diff --git a/module3/exo1/analyse-syndrome-grippal.ipynb b/module3/exo1/analyse-syndrome-grippal.ipynb index 59d72b5b58a3ae26346460dd39e62a39c55243d7..b6b965b3982777a8b0b52e6514be68096e112a2b 100644 --- a/module3/exo1/analyse-syndrome-grippal.ipynb +++ b/module3/exo1/analyse-syndrome-grippal.ipynb @@ -9,14 +9,15 @@ }, { "cell_type": "code", - "execution_count": null, + "execution_count": 22, "metadata": {}, "outputs": [], "source": [ "%matplotlib inline\n", "import matplotlib.pyplot as plt\n", "import pandas as pd\n", - "import isoweek" + "import isoweek\n", + "import requests" ] }, { @@ -28,13 +29,12 @@ }, { "cell_type": "code", - "execution_count": null, - "metadata": { - "collapsed": true - }, + "execution_count": 25, + "metadata": {}, "outputs": [], "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_filename = 'incidence-PAY-3.csv'" ] }, { @@ -61,11 +61,988 @@ }, { "cell_type": "code", - "execution_count": null, - "metadata": {}, - "outputs": [], + "execution_count": 34, + "metadata": { + "scrolled": true + }, + "outputs": [ + { + "data": { + "text/html": [ + "
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weekindicatorincinc_lowinc_upinc100inc100_lowinc100_upgeo_inseegeo_name
020214532578620362.031210.03931.047.0FRFrance
120214431940615338.023474.02923.035.0FRFrance
220214332698721881.032093.04133.049.0FRFrance
320214232834323382.033304.04335.051.0FRFrance
420214132504320586.029500.03831.045.0FRFrance
520214032628621842.030730.04033.047.0FRFrance
620213932215518014.026296.03428.040.0FRFrance
720213831561412310.018918.02419.029.0FRFrance
820213731367310404.016942.02116.026.0FRFrance
92021363102897505.013073.01612.020.0FRFrance
102021353126099282.015936.01914.024.0FRFrance
112021343130159485.016545.02015.025.0FRFrance
122021333103927042.013742.01611.021.0FRFrance
1320213231558611009.020163.02417.031.0FRFrance
1420213131885513664.024046.02921.037.0FRFrance
152021303139919695.018287.02114.028.0FRFrance
162021293136269618.017634.02115.027.0FRFrance
17202128386365430.011842.0138.018.0FRFrance
182021273106936838.014548.01610.022.0FRFrance
19202126370864109.010063.0116.016.0FRFrance
20202125379425540.010344.0128.016.0FRFrance
21202124348553011.06699.074.010.0FRFrance
22202123367104455.08965.0107.013.0FRFrance
23202122378795495.010263.0128.016.0FRFrance
24202121378275403.010251.0128.016.0FRFrance
252021203102787540.013016.01612.020.0FRFrance
26202119395396860.012218.01410.018.0FRFrance
272021183121359165.015105.01814.022.0FRFrance
282021173120588891.015225.01813.023.0FRFrance
2920211631650512735.020275.02519.031.0FRFrance
.................................
190319852132609619621.032571.04735.059.0FRFrance
190419852032789620885.034907.05138.064.0FRFrance
190519851934315432821.053487.07859.097.0FRFrance
190619851834055529935.051175.07455.093.0FRFrance
190719851733405324366.043740.06244.080.0FRFrance
190819851635036236451.064273.09166.0116.0FRFrance
190919851536388145538.082224.011683.0149.0FRFrance
19101985143134545114400.0154690.0244207.0281.0FRFrance
19111985133197206176080.0218332.0357319.0395.0FRFrance
19121985123245240223304.0267176.0445405.0485.0FRFrance
19131985113276205252399.0300011.0501458.0544.0FRFrance
