZGdWHQcUsyr4qnKzwXnbsJmZDchXypuZWV05oJiZWSYcUMzMLBMOKGZNqhm/wKlIWrH/HVDMmpSv7G+sVux/7/IyazL+vvjGyrL/83L/OO/yMsupWk+F+Mr+xsqy/4s2yvGFjWZ1Vv4mUYuvD/CV/Y2VRf8X9f5xDihmdVLPNwlf2d9YI+3/l2+fe9yvCc4zr6GY1UkRv0s8T/KynlAvd6zbyRPb9nLiCaP4zSdHG/qFeF5DMcsZT0WNTNHWE0aqiHcG9wjFrI5ufKyDSePGHjMVUn4HaPs871prvGpHKA4oZpZrnipsPE95mVlT8FRhcTigmFnuFXE9oV7ydIsXT3mZmRXYinU7+eG2vTXdBZbZlJekMyW9KOlNSbsk3ZrSJ0jaJKkzPY8vK7Nc0h5JuyXNL0ufLWlnem2VJKX0MZKeSulbJc0sK7M4naNT0uKy9Fkpb2cqe2K1nWNmVnTnrNjAzGXP8vjWvUSUrmuauexZzlmxoWFtqmbKqxf404j4MnARcIukc4FlwOaIOBvYnH4mvbYIOA9YAHxX0gmprgeAJcDZ6bEgpd8AHIyILwH3AfemuiYAdwIXAnOAO8sC173Afen8B1MdZmYtIY+32Bk0oETE/oj4h3R8GHgTmAYsBFanbKuBK9PxQmBNRPRExFvAHmCOpCnAKRGxJUrzbI9WlOmr62ngsjR6mQ9siojuiDgIbAIWpNcuTXkrz29m1vTyuFlhSLdeSVNRFwBbgTMiYj+Ugo6kySnbNOBnZcX2pbSP03Flel+Zd1JdvZI+BCaWp1eUmQh8EBG9/dRlZtYS8naLnaoDiqQvAH8D/ElEHErLH/1m7SctBkgfTpmB6jq2MdISStNszJgxo78sZmaFVH5R7Morv9LAlpRUtW1Y0mhKweSHEfGjlPxemsYiPXel9H3AmWXFpwPvpvTp/aQfU0ZSG3Aq0D1AXe8Dp6W8lXUdIyIeioj2iGifNGlSNf9cMzMbhmp2eQl4GHgzIv6i7KX1QN+uq8XAM2Xpi9LOrVmUFt+3pemxw5IuSnVeX1Gmr66rgBfSOstGYJ6k8Wkxfh6wMb32YspbeX4zM2uAaqa8LgauA3ZKejWl/RfgHmCtpBuAvcDVABGxS9Ja4A1KO8RuiYhPUrmbgB8AJwEb0gNKAesxSXsojUwWpbq6Jd0NbE/57oqI7nS8FFgjaSXwSqrDzMwaxBc2Ws202u3GzZqV7+VlDddqtxs3a3X+xkbLXFG/vtTMRsYjFMtcHq/gNbPac0CxzOXxCl4zqz1PeVlN5O0KXjOrPe/yMjOzAXmXVwvL0xfumFnrcEBpQt6ua2aN4DWUJuLtumbWSB6hNBFv1zUbnKeEa8cBpYl4u67Z4DwlXDue8moy3q5r1j9PCdeetw2bWUvoOnSElc+9yU92/YojHx9l7OhRzD/vi9zx9S97FD8Ibxs2MyvjKeHa85SXmbUMTwnXlqe8zMxsQJ7yMjOzunJAMTOzTDigmJlZJhxQzMwsEw4oZmaWCQcUMzPLhAOKmZllwgHFzMwy4YBiZmaZcEAxM7NMOKCYmVkmHFDMzCwTDihmZpYJBxQzM8uEA4qZmWXCAcXMzDLhgGJmZplwQDEzs0w4oJiZWSYGDSiSHpHUJen1srQJkjZJ6kzP48teWy5pj6TdkuaXpc+WtDO9tkqSUvoYSU+l9K2SZpaVWZzO0SlpcVn6rJS3M5U9ceRdYWZmI1HNCOUHwIKKtGXA5og4G9icfkbSucAi4LxU5ruSTkhlHgCWAGenR1+dNwAHI+JLwH3AvamuCcCdwIXAHODOssB1L3BfOv/BVIeZmTXQoAElIn4KdFckLwRWp+PVwJVl6Wsioici3gL2AHMkTQFOiYgtERHAoxVl+up6GrgsjV7mA5siojsiDgKbgAXptUtT3srzm5lZgwx3DeWMiNgPkJ4np/RpwDtl+faltGnpuDL9mDIR0Qt8CEwcoK6JwAcpb2VdnyNpiaQOSR0HDhwY4j/TzKzYug4d4VsPbqHr8JGanyvrRXn1kxYDpA+nzEB1ff6FiIcioj0i2idNmnS8bGZmTWnV5k62v93Nquc7a36utmGWe0/SlIjYn6azulL6PuDMsnzTgXdT+vR+0svL7JPUBpxKaYptH3BJRZmXgPeB0yS1pVFKeV1mZgacs2IDPb1HP/358a17eXzrXsa0jWL3yq/V5JzDHaGsB/p2XS0GnilLX5R2bs2itPi+LU2LHZZ0UVoDub6iTF9dVwEvpHWWjcA8SePTYvw8YGN67cWUt/L8ZmYGvHz7XK44fypjR5fe5seOHsXC86fy8tK5NTvnoCMUSU9SGimcLmkfpZ1X9wBrJd0A7AWuBoiIXZLWAm8AvcAtEfFJquomSjvGTgI2pAfAw8BjkvZQGpksSnV1S7ob2J7y3RURfZsDlgJrJK0EXkl1mJlZMvmUsYwb00ZP71HGtI2ip/co48a0MXnc2JqdU6UP/K2hvb09Ojo6Gt0MM7O6uPGxDiaNG8s1c2bwxLa9HDh8hAevax9yPZJ2RMSgBR1QzMxsQNUGFN96xczMMuGAYmZmmXBAMTOzTDigmJlZJhxQzMwsEw4oZmaWiZbaNizpAPBP/bx0OqVbuhRFkdpbpLZCsdpbpLZCsdpbpLZC7dt7VkQMejPElgooxyOpo5o91nlRpPYWqa1QrPYWqa1QrPYWqa2Qn/Z6ysvMzDLhgGJmZplwQCl5qNENGKIitbdIbYVitbdIbYVitbdIbYWctNdrKGZmlgmPUMzMLBNNG1AkPSKpS9LrZWn/StIWSTsl/W9Jp6T00ZJWp/Q3JS0vK/OSpN2SXk2PyQ1u64mSvp/SX5N0SVmZ2Sl9j6RV6cvMMpdhe+vRt2dKejH9v+6SdGtKnyBpk6TO9Dy+rMzy1Ie7Jc0vS69p/2bc1tz1raSJKf9Hku6vqCtXfTtIW/PYt5dL2pH6cIekS8vqqsv7AgAR0ZQP4N8Avwu8Xpa2Hfi36fiPgbvT8TXAmnT8W8DbwMz080tAe47aegvw/XQ8GdgBjEo/bwN+DxClLzD7Ws7bW4++nQL8bjoeB/wjcC7w58CylL4MuDcdnwu8BowBZgG/BE6oR/9m3NY89u3JwO8D3wbur6grb307UFvz2LcXAFPT8VeAf65X35Y/mnaEEhE/pfQNkOXOAX6ajjcBf9iXHThZpe+0Pwn4DXCoHu2EIbf1XGBzKtcFfAC0S5oCnBIRW6L0W/QocGVe21uLdvUnIvZHxD+k48PAm8A0YCGwOmVbzWd9tZDSh4ueiHgL2APMqUf/ZtXWLNuUZXsj4tcR8XfAkfJ68ti3x2trvQyjva9ExLspfRcwVqWvYq/b+wI08ZTXcbwOXJGOrwbOTMdPA78G9lP6SuP/GZ993TDA99PQ9r/WdLhYXVtfAxZKapM0C5idXpsG7Csrvy+l1ctQ29unbn0raSalT3JbgTMiYj+U/ngpjZ6g1GfvlBXr68e69u8I29onb317PHns28HkuW//EHglInqoc9+2WkD5Y+AWSTsoDSN/k9LnAJ8AUylNHfyppH+RXrs2Ir4K/Ov0uK7BbX2E0i9FB/CXwP8BeikNZyvVcwvfUNsLdexbSV8A/gb4k4gYaPR5vH6sW/9m0FbIZ98et4p+0hrdtwPJbd9KOg+4F7ixL6mfbDV7X2ipgBIRv4iIeRExG3iS0pwzlNZQfhwRH6dpmb8nTctExD+n58PAE9RpSuF4bY2I3oj4TxFxfkQsBE4DOim9aU8vq2I68G5lvTlqb936VtJoSn+UP4yIH6Xk99J0QN+US1dK38exI6i+fqxL/2bU1rz27fHksW+PK699K2k6sA64PiL63tvq+r7QUgGlbzeGpFHACuB76aW9wKUqORm4CPhFmqY5PZUZDXyD0tROw9oq6bdSG5F0OdAbEW+k4e9hSRelIfj1wDP1aOtw2luvvk198TDwZkT8RdlL64HF6Xgxn/XVemBRmn+eBZwNbKtH/2bV1hz3bb9y2rfHqyeXfSvpNOBZYHlE/H1