19141985103353231326279.0380183.0640591.0689.0FRFrance
19151985093369895341109.0398681.0670618.0722.0FRFrance
19161985083389886359529.0420243.0707652.0762.0FRFrance
19171985073471852432599.0511105.0855784.0926.0FRFrance
19181985063565825518011.0613639.01026939.01113.0FRFrance
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19211985033213901174689.0253113.0388317.0459.0FRFrance
192219850239758680949.0114223.0177147.0207.0FRFrance
192319850138548965918.0105060.0155120.0190.0FRFrance
192419845238483060602.0109058.0154110.0198.0FRFrance
1925198451310172680242.0123210.0185146.0224.0FRFrance
19261984503123680101401.0145959.0225184.0266.0FRFrance
1927198449310107381684.0120462.0184149.0219.0FRFrance
192819844837862060634.096606.0143110.0176.0FRFrance
192919844737202954274.089784.013199.0163.0FRFrance
193019844638733067686.0106974.0159123.0195.0FRFrance
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1933 rows × 10 columns

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207.0 \n", + "1911 198513 3 197206 176080.0 218332.0 357 319.0 \n", + "1912 198512 3 245240 223304.0 267176.0 445 405.0 \n", + "1913 198511 3 276205 252399.0 300011.0 501 458.0 \n", + "1914 198510 3 353231 326279.0 380183.0 640 591.0 \n", + "1915 198509 3 369895 341109.0 398681.0 670 618.0 \n", + "1916 198508 3 389886 359529.0 420243.0 707 652.0 \n", + "1917 198507 3 471852 432599.0 511105.0 855 784.0 \n", + "1918 198506 3 565825 518011.0 613639.0 1026 939.0 \n", + "1919 198505 3 637302 592795.0 681809.0 1155 1074.0 \n", + "1920 198504 3 424937 390794.0 459080.0 770 708.0 \n", + "1921 198503 3 213901 174689.0 253113.0 388 317.0 \n", + "1922 198502 3 97586 80949.0 114223.0 177 147.0 \n", + "1923 198501 3 85489 65918.0 105060.0 155 120.0 \n", + "1924 198452 3 84830 60602.0 109058.0 154 110.0 \n", + "1925 198451 3 101726 80242.0 123210.0 185 146.0 \n", + "1926 198450 3 123680 101401.0 145959.0 225 184.0 \n", + "1927 198449 3 101073 81684.0 120462.0 184 149.0 \n", + "1928 198448 3 78620 60634.0 96606.0 143 110.0 \n", + "1929 198447 3 72029 54274.0 89784.0 131 99.0 \n", + "1930 198446 3 87330 67686.0 106974.0 159 123.0 \n", + "1931 198445 3 135223 101414.0 169032.0 246 184.0 \n", + "1932 198444 3 68422 20056.0 116788.0 125 37.0 \n", + "\n", + " inc100_up geo_insee geo_name \n", + "0 47.0 FR France \n", + "1 35.0 FR France \n", + "2 49.0 FR France \n", + "3 51.0 FR France \n", + "4 45.0 FR France \n", + "5 47.0 FR France \n", + "6 40.0 FR France \n", + "7 29.0 FR France \n", + "8 26.0 FR France \n", + "9 20.0 FR France \n", + "10 24.0 FR France \n", + "11 25.0 FR France \n", + "12 21.0 FR France \n", + "13 31.0 FR France \n", + "14 37.0 FR France \n", + "15 28.0 FR France \n", + "16 27.0 FR France \n", + "17 18.0 FR France \n", + "18 22.0 FR France \n", + "19 16.0 FR France \n", + "20 16.0 FR France \n", + "21 10.0 FR France \n", + "22 13.0 FR France \n", + "23 16.0 FR France \n", + "24 16.0 FR France \n", + "25 20.0 FR France \n", + "26 18.0 FR France \n", + "27 22.0 FR France \n", + "28 23.0 FR France \n", + "29 31.0 FR France \n", + "... ... ... ... \n", + "1903 59.0 FR France \n", + "1904 64.0 FR France \n", + "1905 97.0 FR France \n", + "1906 93.0 FR France \n", + "1907 80.0 FR France \n", + "1908 116.0 FR France \n", + "1909 149.0 FR France \n", + "1910 281.0 FR France \n", + "1911 395.0 FR France \n", + "1912 485.0 FR France \n", + "1913 544.0 FR France \n", + "1914 689.0 FR France \n", + "1915 722.0 FR France \n", + "1916 762.0 FR France \n", + "1917 926.0 FR France \n", + "1918 1113.0 FR France \n", + "1919 1236.0 FR France \n", + "1920 832.0 FR France \n", + "1921 459.0 FR France \n", + "1922 207.0 FR France \n", + "1923 190.0 FR France \n", + "1924 198.0 FR France \n", + "1925 224.0 FR France \n", + "1926 266.0 FR France \n", + "1927 219.0 FR France \n", + "1928 176.0 FR France \n", + "1929 163.0 FR France \n", + "1930 195.0 FR France \n", + "1931 308.0 FR France \n", + "1932 213.0 FR France \n", + "\n", + "[1933 rows x 10 columns]" + ] + }, + "execution_count": 34, + "metadata": {}, + "output_type": "execute_result" + } + ], "source": [ - "raw_data = pd.read_csv(data_url, skiprows=1)\n", + "try:\n", + " raw_data = pd.read_csv(data_filename, skiprows=1)\n", + "except FileNotFoundError:\n", + " req = requests.get(data_url)\n", + " url_content = req.content\n", + " csv_file = open(data_filename, 'wb')\n", + " csv_file.write(url_content)\n", + " \n", + "raw_data = pd.read_csv(data_filename, skiprows=1)\n", "raw_data" ] }, @@ -78,9 +1055,73 @@ }, { "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
169619891930NaNNaN0NaNNaNFRFrance
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" + ], + "text/plain": [ + " week indicator inc inc_low inc_up inc100 inc100_low inc100_up \\\n", + "1696 198919 3 0 NaN NaN 0 NaN NaN \n", + "\n", + " geo_insee geo_name \n", + "1696 FR France " + ] + }, + "execution_count": 4, + "metadata": {}, + "output_type": "execute_result" + } + ], "source": [ "raw_data[raw_data.isnull().any(axis=1)]" ] @@ -94,9 +1135,978 @@ }, { "cell_type": "code", - "execution_count": null, - "metadata": {}, - "outputs": [], + "execution_count": 5, + "metadata": { + "scrolled": true + }, + "outputs": [ + { + "data": { + "text/html": [ + "
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weekindicatorincinc_lowinc_upinc100inc100_lowinc100_upgeo_inseegeo_name
020214532578620362.031210.03931.047.0FRFrance
120214431940615338.023474.02923.035.0FRFrance
220214332698721881.032093.04133.049.0FRFrance
320214232834323382.033304.04335.051.0FRFrance
420214132504320586.029500.03831.045.0FRFrance
520214032628621842.030730.04033.047.0FRFrance
620213932215518014.026296.03428.040.0FRFrance
720213831561412310.018918.02419.029.0FRFrance
820213731367310404.016942.02116.026.0FRFrance
92021363102897505.013073.01612.020.0FRFrance
102021353126099282.015936.01914.024.0FRFrance
112021343130159485.016545.02015.025.0FRFrance
122021333103927042.013742.01611.021.0FRFrance
1320213231558611009.020163.02417.031.0FRFrance
1420213131885513664.024046.02921.037.0FRFrance
152021303139919695.018287.02114.028.0FRFrance
162021293136269618.017634.02115.027.0FRFrance
17202128386365430.011842.0138.018.0FRFrance
182021273106936838.014548.01610.022.0FRFrance
19202126370864109.010063.0116.016.0FRFrance
20202125379425540.010344.0128.016.0FRFrance
21202124348553011.06699.074.010.0FRFrance
22202123367104455.08965.0107.013.0FRFrance