f5rq/L2S9yp+XB6VPyfuBjylF6RuAWyntlvhH4B4+u7DzC8BfU1rMegP4z/HZTo8dwM/Ta/+LtIumgW2dCeymtEj3PKW7gPbV007pl/uXwP19ZfLY3jr27e9TGuL/HHg1Pf49MJHSZoHO9DyhrMwdqQ93U7Yjptb9m1Vbc963b1Pa0PFR+t05N8d9+7m25rVvKX2I+3VZ3leByfXo2/KHr5Q3M7NMtNSUl5mZ1Y4DipmZZcIBxczMMuGAYmZmmXBAMTOzTDigmJlZJhxQzMwsEw4oZmaWif8P5AS727RchlQAAAAASUVORK5CYII=\n", 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5115251\n", + "1990 5235827\n", + "1989 5466192\n", + "dtype: int64" + ] + }, + "execution_count": 14, + "metadata": {}, + "output_type": "execute_result" + } + ], "source": [ "yearly_incidence.sort_values()" ] @@ -331,9 +2452,32 @@ }, { "cell_type": "code", - "execution_count": null, + "execution_count": 15, "metadata": {}, - "outputs": [], + "outputs": [ + { + "data": { + "text/plain": [ + "" + ] + }, + "execution_count": 15, + "metadata": {}, + "output_type": "execute_result" + }, + { + "data": { + "image/png": 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\n", + "text/plain": [ + "
" + ] + }, + "metadata": { + "needs_background": "light" + }, + "output_type": "display_data" + } + ], "source": [ "yearly_incidence.hist(xrot=20)" ] @@ -341,9 +2485,7 @@ { "cell_type": "code", "execution_count": null, - "metadata": { - "collapsed": true - }, + "metadata": {}, "outputs": [], "source": [] } @@ -364,7 +2506,7 @@ "name": "python", "nbconvert_exporter": "python", "pygments_lexer": "ipython3", - "version": "3.6.1" + "version": "3.6.4" } }, "nbformat": 4, diff --git a/module3/exo1/incidence-PAY-3.csv b/module3/exo1/incidence-PAY-3.csv new file mode 100644 index 0000000000000000000000000000000000000000..3cd4c66990a1dda138a77f22374c3f3c2e31f81c --- /dev/null +++ b/module3/exo1/incidence-PAY-3.csv @@ -0,0 +1,1954 @@ +# @source="réseau Sentinelles, INSERM, Sorbonne Université, http://www.sentiweb.fr", @meta={"period":[198444,202212],"geo":["PAY","1"],"geo_ref":"insee","indicator":"3","type":"all","conf_int":true,"compact":false}, @date=2022-04-03T16:36:02+02:00 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