23202122378795495.010263.0128.016.0FRFrance
24202121378275403.010251.0128.016.0FRFrance
252021203102787540.013016.01612.020.0FRFrance
26202119395396860.012218.01410.018.0FRFrance
272021183121359165.015105.01814.022.0FRFrance
282021173120588891.015225.01813.023.0FRFrance
2920211631650512735.020275.02519.031.0FRFrance
.................................
190319852132609619621.032571.04735.059.0FRFrance
190419852032789620885.034907.05138.064.0FRFrance
190519851934315432821.053487.07859.097.0FRFrance
190619851834055529935.051175.07455.093.0FRFrance
190719851733405324366.043740.06244.080.0FRFrance
190819851635036236451.064273.09166.0116.0FRFrance
190919851536388145538.082224.011683.0149.0FRFrance
19101985143134545114400.0154690.0244207.0281.0FRFrance
19111985133197206176080.0218332.0357319.0395.0FRFrance
19121985123245240223304.0267176.0445405.0485.0FRFrance
19131985113276205252399.0300011.0501458.0544.0FRFrance
19141985103353231326279.0380183.0640591.0689.0FRFrance
19151985093369895341109.0398681.0670618.0722.0FRFrance
19161985083389886359529.0420243.0707652.0762.0FRFrance
19171985073471852432599.0511105.0855784.0926.0FRFrance
19181985063565825518011.0613639.01026939.01113.0FRFrance
19191985053637302592795.0681809.011551074.01236.0FRFrance
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1925198451310172680242.0123210.0185146.0224.0FRFrance
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192819844837862060634.096606.0143110.0176.0FRFrance
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1932 rows × 10 columns

\n", + "
" + ], + "text/plain": [ + " week indicator inc inc_low inc_up inc100 inc100_low \\\n", + "0 202145 3 25786 20362.0 31210.0 39 31.0 \n", + "1 202144 3 19406 15338.0 23474.0 29 23.0 \n", + "2 202143 3 26987 21881.0 32093.0 41 33.0 \n", + "3 202142 3 28343 23382.0 33304.0 43 35.0 \n", + "4 202141 3 25043 20586.0 29500.0 38 31.0 \n", + "5 202140 3 26286 21842.0 30730.0 40 33.0 \n", + "6 202139 3 22155 18014.0 26296.0 34 28.0 \n", + "7 202138 3 15614 12310.0 18918.0 24 19.0 \n", + "8 202137 3 13673 10404.0 16942.0 21 16.0 \n", + "9 202136 3 10289 7505.0 13073.0 16 12.0 \n", + "10 202135 3 12609 9282.0 15936.0 19 14.0 \n", + "11 202134 3 13015 9485.0 16545.0 20 15.0 \n", + "12 202133 3 10392 7042.0 13742.0 16 11.0 \n", + "13 202132 3 15586 11009.0 20163.0 24 17.0 \n", + "14 202131 3 18855 13664.0 24046.0 29 21.0 \n", + "15 202130 3 13991 9695.0 18287.0 21 14.0 \n", + "16 202129 3 13626 9618.0 17634.0 21 15.0 \n", + "17 202128 3 8636 5430.0 11842.0 13 8.0 \n", + "18 202127 3 10693 6838.0 14548.0 16 10.0 \n", + "19 202126 3 7086 4109.0 10063.0 11 6.0 \n", + "20 202125 3 7942 5540.0 10344.0 12 8.0 \n", + "21 202124 3 4855 3011.0 6699.0 7 4.0 \n", + "22 202123 3 6710 4455.0 8965.0 10 7.0 \n", + "23 202122 3 7879 5495.0 10263.0 12 8.0 \n", + "24 202121 3 7827 5403.0 10251.0 12 8.0 \n", + "25 202120 3 10278 7540.0 13016.0 16 12.0 \n", + "26 202119 3 9539 6860.0 12218.0 14 10.0 \n", + "27 202118 3 12135 9165.0 15105.0 18 14.0 \n", + "28 202117 3 12058 8891.0 15225.0 18 13.0 \n", + "29 202116 3 16505 12735.0 20275.0 25 19.0 \n", + "... ... ... ... ... ... ... ... \n", + "1903 198521 3 26096 19621.0 32571.0 47 35.0 \n", + "1904 198520 3 27896 20885.0 34907.0 51 38.0 \n", + "1905 198519 3 43154 32821.0 53487.0 78 59.0 \n", + "1906 198518 3 40555 29935.0 51175.0 74 55.0 \n", + "1907 198517 3 34053 24366.0 43740.0 62 44.0 \n", + "1908 198516 3 50362 36451.0 64273.0 91 66.0 \n", + "1909 198515 3 63881 45538.0 82224.0 116 83.0 \n", + "1910 198514 3 134545 114400.0 154690.0 244 207.0 \n", + "1911 198513 3 197206 176080.0 218332.0 357 319.0 \n", + "1912 198512 3 245240 223304.0 267176.0 445 405.0 \n", + "1913 198511 3 276205 252399.0 300011.0 501 458.0 \n", + "1914 198510 3 353231 326279.0 380183.0 640 591.0 \n", + "1915 198509 3 369895 341109.0 398681.0 670 618.0 \n", + "1916 198508 3 389886 359529.0 420243.0 707 652.0 \n", + "1917 198507 3 471852 432599.0 511105.0 855 784.0 \n", + "1918 198506 3 565825 518011.0 613639.0 1026 939.0 \n", + "1919 198505 3 637302 592795.0 681809.0 1155 1074.0 \n", + "1920 198504 3 424937 390794.0 459080.0 770 708.0 \n", + "1921 198503 3 213901 174689.0 253113.0 388 317.0 \n", + "1922 198502 3 97586 80949.0 114223.0 177 147.0 \n", + "1923 198501 3 85489 65918.0 105060.0 155 120.0 \n", + "1924 198452 3 84830 60602.0 109058.0 154 110.0 \n", + "1925 198451 3 101726 80242.0 123210.0 185 146.0 \n", + "1926 198450 3 123680 101401.0 145959.0 225 184.0 \n", + "1927 198449 3 101073 81684.0 120462.0 184 149.0 \n", + "1928 198448 3 78620 60634.0 96606.0 143 110.0 \n", + "1929 198447 3 72029 54274.0 89784.0 131 99.0 \n", + "1930 198446 3 87330 67686.0 106974.0 159 123.0 \n", + "1931 198445 3 135223 101414.0 169032.0 246 184.0 \n", + "1932 198444 3 68422 20056.0 116788.0 125 37.0 \n", + "\n", + " inc100_up geo_insee geo_name \n", + "0 47.0 FR France \n", + "1 35.0 FR France \n", + "2 49.0 FR France \n", + "3 51.0 FR France \n", + "4 45.0 FR France \n", + "5 47.0 FR France \n", + "6 40.0 FR France \n", + "7 29.0 FR France \n", + "8 26.0 FR France \n", + "9 20.0 FR France \n", + "10 24.0 FR France \n", + "11 25.0 FR France \n", + "12 21.0 FR France \n", + "13 31.0 FR France \n", + "14 37.0 FR France \n", + "15 28.0 FR France \n", + "16 27.0 FR France \n", + "17 18.0 FR France \n", + "18 22.0 FR France \n", + "19 16.0 FR France \n", + "20 16.0 FR France \n", + "21 10.0 FR France \n", + "22 13.0 FR France \n", + "23 16.0 FR France \n", + "24 16.0 FR France \n", + "25 20.0 FR France \n", + "26 18.0 FR France \n", + "27 22.0 FR France \n", + "28 23.0 FR France \n", + "29 31.0 FR France \n", + "... ... ... ... \n", + "1903 59.0 FR France \n", + "1904 64.0 FR France \n", + "1905 97.0 FR France \n", + "1906 93.0 FR France \n", + "1907 80.0 FR France \n", + "1908 116.0 FR France \n", + "1909 149.0 FR France \n", + "1910 281.0 FR France \n", + "1911 395.0 FR France \n", + "1912 485.0 FR France \n", + "1913 544.0 FR France \n", + "1914 689.0 FR France \n", + "1915 722.0 FR France \n", + "1916 762.0 FR France \n", + "1917 926.0 FR France \n", + "1918 1113.0 FR France \n", + "1919 1236.0 FR France \n", + "1920 832.0 FR France \n", + "1921 459.0 FR France \n", + "1922 207.0 FR France \n", + "1923 190.0 FR France \n", + "1924 198.0 FR France \n", + "1925 224.0 FR France \n", + "1926 266.0 FR France \n", + "1927 219.0 FR France \n", + "1928 176.0 FR France \n", + "1929 163.0 FR France \n", + "1930 195.0 FR France \n", + "1931 308.0 FR France \n", + "1932 213.0 FR France \n", + "\n", + "[1932 rows x 10 columns]" + ] + }, + "execution_count": 5, + "metadata": {}, + "output_type": "execute_result" + } + ], "source": [ "data = raw_data.dropna().copy()\n", "data" @@ -122,7 +2132,7 @@ }, { "cell_type": "code", - "execution_count": null, + "execution_count": 6, "metadata": {}, "outputs": [], "source": [ @@ -152,10 +2162,8 @@ }, { "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 +2187,17 @@ }, { "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 +2215,32 @@ }, { "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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lbpS0XdIrkhaW0udKeiHPrcqtgMntgh/M9I2SZpbKLJPUna9lpfRZmbc7yx7bmEtiA9WoZZT9fQofjZ8OR3vPzNpLPT2Ug8D8iHhP0jjgbyVVtu69PSL+tJxZ0myKLXzPBqYBT0j6RG4DvBpYDjwLPA4sotgG+EpgX0ScIWkpcBvwJUmTgJuBDiCALZIei4h9mef2iFgr6btZx+rBXwobrHIgWHnxpwZcvt5P4aPx0+Fo7ZlZe+q3hxKF9/Lbcfmq9QCwxcDaiDgYEa8C24F5kqYCEyJiQxQPELsHWFIqsyaPHwYuyt7LQqAzInoyiHQCi/Lc/MxLlq3UZcPkrJvWMfOGn3Dfxp1EFIFg5g0/4ayb1vVfuMSfwmsbjT0za091zaFIOgbYApwB/O+I2CjpM8C1kq4AuoCv5h/96RQ9kIpdmfZ+Hlenk19fA4iIXknvAJPL6VVlJgNvR0RvH3XZMHnm+guPuEf7QPhTeG2jsWdm7amuVV4RcSgi5gAzKHob51AML30cmAPsBr6V2dVXFTXSB1OmVl2HkbRcUpekrr179/aVxQapkYHAn8JHHj+iZPQZ0CqviHhb0tPAovLciaTvAz/Ob3cBp5aKzQDeyPQZfaSXy+ySNBY4EejJ9E9XlXkaeAs4SdLY7KWU66pu853AnVA8vn4gP6/1r1H7cPhT+MhztHNr1n763Q9F0hTg/QwmxwM/pZgQ3xIRuzPPHwLnRcRSSWcD9wPzKCblfwacGRGHJG0G/iuwkWJS/n9FxOOSrgE+FRFfyUn5346I381J+S3Ab2Zzfg7MjYgeSX8F/LA0Kf+LiPhOrZ/F+6GYDT3vcT/y1LsfSj09lKnAmpxHGQM8FBE/lnSvpDkUQ007gC8DRMQ2SQ8BLwG9wDW5wgvgKuBu4HiK1V2V2du7gHslbafomSzNunok3Qpszny3RERPHq8A1kpaCWzNOsysyRo1t2btp9+AEhG/AM7tI/3yGmX+BPiTPtK7gF8Zz4iIA8AXj1DXD4Af9JH+/yh6QWbWQrzIYvTynfJm1nDe43508p7yZmZWk/eUNzOzYeWAYmZmDeGAYmZmDeGAYmZmDeGAYmZmDeGAYmZmDeGAYmZmDeGAYmZmDeGAYmZmDeGAYjaEvCeIjSYOKGZDqLwniNlI54dDmg2B6j1B7tu4k/s27vSeIDaiuYdiNgSeuf5CvjBnGuPHFf/Fxo8bw+I503hmxYVNbpnZ0HFAMRsC3hPERiMHFBtRWmkSvLInyCNXX8Bl553O3vcONrtJZkOq34AiabykTZKel7RN0h9n+iRJnZK68+vEUpkbJW2X9IqkhaX0uZJeyHOrJCnTj5P0YKZvlDSzVGZZvke3pGWl9FmZtzvLHtuYS2LtrJUmwb93eQcrl5zD7GkTWLnkHL53eb/bSZi1tX432Mo/+h+JiPckjQP+FrgO+G2gJyK+IekGYGJErJA0G3iAYnveacATwCci4pCkTVn2WeBxYFVErJN0NfAbEfEVSUuBiyPiS5ImAV1AB8Xe9VuAuRGxL/et/1FErJX0XeD5iFhd62fxBlsjV/UkeIUnwc2OXsM22IrCe/ntuHwFsBhYk+lrgCV5vBhYGxEHI+JVYDswT9JUYEJEbIgiit1TVaZS18PARRnIFgKdEdETEfuATmBRnpufeavf30YhT4IPr1YaWrTWUdcciqRjJD0H7KH4A78ROCUidgPk15Mz+3TgtVLxXZk2PY+r0w8rExG9wDvA5Bp1TQbezrzVdVW3fbmkLklde/furefHtTbkSfDh1UpDi9Y66roPJSIOAXMknQQ8IumcGtnVVxU10gdTplZdhydG3AncCcWQV195bGSoTIJfOu807t+0k73+9Nxwvr/GahnQjY0R8bakp4FFwJuSpkbE7hzO2pPZdgGnlorNAN7I9Bl9pJfL7JI0FjgR6Mn0T1eVeRp4CzhJ0tjspZTrslGqPOm9ckmtzzw2WM9cfyErH3+Zn277Jw68/wHjx41h4dm/ztc+98lmN81aQD2rvKZkzwRJxwP/Gfgl8BhQWXW1DHg0jx8DlubKrVnAmcCmHBbbL+n8nAO5oqpMpa5LgCdznmU9sEDSxFxFtgBYn+eeyrzV729mQ8RDi1ZLPT2UqcAaScdQBKCHIuLHkjYAD0m6EtgJfBEgIrblCqyXgF7gmhwyA7gKuBs4HliXL4C7gHslbafomSzNunok3Qpszny3RERPHq8A1kpaCWzNOsxsiHlo0Y6k32XDI8lQLhve8+4Brn1gK3dceq4/rZk1UDv+32rHNtfSsGXDVh+vejEbGu34f6sd29wI7qEcJd9QZzY02vH/Vju2uR7uoQwT31BnNjTa8f9WO7a5kRxQjtJAVr347mJrB63ye9qOK8rasc2N5IDSAPU+VXa0jqtae2ml39N2fGJzO7a5UTyHMgxG6riqjSz+PbUj8RxKCxnt46rWHvx72npaZfixXg4ow6Cdx1Xb7RfaBq+df09HqlYafqzHgJ7lZYPXrncXl3+hV178qWY3x4ZYu/6ejjTt+hBOz6FYnzyebtY8e949cMSHcDajx+g5FDsqHk83a552HX70kJf1qV1/oc1GinYcfnRAsSNqx19os5GiHff38RzKKDbSnohqZkPDcyjWr3Zbkmhmrc1DXqNQuy5JbDXu4Zkdrp4tgE+V9JSklyVtk3Rdpn9d0uuSnsvXZ0tlbpS0XdIrkhaW0udKeiHPrcqtgMntgh/M9I2SZpbKLJPUna9lpfRZmbc7yx7bmEsy8nkFV2O4h2d2uHp6KL3AVyPi55JOALZI6sxzt0fEn5YzS5pNsYXv2cA04AlJn8htgFcDy4FngceBRRTbAF8J7IuIMyQtBW4DviRpEnAz0AFEvvdjEbEv89weEWslfTfrWD34SzF6eAXX0XEPz6xv/fZQImJ3RPw8j/cDLwPTaxRZDKyNiIMR8SqwHZgnaSowISI2RLES4B5gSanMmjx+GLgoey8Lgc6I6Mkg0gksynPzMy9ZtlKX1WE0PxH1aLmHZ9a3Ac2h5FDUucBG4ALgWklXAF0UvZh9FMHm2VKxXZn2fh5Xp5NfXwOIiF5J7wCTy+lVZSYDb0dEbx91WR3acUliq3APz6xvda/ykvRR4IfAH0TEuxTDSx8H5gC7gW9VsvZRPGqkD6ZMrbqq271cUpekrr179/aVxWzA3MMz+1V19VAkjaMIJn8ZET8CiIg3S+e/D/w4v90FnFoqPgN4I9Nn9JFeLrNL0ljgRKAn0z9dVeZp4C3gJEljs5dSruswEXEncCcU96HU8/Oa9cc9PLNfVc8qLwF3AS9HxLdL6VNL2S4GXszjx4CluXJrFnAmsCkidgP7JZ2fdV4BPFoqU1nBdQnwZM6zrAcWSJooaSKwAFif557KvGTZSl1mZtYE9fRQLgAuB16Q9Fym/RHwXyTNoRhq2gF8GSAitkl6CHiJYoXYNbnCC+Aq4G7geIrVXesy/S7gXknbKXomS7OuHkm3Apsz3y0R0ZPHK4C1klYCW7MOMzNrEj96xczMavKjV8zMbFg5oJiZNcFI3F7bAcVsFBmJf8Ta1Uh8dI8fDmk2ipT/iK28+FPNbs6oNJIf3eNJebNRoPqPWMVI+CPWbhq5X/xwPfHak/Jm9q/8/LHW0chH97TasJmHvMyabDg+Zfr5Y63laLfXbtVhMwcUsyYbrnmNo/0jZo1ztI/ueeb6C484bNZMDihmTTLcnzL9/LGRo1V7nJ5DMWsSz2s0zmhcDt2KT7x2D8WsSVr1U2Y7Go3LoVuxx+mAYtZEntc4Oq06OT1a+T4UM2tbjbynw47M96GY2YjnYcPW4iEvM2trHjZsHR7yMjMbwRpx46yHvMzMbFgfz1LPnvKnSnpK0suStkm6LtMnSeqU1J1fJ5bK3Chpu6RXJC0spc+V9EKeW5V7y5P7zz+Y6RslzSyVWZbv0S1pWSl9VubtzrLHNuaSmJm1v7NuWsfMG37CfRt3ElGsgJt5w08466Z1/RcepHp6KL3AVyPik8D5wDWSZgM3AD+LiDOBn+X35LmlwNnAIuA7ko7JulYDy4Ez87Uo068E9kXEGcDtwG1Z1yTgZuA8YB5wcylw3Qbcnu+/L+swMzOac+NsvwElInZHxM/zeD/wMjAdWAysyWxrgCV5vBhYGxEHI+JVYDswT9JUYEJEbIhi4uaeqjKVuh4GLsrey0KgMyJ6ImIf0AksynPzM2/1+5uZjXrNWAE3oFVeORR1LrAROCUidkMRdCSdnNmmA8+Wiu3KtPfzuDq9Uua1rKtX0jvA5HJ6VZnJwNsR0dtHXWZmxvCvgKs7oEj6KPBD4A8i4t2c/ugzax9pUSN9MGVq1XV4Y6TlFMNsnHbaaX1lMTMbkYb78Sx1rfKSNI4imPxlRPwok9/MYSzy655M3wWcWio+A3gj02f0kX5YGUljgROBnhp1vQWclHmr6zpMRNwZER0R0TFlypR6flwzMxuEelZ5CbgLeDkivl069RhQWXW1DHi0lL40V27Noph835TDY/slnZ91XlFVplLXJcCTOc+yHlggaWJOxi8A1ue5pzJv9fubmVkT1DPkdQFwOfCCpOcy7Y+AbwAPSboS2Al8ESAitkl6CHiJYoXYNRFxKMtdBdwNHA+syxcUAeteSdspeiZLs64eSbcCmzPfLRHRk8crgLWSVgJbsw4zM2sS3ylvZmY1+U55aymjcQMks9HGAcWGxXA+/sHMmsNPG7Yh5Q2QzEYP91BsSHnfdLPRwwHFhpQ3QDIbPTzkZUPOGyCZjQ5eNmxmZjV52bCZmQ0rBxQzM2sIB5QRyjcSmtlwc0AZoXwjoZkNN6/yGmF8I6GZNYt7KCOMbyQ0GzwPFR8dB5QRxjcSmg2eh4qPjoe8RiDfSGg2MB4qbgzf2Ghmo96edw+w8vGX+em2f+LA+x8wftwYFp7963ztc590754G3tgo6QeS9kh6sZT2dUmvS3ouX58tnbtR0nZJr0haWEqfK+mFPLcqtwEmtwp+MNM3SppZKrNMUne+lpXSZ2Xe7ix7bD0XxcysLx4qbox65lDuBhb1kX57RMzJ1+MAkmZTbN97dpb5jqRjMv9qYDnFHvNnluq8EtgXEWcAtwO3ZV2TgJuB84B5wM25rzyZ5/aIOBPYl3WYmQ1aZaj4kasv4LLzTmfveweb3aS20+8cSkT8TbnX0I/FwNqIOAi8mnvEz5O0A5gQERsAJN0DLKHYU34x8PUs/zBwR/ZeFgKdlT3kJXUCiyStBeYDl2aZNVl+dZ1tNDP7Fd+7/MMRnZVLzmliS9rX0azyulbSL3JIrNJzmA68VsqzK9Om53F1+mFlIqIXeAeYXKOuycDbmbe6LjMza5LBBpTVwMeBOcBu4FuZrj7yRo30wZSpVdevkLRcUpekrr179x4pm5mZHaVBBZSIeDMiDkXEB8D3KeY4oOgtnFrKOgN4I9Nn9JF+WBlJY4ETgZ4adb0FnJR5q+vqq613RkRHRHRMmTJloD+qmZnVaVABRdLU0rcXA5UVYI8BS3Pl1iyKyfdNEbEb2C/p/JwfuQJ4tFSmsoLrEuDJKNYyrwcWSJqYQ2oLgPV57qnMS5at1GVmZk3S76S8pAeATwMfk7SLYuXVpyXNoRhq2gF8GSAitkl6CHgJ6AWuiYhDWdVVFCvGjqeYjF+X6XcB9+YEfg/FKjEiokfSrcDmzHdLZYIeWAGslbQS2Jp1mJlZE/nGRjMzq6neGxtHVUCRtBf4xz5OfYxibqaduM1Dr93aC27zcGm3Nh9te0+PiH4noUdVQDkSSV31RN9W4jYPvXZrL7jNw6Xd2jxc7fXThs3MrCEcUMzMrCEcUAp3NrsBg+A2D712ay+4zcOl3do8LO31HIqZmTWEeyhmZtYQIzKgHGEPl38raUPuyfJ/JE3I9HGS1mT6y5JuLJV5Ovd1qez7cnKLtPlYSX+R6c9L+nSpTJ/7zrR4m4flOks6VdJT+e+8TdJ1mT5JUmfur9NZetjpgPf3afE2t+R1ljQ5878n6Y6qulryOvfT5iG/zoNo729J2pLXcouk+aW6GneNI2LEvYD/CPwm8GIpbTPwn/L494Fb8/hSikfuA/waxZ3/M/P7p4GOFmzzNcBf5PHJwBZgTH6ruEO0AAADpklEQVS/Cfh3FA/RXAd8pg3aPCzXGZgK/GYenwD8PTAb+CZwQ6bfANyWx7OB54HjgFnAPwDHDOd1bnCbW/U6fwT498BXgDuq6mrV61yrzUN+nQfR3nOBaXl8DvD6UFzjEdlDiYi/oXiMS9lZwN/kcSfwO5XswEdUPGzyeOBfgHeHo51lA2zzbOBnWW4P8DbQoeIZaxMiYkMUvymVfWdats1D1ba+RMTuiPh5Hu8HXqbY+mAxxb465NfKNfvX/X0i4lWgsr/PsF3nRrV5KNrWqDZHxD9HxN8CB8r1tPJ1PlKbh8sg2rs1IioP0d0GjFfxzMWGXuMRGVCO4EXgC3n8RT58kvHDwD9TPIZ/J/Cn8eEzwwD+Irut/2Moh4+O4Ehtfh5YLGmsiodwzs1ztfadGS4DbXPFsF5nFZvGnQtsBE6J4gGm5NfKEMVg9vcZMkfZ5opWvM5H0srXuT/Ddp0H0d7fAbZGsRFiQ6/xaAoovw9cI2kLRRfxXzJ9HnAImEYxRPBVSf8mz10WEZ8C/kO+Lh/eJh+xzT+g+IfvAv4M+L8UD+Mc0F4xQ2SgbYZhvs6SPgr8EPiDiKjVG23InjyN0IA2Q+te5yNW0Udaq1znWobtOg+0vZLOpthC/cuVpD6yDfoaj5qAEhG/jIgFETEXeIBibBmKOZS/joj3cyjm78ihmIh4Pb/uB+5n+IcO+mxzRPRGxB9GxJyIWAycBHRTe9+ZVm3zsF5nSeMo/gP+ZUT8KJPfzK5/ZZhlT6YPZn+fVm1zK1/nI2nl63xEw3WdB9peSTOAR4ArIqLy96+h13jUBJTKSgtJY4CbgO/mqZ3AfBU+ApwP/DKHZj6WZcYBn+fDfV+a2mZJv5ZtRdJvAb0R8VLU3nemJds8nNc5r8ldwMsR8e3SqfKePOX9dQazv09LtrnFr3OfWvw6H6meYbnOA22vpJOAnwA3RsTfVTI3/BoPdja/lV8Un4x3A+9TROArgesoVkL8PfANPryp86PAX1FMVL0E/Pf4cBXHFuAXee5/kqtlWqDNM4FXKCbinqB4Emilng6KX+B/AO6olGnVNg/ndaZYlRP5Xs/l67PAZIoFA935dVKpzNfyWr5CafXLcF3nRrW5Da7zDooFHu/l79LsNrjOv9Lm4brOA20vxYe7fy7lfQ44udHX2HfKm5lZQ4yaIS8zMxtaDihmZtYQDihmZtYQDihmZtYQDihmZtYQDihmZtYQDihmZtYQDihmZtYQ/x/rFzgxQKYDrwAAAABJRU5ErkJggg==\n", 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" + ] + }, + "metadata": { + "needs_background": "light" + }, + "output_type": "display_data" + } + ], "source": [ "yearly_incidence.plot(style='*')" ] @@ -314,9 +2397,55 @@ }, { "cell_type": "code", - "execution_count": null, + "execution_count": 17, "metadata": {}, - "outputs": [], + "outputs": [ + { + "data": { + "text/plain": [ + "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": 17, + "metadata": {}, + "output_type": "execute_result" + } + ], "source": [ "yearly_incidence.sort_values()" ] @@ -331,9 +2460,32 @@ }, { "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", + "text/plain": [ + "
" + ] + }, + "metadata": { + "needs_background": "light" + }, + "output_type": "display_data" + } + ], "source": [ "yearly_incidence.hist(xrot=20)" ] @@ -364,7 +2516,7 @@ "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..03afd928708035fc61b771e4b3087be52bf074bf --- /dev/null +++ b/module3/exo1/incidence-PAY-3.csv @@ -0,0 +1,1935 @@ +# @source="réseau Sentinelles, INSERM, Sorbonne Université, http://www.sentiweb.fr", @meta={"period":[198444,202145],"geo":["PAY","1"],"geo_ref":"insee","indicator":"3","type":"all","conf_int":true,"compact":false}, @date=2021-11-18T16:11:45+01:00 +week,indicator,inc,inc_low,inc_up,inc100,inc100_low,inc100_up,geo_insee,geo_name +202145,3,25786,20362,31210,39,31,47,FR,France +202144,3,19406,15338,23474,29,23,35,FR,France 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